American Association of Equine Practitioners ECONOMIC …...American Horse Council estimated the...
Transcript of American Association of Equine Practitioners ECONOMIC …...American Horse Council estimated the...
American Association of Equine Practitioners
ECONOMIC REPORT
4_1_2019
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OBJECTIVE
The American Association of Equine Practitioners (AAEP) partnered with the American
Veterinary Medical Association (AVMA) early in 2016 to produce a survey that explored the
economics of the equine segment of the veterinary profession. As of December 31, 2017, there
were 110,531 veterinarians in the United States, and a total of 117,735 veterinary positions
that were being worked in.1 The equine sector is currently estimated at 5.7 percent of the total
number of private practice positions in the United States. Of the 117,735 U.S. veterinary
positions, 71,393 are private clinical practice, and 4,043 of these positions are positions in
equine practice. An additional 4,220 positions are in mixed animal practice (“Market Research
Statistics: U.S. Veterinarians 2017,” 2018).
The recession of 2008, coupled with changes in the equine industry, had a negative effect on
equine practices (Blach, 2015), but little economic data were available to measure the impact
of the economic downturn on the economics of equine veterinary practice. The objective of the
AVMA-AAEP 2016 Survey of Equine Practitioners was to collect data to analyze the economics
of the equine veterinary industry as well as answer important questions about the profession,
including:
1. What does this population look like?
What are the current demographics of the equine veterinary profession in the United States?
What does the current workforce look like? What is the educational cost of becoming an equine
veterinarian? How much student loan debt are equine veterinarians carrying?
1 Veterinarians may hold more than one position.
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2. How do the multiple sectors of equine practice differ?
How do sectors of the equine veterinary industry differ in their business models? Are there
differences in economic performance between sectors? Does associate and owner
compensation methodology differ between sectors?
3. What is the current state of transitions of ownership in equine practice?
What is the current state of ownership entry/succession planning by practitioners?
4. What is the impact of internships on the profession?
What is the value of an equine internship? What do the current internships typically look like
for participants and practices? Do graduate veterinarians feel prepared by their education as
they begin their careers? What expectations do employers have for new associates? What
reasons may emerge to suggest why young equine veterinarians are leaving the profession?
5. What is the current state of health of equine practitioners?
How healthy are equine practitioners? How risky is the profession? Where do the risks lie?
This report outlines the results of the AVMA-AAEP 2016 Survey of Equine Practitioners, with
inclusion of data from the Equine respondents of the AVMA 2016 Census of Veterinarians, and
contrasts these data with those of all U.S. veterinarians responding to the AVMA 2016 Census
of Veterinarians, the annual general membership survey. Through understanding the current
economic environment, efforts to improve the experiences of equine practitioners and the
economic outcomes in equine practice may be more effective.
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INTRODUCTION
Veterinarians identifying as working with equids, whether in an exclusive or predominant
equine practice, or in a mixed animal practice, are a minority in the profession. The equine
segment of the veterinary profession is currently estimated at 5.7 percent of the total number
of private practice positions in the United States. As of December 31, 2017, 71,393 of the
117,735 U.S. veterinary positions are private clinical practice, and 4,043 of these positions are
positions in equine practice2. An additional 4,220 positions are in mixed animal practice
(“Market Research Statistics: U.S. Veterinarians 2017,” 2018).
Economic trends in the equine industry, and thus the equine veterinary industry, were
predominantly negative in the years following the recession of 2008. Based on AVMA data
(2016), it is estimated that the U.S. horse pet horse population declined between 2011 and
2016, and according to the USDA, the horse population on farms that reported at least $1,000
in annual sales declined by 10 percent (National Agricultural Statistics Service, 2012). The
American Horse Council estimated the U.S. horse population at 7.2 million in their recently
released report (American Horse Council Foundation, 2018), down from 9 million in 2004
(American Horse Council Foundation, 2005). Youth participation in equine activities has
declined, according to the 2014 Brakke Equine Market Mega Study. The proportion of horse
owners aged 18 to 34 has declined from 24 percent in 2006 to 11 percent in 2013, according to
Brakke (JAVMA News, 2014). Data from the Merck-Henry Schein National Equine Veterinary
Economic Study also showed a 6.7 percent reduction in the annual income of equine
veterinarians during the period of 2006 to 2012. In contrast, companion animal exclusive
veterinarians saw an increase in annual income of 22.7 percent during the same period (Blach,
2017).
2 Veterinarians may hold more than one position.
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Historically, many veterinarians who work with horses in the early phases of their careers have
opted to switch to other career paths within the first four years after graduation. AAEP
membership data from 2008 to present show that almost 33 percent to 50 percent (depending
on the year) of new veterinarians who are members of the AAEP at the time of their graduation
are no longer members just four years later. This suggests that these doctors no longer work in
the equine field. Gathering data about the current state of the equine veterinary industry will
allow stakeholders to make informed decisions and initiate more effective efforts to strengthen
the profession. The results of this study will help facilitate the AAEP’s strategic direction, and
assist in the creation of new strategies and policies to achieve identified goals.
By conducting a comprehensive analysis of internal resources, the factors affecting these
resources, and the environment in which the industry operates, a detailed picture of the
present reality emerges. The general conditions of the local, regional, and national economy
and the characteristics of the equine veterinary market – including the structure of the
profession (the number and size of practices), the level of competition existing within the
profession and between veterinary and non-veterinary service providers, and the institutional
rules that govern the interactions between organizations or individuals within the market
regions – all factor into this analysis.
The success of the equine veterinary profession is strongly linked to the economic conditions of
the equine industry and the agricultural industry as a whole. Equine veterinary practices
provide services to horse owners. The demand for these services is related to the number of
horses in the area served by the practice, the health needs of these horses, and the willingness
and ability of horse owners to pay for the available services of the equine practitioners. The
willingness and ability to pay for veterinary services is generally related to the income level of
households. Thus, a change in household income of horse owners would be expected to affect
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the demand for equine veterinary services. A brief economic downturn might not have
significant impact on horse owner income, but if the downturn persisted it would be harmful to
the horse owners’ financial health and, in turn, the revenue of equine veterinary practices.
The Current Face of Equine Practice
Of the total number of AVMA member veterinarians in the U.S. in 2017, 60 percent were
female. In the equine veterinary field, there were 47 percent males and 53 percent females
(“Market Research Statistics: U.S. Veterinarians 2017,” 2018). Women are projected to grow to
71 percent of the veterinary workforce by 2030. Women constitute 81 percent of new
graduates, whereas the older workforce nearing traditional retirement age is predominantly
male (AVMA, 2013). This report elucidates the current gender-related data that are changing
the face of equine veterinary practice.
Participation in a year-long internship program after graduation has been identified by the
AVMA Economics Division as a negative factor in career income generation and outcomes for
the general population of veterinarians (Nolen, 2015). In the equine veterinary field, however,
an internship is often considered essential for employment. This study sought to explore the
reasons for this perspective and to describe the competencies that practice owners expect of
new graduate hires.
With starting salaries that lag behind other segments of the veterinary industry, equine
veterinarians with high educational debt raise significant concerns. The debt-to-income ratio
and other parameters of educational debt are explored in this report to outline the current
reality for this younger generation of equine practitioners.
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A 2014 British Equine Veterinary Association (BEVA) study raised concerns about the
occupational danger of an equine veterinary career (BEVA, 2014). Their findings concluded that
equine practitioners carry the highest risk of injury of any civilian occupation in the United
Kingdom. The AVMA-AAEP 2016 Survey of Equine Practitioners offers a view of the physical and
mental wellness of equine veterinarians in the United States.
Like other sectors of private practice within the veterinary profession, the equine veterinary
industry is facing competition from non-veterinary parallel service providers that adversely
affects revenue. These competitors may provide services in fields that were once exclusively in
veterinarians’ purview . Pharmaceuticals are also widely available from sources other than
veterinarians. Some equine owners rely on these alternatives at the expense of traditional
veterinary service providers. This report explores the impact of these parallel service providers
in equine veterinary medicine.
A Diversity of Practices
Equine veterinary practice is unique in that many different sectors exist within the equine
veterinary profession; while many veterinary firms engage in general equine practice, others
concentrate only on a particular discipline such as Western performance, Thoroughbred racing,
or reproduction. This study reports on how the economic results and practice business models
differ between these equine sectors.
Equine practices in the United States vary in size from solo practices to large hospitals
employing more than 10 doctors. Sole proprietorships (practices owned by a single
veterinarian) are the most common entity, consistently representing approximately 40 percent
of the AAEP membership, followed by two-doctor practices. The delivery of care in equine
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practices ranges from strictly ambulatory service to small haul-in clinics to large hospitals
providing advanced surgery and intensive treatment. This report compares and contrasts these
varying business models.
Owners of sole proprietorships, partnerships and equine veterinary corporations must plan the
eventual sale of their practice equity, and some may depend upon this asset to fund
retirement. Many practice owners, particularly sole proprietors, have been shown to lack
confidence in their ability to sell their practice (Grice, 2016). This report surveys respondent
attitudes regarding practice ownership and analyzes other factors that impact practice
transitions.
The Role of Equine Practice in the Economy
Equine veterinarians are an important part of the general economy in some communities,
especially in those areas with a significant equine industry presence. To better understand how
the profession is woven into the economy, an economy-wide impact analysis was conducted for
the equine profession. An input-output analysis was performed using IMPLAN software, a
program that facilitates observing economic linkages between the business under study and
other businesses in the area of analysis. The input-output analysis relies on a specific type of
algorithm that identifies the share of inputs purchased by equine veterinary practices from all
other industries, the share of total output from equine veterinary practices that is consumed by
other industries, and the economic activity created as a result of the expenditures from those
working in and providing services to this profession. The impact analysis in this report
considers how the activities within an economy would differ with, and without, equine
veterinary practices.
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Organization of this Report
This AVMA-AAEP 2016 Survey of Equine Practitioners report is divided as follows: Section I
provides an overview of the state of the U.S. Economy. Section II provides an overview of the
demographics of the equine veterinary medical profession. Section III describes the market for
veterinary education. Section IV offers information on the market for veterinarians. Section V
provides information on the market for veterinary services. Section VI presents a portrait of
equine veterinary practice, and Section VII relates findings from the economic impact analysis
of equine veterinary practices.
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EXECUTIVE SUMMARY
Equine veterinary practice accounts for less than 6 percent of all veterinary private practice
types in the veterinary medical field. Veterinarians identifying as working with equids, whether
in an exclusively or predominantly equine practice, or in a mixed animal practice, are a minority
in the profession. Economic trends in the equine industry, and thus in the equine veterinary
industry, were mostly negative in the years following the recession of 2008. Based upon AVMA
data (2016) it is estimated that the U.S. horse pet population declined between 2011 and 2016,
and the horse population on farms that reported at least $1,000 in annual sales decreased by
10 percent (NASS, 2012). AVMA data also showed a 6.7 percent reduction in the annual income
of equine veterinarians during that same period, while companion animal exclusive
veterinarians saw an increase in annual income of 22.7 percent (Blach, 2015). Analyzing data
gathered about the current state of the equine veterinary industry through the AVMA-AAEP
2016 Survey of Equine Practitioners will allow stakeholders to make informed and more
directed efforts to strengthen the profession.
This study of the economics of equine practice is a joint effort of the AAEP and the AVMA. The
purpose of this effort is to gain an understanding of common and unique attributes of equine
veterinary practices and practitioners compared to the general veterinary profession and to
identify challenges facing the equine veterinary profession so that these issues can be
addressed with maximal effect.
In this report, the following datasets were analyzed:
1. The AAEP membership database was utilized to develop aggregate gender, age and ZIP code
information. This database can be found in the “Demographics “and “Geographic Distribution
of Equine Practitioners” sections of this report. These data are referred to as “AAEP Members”
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in this section of the report. The number of observations in the AAEP membership database
was N=7,432.
2. The AVMA-AAEP 2016 Survey of Equine Practitioners, which comprises survey responses from
AAEP members, is referred to as “AAEP” throughout the report. The number of AAEP
observations (respondents) was N=975.
3. The AVMA’S 2016 Census of Veterinarians, which comprises survey responses from AVMA
members, is referred to as “AVMA” throughout the report. The number of AVMA observations
(respondents) was N=2,545.
4. The combined dataset of AAEP (N=975) and the self-identified equine practitioners from the
AVMA (N=81), is collectively called “Equine.” The number of such combined Equine
observations (respondents) was N=1,056.
Dataset Observations (n)
AAEP Membership database 7,432
AAEP - secondary sample 975
AVMA - comparative sample 2,545
Equine - main sample (81 equine respondents from AVMA + 975 AAEP)
1,056
This report includes information on general economic conditions, demographics, the market for
veterinary education, the market for veterinarians, the market for veterinary services, a portrait
of equine veterinary practice, and an analysis of the impact of equine practices on economic
activity in the United States.
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GENERAL ECONOMIC CONDITIONS
Recent economic data for the United States show a low annual rate of growth. Close analysis of
the Conference Board’s U.S. Leading Economic Indexes reveals that while the United States has
been in an expansion since the middle of 2009, there are some indications that economic
growth may be slowing. Slower growth may limit the demand for veterinary services and result
in reduced veterinary incomes. Another recession may occur within the next several years.
DEMOGRAPHICS OF EQUINE PRACTITIONERS
The descriptive statistics of equine practitioners include the demographic characteristics of age,
veterinary medical college attended, gender, ethnicity, regional distribution, living and work
location, and marital status.
What are the current demographics of the equine veterinary profession in the United States?
Most equine practitioners who responded to this survey graduated from one of the 30 U.S.
AVMA accredited veterinary schools (90 percent Equine, 85 percent AVMA) (Table 2). Of
Equine respondents, approximately 60 percent graduated before 2007, and 40 percent
graduated after 2007 (Figure 9). There was a higher percent of AAEP members over the age of
51 years (43 percent) than Equine respondents (38 percent) or AVMA respondents (26.5
percent) in the same age group (Figure 10). The mean age of all three groups was
approximately 46 years (AAEP Members: 49; Equine: 46; AVMA: 43). The distribution of
respondents across years of graduation suggests that equine practitioners remain in practice
longer than the general AVMA practitioner pool.
Many variables affected the data that were mined by the survey. The group of respondents
ranged in age from veterinarians in their late 20s to those in their 80s. Participants ranged from
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veterinarians with less than one to more than 60 years of clinical experience. The survey results
should be interpreted with these facts in mind, as vast changes have occurred in the equine
veterinary profession, the equine industry, the economy and the culture in the past 60 years.
Of particular note is the age and experience distribution of male and female equine practitioner
respondents. Thirty years ago, women represented less than 10 percent of all equine
veterinarians, while today women comprise the majority of new graduates.
The male and female cohorts in the Equine group were very different. Males had an average
age of 55 years, and an average of 29 years of experience. Many of these Equine males had
more than 40 years of experience as equine veterinarians. In contrast, the average age of the
females was 39 years and they had an average of 12.3 years of experience. Many of the Equine
women veterinarians had less than 10 years of experience (median was 9 years), with almost 60
percent of the female respondents having less than 10 years of experience. The variance in age
and experience between the male and female groups should be borne in mind when
interpreting survey data.
Although females constituted the majority of Equine respondents (58 percent female, 42
percent male) (Figure 11), the inverse relationship between gender and age was notable.
Eighty-two percent of Equine respondents over 60 years of age were male, while 83 percent of
those less than 30 years of age were female (Figure 12). The shifting gender distribution within
equine practice undoubtedly impacted some of the economic differences noted in this report
and may have also had an effect on data involving equine practice ownership. For example, the
differing percentage of male versus female practice owners noted in this report is likely related
to higher numbers of the older (mostly male) Equine respondents acquiring ownership status
due to their longer years in their careers. This ownership gender disparity may change in the
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future as females serve more years in the profession, but there is uncertainty as well about
generational changes associated with risk tolerance and priorities (Figure 1 and Figure 2).
Figure 1: Distribution of Equine Respondents' Age by Gender
Figure 2: Distribution of Equine Respondents' Years of Experience by Gender
0
10
20
30
40
50
20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
# of
Res
pond
ents
Age
Distribution of Equine Respondents' Age by Gender
Male (n=434) Female (n=610)
0
20
40
60
0 5 10 15 20 25 30 35 40 45 50 55 60 65
# of
Res
pond
ents
Years of Experience
Distribution of Equine Respondents' Years of Experience by Gender
Male (n=429) Female (n=602)
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Of the Equine respondents, 65 percent were in exclusively equine practice, 12 percent were in
mixed practice and 10 percent were in academia (Figure 13). Of these veterinarians, 95 percent
were Caucasian (Figure 14). The most ethnic diversity was seen in equine practitioners less than
40 years of age, suggesting that cultural and socioeconomic barriers may be declining for entry
to equine practice (Figure 15).
The United States Postal Service allocates ZIP codes for regions 0-9 in the United States (Figure
16). These regions are not only different geographically but were also found to have significant
differences in past analysis by the AVMA regarding debt, income, unemployment and
underemployment.
Representation of equine practitioners was highest in the West Coast (15 percent) and
Southeast regions (12 percent) of the U.S., while the northern Midwest and central states (both
approximately 6 percent) had the least representation among Equine respondents (Figure 17).
This distribution may be related to a variety of factors such as population density, the
willingness and ability of horse owners to support equine veterinary services, and seasonal
challenges inherent to the equine industry.
The majority of Equine respondents (70 percent) were married, with 22 percent single, 6
percent divorced, and the remainder separated or widowed. These numbers were similar to
those of AVMA respondents (75 percent married, 18 percent single and 6 percent divorced),
suggesting that equine practice marital status is comparable to the veterinary profession at
large (Figure 19).
Higher population density in some areas may play a part in equine practice locations; however,
51 percent of equine practitioners lived in a rural environment, 40 percent in suburban areas,
and 9 percent in cities (Figure 18). Most Equine respondents were happy with their living
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environments, although 17 percent of the suburban dwellers would move to a rural location if
opportunity arose (Table 3).
THE MARKET FOR VETERINARY EDUCATION
The report on the market for veterinary education includes the supply of veterinary education;
the supply of seats at AVMA-accredited schools of veterinary medicine; outcomes of equine
veterinarians following graduation and/or participation in externships, internships and
residencies; expectations of veterinary students/recent graduates before entering the
profession; the most important skills desired by employers; equine veterinary student debt, and
the debt-to-income ratio (DIR) of equine veterinarians.
There are 30 AVMA-accredited veterinary colleges in the U.S., three AVMA-accredited
Caribbean colleges, 16 AVMA-accredited colleges in other countries, and many other non-
AVMA accredited veterinary colleges around the world. Recently, the number of applicants to
veterinary colleges has seen an increase, with 6,667 in 2016; 7,071 in 2017 and 7,507 in 2018
(Figure 20). The expected supply of seats at AVMA-accredited schools is expected to remain
constant at approximately 3,300 seats per year at the 30 U.S. colleges, 490 at the three
Caribbean colleges and more than 500 at the 16 U.S.-accredited foreign colleges (Figure 22).
Since 2000, the number of new veterinarians entering equine practice has declined linearly
from approximately 5 percent to about 1.1 percent in 2017 (Figure 24). More than 81 percent
of AAEP respondents participated in externships while in veterinary school (Figure 26), and
among Equine respondents, 5.7 percent were currently participating in an internship and 47.7
percent had participated in an internship previously (Figure 27). In contrast, the AVMA survey
sample showed only 26 percent of general veterinary practitioners had participated in an
internship, while 74 percent had not. This disparity between equine and general practitioners
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may be a result of the employment climate in equine veterinary medicine, an environment
where most available jobs require an internship or several years of clinical experience.
Internship experience has become a de facto entry requirement to equine practice in many
sectors of the industry.
What factors affect the decision of equine veterinarians to pursue an internship?
Many veterinary students do not have the opportunity to hone their diagnostic and technical
skills during veterinary school due to the high value of many equine patients, a low clinical case
load, and/or client attitudes. As a result, new graduates can rarely be seamlessly integrated into
an equine practice without significant mentoring and skill-building. Practice owners may have
neither the time nor inclination to take on this role, and over time, completion of an internship
has become considered nearly essential for successful employment in the equine veterinary
field. Data from this study show that respondents who completed an internship desired to
improve their clinical skills and practice better medicine. Rather than showing a lack of
confidence, as some have suggested, this may indicate a realization of the limitations of their
training and the need for focused skill building at the commencement of their career (Table 7).
The data show that most internships provided comprehensive and focused training
opportunities through clinical skills acquisition, case rounds, and close mentoring.
Internship responsibilities reported by AAEP respondents included primary on-call emergency
duty with mentoring available (82.1 percent), primary on-call emergency duty with no
mentoring available (16.9 percent), primary client communication (70.1 percent), case rounds
(68.2 percent), overnight treatment duty on a regular basis (60.9 percent), Journal Club (52.7
percent), hands-on procedural rounds designed specifically for learning a skill or technique
(31.6 percent), and radiology rounds (23.6 percent) (Table 8).
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More female Equine respondents (64.3 percent) reported participation in an internship than
Equine males (37.9 percent). In contrast, the AVMA sample reported an approximately equal
percentage of males (23.5 percent) and females (27.6 percent) who had participated in an
internship (Figure 28). Because 40.6 percent of all internships reported by Equine respondents
have been completed in the last five years (AVMA 29.5 percent), the markedly increased
percentage of females in this cohort may explain the apparent gender difference in
participation rates in the Equine dataset (Figure 29).
Equine respondents from graduation years 2012-2016 reported an average annual internship
stipend of $26,915 while AVMA respondents from the same graduation years reported an
average internship salary of $29,174 (Table 10). About one-third of AAEP respondents reported
receiving free housing as a part of their compensation package (Figure 32). Over time, the
number of benefits received by interns has increased, as has the percentage of interns receiving
them. In the past five years, 65.5 percent of AAEP interns reported receiving health insurance,
71.4 percent professional liability insurance, 75.6 percent continuing education expenses, and
75 percent professional licenses and association dues (Table 14).
Except for improving their understanding of business management, the majority of Equine
respondents reported that their expectations of their internship were met well to extremely
well (Figure 39). Fully three-quarters of respondents would participate in the same internship
again if given the option (Figure 40).
Many equine practices have created business models that rely upon the skills of interns to
provide after-hours evaluation of patients in hospital and ambulatory settings at a cost that is
less than that of employing experienced veterinarians. This mutually beneficial paradigm allows
older doctors to experience the satisfaction of teaching and mentorship while experiencing a
financial benefit and allows new graduates access to experienced practitioners’ clients and
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patients while benefiting from the experience of their employers. The employer gives of their
time and knowledge. The intern trades their hard work for valuable education and access to
experiences that they might otherwise not have the opportunity to share.
Of Equine respondents, 20.9 percent reported participation in a residency program at some
point during their veterinary career, compared to 13.0 percent of AVMA respondents (Figure
41). Of Equine respondents who desired to pursue a residency, over three-quarters either
completed a residency or at the time of the survey were participating in one (Figure 42).
Ninety-five percent of these residencies were in academic settings with just a few in private-
referral settings (Figure 46). Participation in residencies showed an increasing incidence from
2005 to 2014 for both Equine and AVMA respondents, followed by a sharp decline (Figure 43).
Surgery (44.3 percent), Internal Medicine (28.5 percent) and Theriogenology (11.8 percent)
were the most common specialties reported by Equine respondents (Table 20).
An inverse relationship was noted between graduation year and Equine respondents’
perception of how well their veterinary school education prepared them for practice. Among
the Equine respondents, 51.4 percent of those who graduated in 2012-2016 were satisfied
“moderately well,” “not too well” or “not well at all” with their veterinary education, compared
to 39.3 percent of AVMA respondents. Eighty-nine percent of Equine respondents who
graduated in 1967-1976 reported that their education prepared them “very well” to “extremely
well.” This percentage dropped in a linear fashion, with only 48.5 percent of Equine
respondents in graduate years 2012-2016 reporting the same (Figure 48). This trend line
parallels the variation in respondent mental health found in this study, with a linear decline in
overall mental health with more recent graduation (Figure 122). Factors that may contribute to
the decreased satisfaction with educational preparedness could include markedly increased
amounts of information that must be learned during the four years of veterinary school
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curriculum, fewer opportunities to see clinical cases due to the proliferation of private-referral
hospitals, licensing requirements to be competent in all species, and declining emphasis on
equine skills as the equine population has dropped. There was, however, no data collected in
this survey to capture reasons for the decline in educational satisfaction.
AAEP respondents opined that the entry level clinical skills considered essential to enter the
profession included the ability to: diagnose and treat a foot abscess (90.6 percent), repair
simple lacerations (90.4 percent), work up, treat and make recommendations for a colic case in
the field (88.7 percent), and perform physical and ophthalmic exams (87.6 percent). Diagnosis
of uncomplicated lameness with diagnostic nerve blocks, obtaining radiographs of limbs, setting
up preventative health protocols, and placing intravenous catheters and subpalpebral lavage
systems were expected as entry level skills by more than 80 percent of respondents. Over 70
percent of AAEP respondents also expected new practitioners to be able to remove shoes,
perform basic dental procedures, perform castration on a recumbent patient under general
anesthesia, and complete routine reproductive procedures such as a Caslicks and uterine
culture. Over 60 percent expected new practitioners to be able to induce and recover a patient
in the field with intravenous anesthesia, ultrasound a mare to diagnose a singleton pregnancy
at 16-18 days post ovulation, and obtain samples from or inject substances into synovial
structures such as joints or tendons. Skills in more advanced imaging, diagnostic sampling and
surgery were expected by less than half the respondents (Table 22). Expectations for the
specific entry level clinical skillset differed between respondents who had been in practice for
more than 20 years and those in practice for fewer than 20 years (Table 23).
AAEP respondents were also asked to rank 10 workplace competencies on a scale of one to 10
for their importance for new associates (Table 24). In general, people-skills ranked higher than
organizational, technical or writing skills. People-skills were cited as the most important
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competency by 63.9 percent, followed by client communication (21.2 percent), and customer
services skills (4.8 percent).
AAEP membership data show that many young veterinarians fail to renew their AAEP
membership four years from their graduation date from veterinary school, and that the trend is
slowly increasing (Figure 49). Starting with the Class of 2000, almost 40 percent of former AAEP
members dropped their membership within four years of their graduation date. Of the Equine
respondents who were currently not employed in equine medicine and reported the number of
years they were employed as an equine veterinarian in their first job, 67.4 percent were in the
equine profession from zero to five years after graduation, 14.6 percent six to 10 years, 5.6
percent 11-15 years, and 12.4 percent 16 years or more (Figure 50). When the 89 respondents
who reported leaving the equine veterinary sector were analyzed by graduation year, 100
percent of respondents who graduated within the last five years and subsequently left equine
practice did so within five years of graduation, followed by 91.3 percent from 2007-2011, and
27.8 percent from 1987-1996 (Figure 51).
What factors affect starting salaries for equine veterinarians?
Starting salaries in the equine veterinary field lag behind those offered in other types of private
practice. AVMA respondents reported higher post-internship salaries than Equine respondents
on average, except for male Equine respondents who graduated in the period 2012-2016; these
graduates reported an average starting salary of $61,867 compared to AVMA males who
reported $61,810 (Table 15). In contrast, female Equine respondents who graduated from
2012-2016 reported an average starting salary of $51,109 compared to AVMA females who
reported $70,452.
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Associate veterinarians starting their careers in equine practice face several challenges.
Because of the high dollar value of many of the horses that they encountered as patients in
veterinary school, many were not allowed the opportunity to practice hands-on clinical skills,
communicate with owners, or develop independent case management abilities. Data show that
survey respondents value a comprehensive list of entry level skills that many job candidates
may not possess (Table 22 and Table 23). In addition, horse owners are frequently very bonded
to a specific veterinarian and are often reluctant to allow care by a new doctor.
These realities create an environment where new associates have difficulty producing sufficient
production revenue to support robust starting salaries. Many of these young doctors struggle to
produce sufficient income to support the total cost of their compensation for several years, if
not longer. Most practice management resources indicate that the total cost of compensation
(including salary, benefits, payroll taxes, etc.) for associate veterinarians should not exceed 25
percent of collected gross revenue production. When equine practice owners determine
starting salaries for new graduate associates, they must determine how much of their profit
they are able and willing to invest in mentoring these young veterinarians during that period
until they can become self-supporting within the practice.
If a new graduate was able to bring in personal gross service revenue from production of
$200,000 in their first year of employment after internship, the Equine female respondent’s
average salary of $51,109 would represent 25.5 percent of revenue, even without considering
the additional costs of employment. The Equine male respondent’s average starting salary of
$61,810 would represent 30.9 percent of production before considering other relevant
expenses.
The study data indicate that the median personal gross revenue from production for practice
owner Equine respondents was $385,832, and the mean personal gross revenue from
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production for associates was $356,500. For AVMA respondents, the median personal gross
revenue from production was $500,000 for owners and $450,000 for associates (Table 156).
Among those in their first five years of practice, the median personal gross revenue for Equine
respondents was $300,000 and for AVMA respondents was $410,000 (Table 157).
With the current sluggish growth or outright contraction of the equine industry (dependent on
geographic region) , there is also less growth in demand for services. Mature practitioners
wishing to prepare for a transition out of practice often must transfer some of their own work
(and the associated revenue production) to younger associates to create an exit strategy. In
some cases, there may simply not be enough revenue produced to support two veterinarians,
but orderly transition and emergency coverage demand the addition of another practitioner.
Under these conditions, robust starting salaries are often impossible.
The gender disparity in starting salaries after internship for Equine respondents in the last five
years is approximately $10,000, or 16.2 percent lower for females (Table 15). This negative
finding reflects the broader issue across industries that also find a gender wage gap between 8
percent-20 percent in the United States (Graf, Brown, and Patten, 2018). Scarcity increases
perceived value; in equine veterinary medicine, this disparity among recent graduates may
arise in part because of the low numbers of males entering the profession compared to
females. In addition, 60 percent of current equine practice owners are male, which may
influence their decision to hire male associates over females, a decision that could be based on
the status quo bias (the tendency for people to like things to stay relatively the same), resulting
from the exposure effect (the tendency for people to like things merely because they are
familiar with them). Gorman (2005) has looked at many aspects of gender-related stereotypes
on work environment. The data report that, on average, Equine male respondents add an
additional $477,929 to revenue while Equine female respondents add an additional $346,638;
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this disparity may also be influencing the gender wage gap identified (Table 158). However, it is
critical to note that the average age of male versus female respondents is 55 years versus 39
years, respectively, and so the average revenue increase is likely being influenced by experience
and skills gained over time.
What factors affect the debt of equine veterinarians?
Data show that the educational debt of new equine veterinarians is lower than those entering
other types of practice. Average educational debt of all AVMA graduates was $142,732 and
those entering equine practice was $131,325 in 2016 (Figure 54). This difference may be due to
students who are interested in equine practice having awareness of the lower starting salaries,
and subsequently making more careful financial choices. It is also possible that it is more
affluent students who are choosing equine practice. The data show that about 30 percent of
graduates who entered equine practice had no debt, compared to about 20 percent who
entered companion animal practice.
More than two-thirds (70.8 percent) of Equine respondents incurred debt from their veterinary
medical education (AVMA: 79.2 percent). Overall mean student debt from post-secondary
education of Equine respondents for all graduating years was $92,918 compared to AVMA
respondents who reported an average of $114,202 (Table 27). The average debt among Equine
respondents who graduated within the last five years was $168,710. The average debt among
Equine respondents who graduated 6-10 years ago was $125,374. From 2001 to 2015 mean
student veterinary debt of new grads has more than doubled (Table 29).
The mean educational debt of the 437 Equine respondents who did internships ($109,865) was
considerably higher than the 326 equine graduates who did not ($70,201) (Table 31). It is
uncertain why this would occur. It is possible that graduates of veterinary schools with higher
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tuition and attendance costs are more likely to pursue internships. However, the 139 Equine
respondents who undertook residency training reported lower mean student debt than those
who did not pursue specialty training. One explanation is that those planning a residency
training were exceptionally frugal or perhaps had more financial support from their families.
There is an increasing gap between student debt totals and average professional income. Most
Equine graduates had little to no pre-veterinary student debt (33.1 percent and 61.3 percent,
respectively) (Figure 55). This was true no matter what decade they graduated in (Figure 56).
However, 70.8 percent of Equine respondents reported that they incurred debt during
veterinary school, and 53.5 percent of these veterinarians reported they were still paying off
debt. Of those still paying on educational debt, 13.2 percent said that more than 30 percent of
their compensation was used to service debt. An additional 12.2 percent reported that they
were utilizing 21-30 percent of their compensation toward debt, with an additional 23.5
percent of respondents who reported spending 11-20 percent (Figure 57). Of those who
graduated within the last 10 years, the mean percentage of compensation used to repay
educational loans was 20 percent (Table 28).
How does the Debt to Income Ratio (DIR) of equine vets compare to other veterinarians?
The gender weighted average DIR of new veterinarians who work full time in equine medicine
was 2.48 (median was 2.10) in 2016. The weighted average DIR of all new veterinarians working
full time in 2016 was 1.71 (median was 1.62) (Table 43). According to financial professionals,
the level of debt-to-income that can be serviced in professional fields without posing serious
financial stress is 1.4:1.
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THE MARKET FOR VETERINARIANS
The AVMA/AAEP survey queried respondents on their professional income and benefits. The
results were used to assess the net present value of an equine veterinary professional
education. Employment status and work schedule were determined, and respondents were
asked to rate their satisfaction with their current position, working hours, on call
responsibilities, income, and geographic location. The section had multiple questions on health
and wellness. Respondents rated their physical and mental health, and provided historical data
about work related injuries, including the effect of injury on their work and daily activity. The
section concluded with the ProQOL survey instrument, a standardized set of questions designed
to measure three subscales of wellbeing: compassion satisfaction, burnout and secondary
traumatic stress.
The data were evaluated for statistical significance and trends relating to respondent gender,
age, year of graduation, veterinary college, and level of education. Additional filters included
participation in internship or residency, board certification, income level, and whether the
respondent was a practice owner, practice associate or an employee at a university or other
institution. The specific practice sector and geographic location that each respondent worked in
was examined, as was the business model and size of their workplace.
Income and the Gender Gap
Mean professional income for Equine respondents was $99,000 annually, with practice owners
reporting $118,000 and associates reporting $78,000. In comparison, AVMA respondents had a
mean income of $112,000, with $159,000 reported for practice owners and $90,000 for
associates (Figure 59). Income levels were noted to rise in a roughly linear fashion with years of
experience; equine veterinarians who had been in the workplace less than five years reported
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the lowest mean incomes while those who had 30 or more years of experience had the highest
(Table 45).
Practice ownership had a statistically significant impact on professional income (p-value <.001)
among both the Equine and AVMA respondents. Mean annual income reported for practice
owners and for non-practice owners differed by about $40,000 for Equine respondents and
about $69,000 for AVMA respondents (Table 52). Participation in an internship was associated
with lower mean income levels among peer graduation years (Figure 62), but board
certification was associated with higher mean income levels (Table 53). Employment in the
racing, reproduction or performance horse sectors was also associated with higher income
levels (Table 54).
Separating mean income by gender, in all comparisons the mean income of male respondents
exceeded female respondents. Female Equine practice owner respondents had a mean income
that was $55,000 less than male owners ($85,000 female vs. $140,000 male). Among AVMA
respondents, male owners had $66,000 more in mean income ($186,000) than their female
counterparts ($120,000). A $24,000 difference between male and female Equine respondent
associates, and a $15,000 difference between male and female AVMA respondent associates
were measured. Again, it is essential to recall the age and experience differences between the
male and female cohorts when observing these data (Figure 59).
For both Equine and AVMA respondents, the difference in mean income between genders was
large and statistically significant (Equine: p-value <.001; AVMA: p-value <.001) (Table 49). The
highly significant wage gap that was noted between male and female respondents was
calculated by multiple linear regression analyses to be about $30,000 for Equine respondents
and $50,000 for AVMA respondents (Table 55). It must be noted that the male Equine
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respondents had a mean of 29 years of experience versus the female Equine respondents, who
had a mean of 12.3 years of experience in this sample.
While it is impossible to know with certainty why this gap exists, according to data that look at
the general population, a wage disparity of 20 percent is observed (Graf, Brown, and Patten,
2018). According to the Pew Research Center, the gender gap in pay has narrowed since 1980,
particularly among younger workers, it still unfortunately persists. In 2015, women earned 83
percent of what men earned, according to a Pew Research Center analysis of median hourly
earnings of both full- and part-time U.S. workers. Based on this estimate, it would take an extra
44 days of work for women to earn what men did in 2015. By comparison, the U.S. Census
Bureau found that women earned 80 percent of what their male counterparts earned in 2015
when looking at full-time, year-round workers only. However, for adults ages 25 to 34, the 2015
wage gap is smaller. Women in this group earned 90 cents for every dollar a man in the same
age group earned (Graf, Brown, and Patten, 2018).
Factors that may also contribute to the wage gap in veterinary medicine, particularly in equine
practice, include the variance in number of years of experience between males and females
(male Equine respondents had a mean of 29 years of experience versus the female Equine
respondents, who had a mean of 12.3 years of experience in this sample). According to AAEP
leadership, there may be a perception that females produce less revenue for a practice than
equivalently experienced males, for a variety of reasons. Possible contributors to these
perceived reasons may be family responsibilities, confidence, or efficiency. In addition, in recent
years some leaders in the equine veterinary industry have observed there seems to be a strong
trend in the marketplace for new graduates to start out at a practice as an associate and then
start a solo practice on their own without sufficient knowledge of business. Unsure of how to
set prices but eager to build their client base, they may charge reduced prices or may comply
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with unreasonable requests to work pro bono. It is postulated that due to geography, cases
cannot always be seen in the most efficient manner and instead these veterinarians may feel
compelled to give phone advice for free. In addition, solo practices may struggle to afford
diagnostic equipment that is not used every day but is essential to meet client expectations.
Profitability (and thus income) could be adversely affected by these factors. These factors may
contribute to the reported lower earnings for females, who make up the majority of recent
graduates.
Mean income of the AAEP respondents was shown to vary by size of practice, with those
employed in larger practices earning more than those employed in smaller practices (Figure
61). Data showed that veterinarians who worked in academia reported higher mean incomes
than those in private practice. AVMA respondents who worked in Industry reported the highest
incomes (Table 50). When the distribution of mean income of Equine respondents who
participated in an internship and those who didn’t was plotted by graduation year (Figure 62),
there was very little difference in mean incomes reported by graduates in recent years. There
was nearly $30,000 more income reported by Equine respondents with residency training
compared to those who did not complete a residency (Table 48).
For both the Equine and AVMA sample, the variation in mean incomes between the 10 regions
was substantial (Table 51). The region with the highest mean professional income in the Equine
sample was Region 4 ($115,410). Kentucky is located in Region 4, and Lexington, Ky., is known
as the “Horse Capital of the World” because it is heavily populated with horses and large
Thoroughbred breeding operations. Region 5 had the lowest reported Equine mean income at
$83,640. The mean income that veterinarians reported they earned was statistically significant
(p-value = .011). with respect to the primary equine sector served.
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What benefits are offered?
More than 75 percent of Equine respondents received the benefits of continuing education
expenses, licensure, liability insurance, and association dues. A little over 60 percent were
granted discounted veterinary care and continuing education leave. Health insurance (52.8
percent) and paid vacation (51.4 percent) were received by a little more than half of Equine
respondents. Less than 10 percent were granted paid maternity or paternity leave (Table 56).
Do equine veterinarians have retirement assets?
Among AAEP respondents, 63.8 percent reported having assets for retirement. The primary
asset reported was a combination of assets (36.2 percent) followed by a 401(k)/Keogh/IRA fund
(31.3 percent) (Table 58). Nearly 80 percent reported having a 401(k)/Keogh/IRA account (Table
59). Nearly 29 percent of these respondents indicated they were either very or extremely
confident in their financial preparation for retirement, while 34.5 percent indicated they were
not very or not at all confident, and 36.8 percent of respondents were moderately confident.
Are equine veterinarians having families?
Regarding family status, just over half of the Equine respondents (52.1 percent) indicated they
had children during their professional career. Another 31.4 percent of respondents reported
that they did not have children, nor did they plan to have children during their professional
career, while 16.5 percent of respondents did not currently have children but plan to have
children in the future during their professional career (Figure 64). With regard to available
maternity or paternity leave, 40.1 percent of Equine respondents had no maternity/paternity
leave offered, and 31.8 percent had one-two months (Figure 66). Of those with leave, 41.2
percent of respondents reported that none of the maternity or paternity leave was eligible for
compensation, and 34.6 percent reported one-to-two months of leave was eligible for
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compensation (Figure 67). Almost three-quarters of AAEP respondents perceived that policy
relating to maternity or paternity leave was not well addressed in their employment contracts
(Figure 70).
What is the Net Present Value (NPV) of a veterinary degree?
Net present value (NPV) of the DVM/VMD degree is a key performance indicator for the
profession as it provides an indication of the willingness of society to compensate veterinarians
for the investment in the DVM/VMD degree. The NPV provides the current value of the lifelong
earnings of the veterinarian above what they would have earned had they not obtained their
DVM/VMD degree.
Net present value is the difference between the present value of cash inflows (income) and the
present value of cash outflows (expenses). Thus, in examining the NPV of a veterinary
education, one would look at the present value of the expected cash flow from being employed
as a veterinarian over the course of the career minus the present value of the investment in
earning the veterinary degree. If the NPV is positive, then the investment yielded more inflow
than outflow. In the model presented here, the veterinary degree is compared with the
bachelor’s degree to determine whether the additional investment in the DVM/VMD is borne
out by equivalently increased cash inflows over the course of the career.
The NPV has been declining in the general veterinary profession since 2010. The primary
reason for the declining NPV is increasing opportunity costs: Starting salaries for bachelor’s
degree holders grew more than 19 percent during this time, whereas starting salaries for the
DVM/VMD degree holders grew approximately 5.5 percent. If the earnings gap between
DVM/VMD and bachelor’s degree holders continues to narrow, veterinary students may begin
to view the DVM/VMD degree as not worth the price of admission to the veterinary profession.
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The decline in the NPV for men has been much steeper than for women and this may be a
contributing factor to the changing gender distribution in the profession. Males have a much
larger opportunity cost3 to become a DVM than do women, as the difference between mean
veterinary income and the mean income of a general bachelor’s degree recipient is
substantially less for men than for women (Figure 72 and Figure 73). Table 62 shows the income
levels that would be necessary for each group to enter a positive NPV range relevant to the
amount of debt carried. The report stated that small increases in annual income (around
$2,000) could potentially offset large increases in debt (up to $50,000), and have a strong
influence on the NPV of the equine veterinary degree.
Employment Status and Hours Worked
Slightly more than four-fifths (80.5 percent) of Equine respondents reported employment in
clinical veterinary medicine (AVMA: 67.0 percent); 11.4 percent were employed but not in
clinical veterinary medicine (AVMA: 23.6 percent); 6.6 percent were retired (AVMA: 6.0
percent); and 1.5 percent were unemployed (AVMA: 3.4 percent) (Table 63). Of the Equine
respondents who were not practicing in clinical veterinary medicine, approximately 71 percent
were in professor roles (AVMA: 26.1 percent) and 24.7 percent in an academic clinician position
(AVMA: 19.4 percent), followed by 2.2 percent of respondents who were managers (AVMA: 21
percent), and 2.2 percent in another type of field (AVMA: 26.8 percent) (Table 64).
Among employed equine practitioners a wide variation of hours worked per week was
reported; the majority worked between 40-60 hours, which exceeded the average work hours
reported by the AVMA group (Figure 74). The mean hourly reported work week for Equine
respondents was 54.9 hours for males and 56.6 hours for females with the majority (60.4
3 The opportunity cost refers to the l ifetime income-earning potential had veterinarians pursued an alternative career prior to entering veterinary college.
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percent) between 40 and 60 hours per week. For the AVMA survey respondents, the mean
hourly work week was 48.5 hours for males and 45.9 hours for females, with the majority (68.0
percent) of AVMA respondents between 40 and 60 hours per week (Table 65). Near all of male
(89.5 percent) and female (89.4 percent) Equine respondents reported working more than 40
hours a week. By comparison, 80.8 percent of male AVMA respondents and 78.3 percent of
female AVMA respondents reported working more than 40 hours a week (Figure 74).
Among those in clinical veterinary medicine, 94.6 percent of Equine respondents reported
working full time and the remaining 5.4 percent were employed part time. In the AVMA
sample, 89.0 percent were employed full time and 11.0 percent were employed part time in
clinical veterinary medicine (Figure 75).
On average, Equine respondents employed full time worked 10 emergency hours during a
typical week, compared to 7.1 hours for full-time AVMA respondents (Table 67). Almost one-
third (32.6 percent) of AAEP respondents working full time reported that they performed 26
percent to 50 percent of the total amount of on-call or emergency duty at their place of
employment, and 24.9 percent reported that they were responsible for 100 percent of this duty
(Figure 80). The data reflect the high number of solo or small (two to three DVM) practices in
the equine veterinary industry. Among 72 solo practitioner respondents, 46 (63.9 percent) were
on call or performed emergency duty 100 percent of the time. Not surprisingly, the higher the
number of full-time equivalent (FTE) veterinarians at the place of a respondent’s employment,
the more likely respondents reported lower on-call/emergency duty percentages (Figure 81).
Satisfaction with employment
Survey data showed that Equine respondents tended to be more satisfied with their work than
AVMA respondents. Male Equine respondents reported higher satisfaction levels than female
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equine respondents. Of female Equine respondents, 34.3 percent were moderately, not too, or
not at all satisfied, while 65.7 percent were very or extremely satisfied (Table 74). Higher
satisfaction levels were reported in older graduates as their years of experience increased
(Table 76). The high debt levels and low salaries of those who have graduated more recently
undoubtedly impact satisfaction with employment. In addition, differing priorities of different
generations may also drive these findings.
Regression analysis showed that respondents who were practice owners, those with higher
incomes and those who “felt well prepared by their education” were significantly likely to
report high levels of job satisfaction while respondents who had participated in a residency
reported less job satisfaction (Table 80). Equine respondent practice owners were much more
satisfied than Equine respondent associates. Many more Equine respondent practice owners
(49.4 percent) reported that they were extremely satisfied with their employment than Equine
associates (20.2 percent). Among AVMA respondents, 45.2 percent of owners were extremely
satisfied versus 15.4 percent of associates. More than 40 percent of associate respondents in
both the Equine and AVMA samples reported being not at all satisfied to moderately satisfied
with their employment (Table 78).
More than one-third of Equine respondents have been with their current employer for less than
five years, less than 20 percent for six to 10 years, and about 40 percent for more than 10 years
(Figure 82). AAEP respondents were asked if they were likely to remain employed at their place
of employment over the next five years. The majority of AAEP respondents reported that it was
veryto extremely likelythat they would stay at their current job over the next five years (Male:
72.9 percent; Female: 66.3 percent) (Figure 83). A sizeable group of AAEP respondents,
however, reported they are moderately likely to not at all likely to stay employed within the
next five years at their current employment (Male: 25.7 percent; Female: 31.2 percent). When
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the likelihood of staying at their current job over the next five years is shown with respect to
graduation year (Figure 84), 42.8 percent of AAEP respondents revealed that they are not at all
likely to moderately likely to want to stay at their job if they entered the veterinary workforce
within the last five years. The reality of equine practice (long work weeks, additional
responsibility of emergency duty, low salaries compared to other sectors of practice) and
educational indebtedness may be driving this dissatisfaction of newer graduates. However, it is
notable that when Equine respondents were asked would they change to a different veterinary
sector if they could, 83.3 percent indicated they would not (AVMA: 71.8 percent).
In both the Equine and AVMA sample, those who graduated more recently indicated that they
preferred a larger workplace. The percentage of respondents who reported this preference
increased in a linear fashion with decreasing level of experience (fewer years from graduation)
(Figure 93). This finding may follow the Millennial preference for collaboration and teamwork.
Having grown up in an environment that fosters teamwork, most Millennials like working in
groups and highly prefer a sense of unity and collaboration over division and competition. They
look for support and reassurance among their peers and are a highly social generation (Yingling,
n.d.).
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Retirement
At the time this survey was conducted, 60 Equine respondents (6.6 percent) and 152 AVMA
respondents (6.0 percent) were retired. 72.9 percent of these Equine respondents retired in the
past five years (Figure 95). Respondents were asked about retirement decisions. Both samples
revealed that most respondents retired from clinical veterinary medicine on or around their
anticipated timeframe. However, while 50.8 percent of Equine respondents retired on or
around their anticipated timeframe (AVMA: 71.8 percent), 32.2 percent retired from clinical
veterinary medicine earlier than anticipated (AVMA: 18.5 percent) (Table 83). The two highest
ranking reasons for retiring early from equine clinical veterinary medicine were “improve work-
life balance,” and “stress level” (Table 84).
Unemployment and Underemployment
In 2015, 2.4 percent of Equine respondents were unemployed in clinical veterinary medicine at
some point in that year. Of the 2.4 percent respondents who reported unemployment, 35.3
percent of them found a job within one month, 29.4 percent found a job between three to six
months after beginning a job search, and 35.3 percent found work within a year.
Underemployment is defined as the measure of a person’s desire and ability to increase one’s
hours spent working. The desire and ability to increase one’s working hours is often
unattainable due to a lack of demand for one’s services. In this survey, underemployment
represents the number of additional hours that veterinarians desire to work above what they
are currently working. Measured in total hours, underemployment reflects the increase or
decrease in weekly hours that one wishes to work for an equivalent increase/decrease in
compensation.
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Among Equine respondents, 60 percent stated they would work the same number of hours per
week as they are currently working with no change to their current level of total compensation
(AVMA: 65.8 percent), 16.8 percent wished to work more hours per week than they do now, for
a higher level of total compensation (AVMA: 12.0 percent), and 23.2 percent wished to work
fewer hours per week for a lower level of total compensation (AVMA: 22.2 percent) (Figure 99).
By gender, 25.3 percent of female (AVMA: 23.9 percent) and 19.9 percent of male (AVMA: 18.6
percent) Equine respondents wished to work fewer hours for less compensation. In contrast,
16.5 percent of Equine sample females (AVMA: 12.5 percent) and 17.7 percent of Equine males
(AVMA: 11.7 percent) wished to work more hours for greater compensation (Figure 100).
Of the Equine respondents who desired to work more hours, the mean number of additional
hours desired was 19.7 hours (AVMA 18.9 hours). Reasons that Equine respondents gave for
wanting to work more hours a week were the desire to gain professional expertise (14.7
percent), not currently working to capacity (42.2 percent), the desire to earn more
compensation (82.6 percent), or other reasons such as paying off student loans, providing
better service to the community, satisfying needs of the client, and social benefits (4.6 percent).
The Equine respondents who desired to work fewer hours wanted to lessen their work week by
16.4 hours (AVMA: 14.9 hours) and cited the need to improve work-life balance as the main
reason they want to work less (77.3 percent), followed by taking care of children/childbearing
(Table 89).
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How is the physical and mental health of equine practitioners?
The survey asked a number of questions relating to respondents’ physical and mental health,
history and severity of on the job injuries and chronic pain, and how respondents felt these
factors affected their productivity.
Approximately 90 percent of AAEP respondents of both genders reported their physical health
as good to excellent. Just over 90 percent of the male respondents reported their mental health
as being in good to excellent condition, and 76.6 percent of the female respondents reported
their mental health being in good to excellent condition. 9.2 percent of AAEP males and 18.7
percent of females reported their mental health to be in fair condition, and 0.7 percent of
males and 4.6 percent of females reported their mental health as being in poor to very poor
condition (Figure 118). Thus, nearly one-quarter of female AAEP respondents reported their
mental health to be fair to very poor. The reasons for these disparities must first be viewed
through the lens of the differing profiles of the respondents: males had an average age of 55
and an average of 29 years of experience versus females with an average age of 39 and an
average of 12.3 years of experience. In addition, the burdens of high educational debt and low
starting salaries borne by recent graduates, along with the stressful lifestyle of equine practice,
are undoubtedly factors in decreased mental health.
AAEP male respondents reported more limitations on their daily activity from physical health
than females, while females reported more limitations from mental health. Among the AAEP
members surveyed, 43 percent of male respondents and 40 percent of females reported that
their physical health limited them in some degree from meeting the demands of their job or
daily life (Figure 123). Vigorous activity was limited more than moderate activity for both
genders (Figure 127 and Figure 128). There was a general linear trend of activities, especially
vigorous, being more limited in practitioners of advancing age, though most respondents with
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up to 50 years of experience reported that moderate activity was not limited at all by their
health (Table 92).
Nearly one-quarter of AAEP males reported that their mental health limited them a little to a
great deal in meeting the demands of their job or daily life, while 42.5 percent of AAEP females
reported their mental health affected their ability to meet the demands of their job or daily life
a little to a great deal. However, most respondents reported no limitation (Figure 123). AAEP
graduates from the last 10 years reported higher levels of negative effects of their mental
health on their work and accomplishments in the four weeks prior to the survey than other
experience cohorts (Table 96).
Work Injuries
Nearly four-fifths of AAEP respondents reported they had been injured while performing work
as a veterinarian. Of the respondents who reported work injuries that caused them to miss
work, most (53.0 percent) reported two to four injuries over the course of their career (Figure
125). Out of the 764 respondents who were injured at some point during their career and who
answered this question, 48.0 percent did not miss work due to a work injury for at least one of
the injuries they reported having, 36.7 percent indicated no more than seven days of work
were missed, 10.7 percent no more than 30 days, 4.7 percent no more than 90 days, and 3.4
percent more than 90 days. A small number (2.1 percent) indicated they sustained a permanent
disability from an injury that occurred while practicing veterinary medicine (Figure 124). Slightly
more than 16 percent of AAEP respondents reported being hospitalized and 20.3 percent
reported having surgery for a work-related injury. Equine veterinarians commonly continue to
work despite injuries. This may be related to the high numbers who are solo practitioners, who
may feel they have no choice but to continue to produce revenue and provide services to their
clients. Many multi-doctor practices have limited capacity to take on the work of an injured
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coworker without increasing the already robust average number of hours worked each week.
Equine practitioners likely feel a strong responsibility to not only continue to care for their
patients, but to not unduly burden their fellow veterinarians.
AAEP respondents were asked how much bodily pain they had experienced during the four
weeks prior to completing the survey, as well as the degree to which pain had interfered with
their normal work, including both their work outside the home and their chores in daily living.
While two-thirds of male and female AAEP respondents reported mild or very mild pain, 23.8
percent of males and 16.5 percent of females reported moderate pain, and 2.6 percent of
males and 2.3 percent of females reported experiencing severe or very severe pain. About half
said the pain did not interfere at all with normal work. Most of the rest reported a small
amount of interference. A minority of respondents reported a lot of interference (Table 97).
While equine practice is quite a physical career, and injuries are not uncommon, equine
practitioners are clearly tough individuals, and persist despite chronic pain.
Professional Quality of Life (ProQOL) Measures
Professional Quality of Life (ProQOL) (Stamm, 2010). Questions were included in the AVMA-
AAEP 2016 Survey of Equine Practitioners to investigate the effect that expending compassion
during work as a veterinarian has on the practitioner’s well-being. Responses to the ProQOL
questions are scored based on the responses of thousands of individuals across many different
occupations.
The ProQOL application is used to measure compassion satisfaction, burnout and secondary
traumatic stress associated with helping others who have experienced suffering. Compassion
satisfaction is about the pleasure someone derives from their work. An individual might, for
example, feel like it is a pleasure to help others through the work that he or she does, and
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might feel positively about colleagues, or his or her ability to contribute to the work setting or
the greater good of society by working with people who need care. On the other hand, negative
feelings derived from work is measured by scoring burnout (exhaustion, frustration, anger,
depression) and secondary traumatic stress (work-related mental trauma).
Mean compassion satisfaction scores for Equine respondents (Figure 131) were in the high-
normal range, and Equine respondent scores for burnout (Figure 132) and secondary traumatic
stress (Figure 133) were in the low-normal range. On average, Equine respondents had scores
that were a bit better than the AVMA cohort (higher for compassion satisfaction and lower for
burnout and secondary traumatic stress). A linear trend was seen for compassion satisfaction
across graduation year cohorts with the older graduates reporting higher scores than recent
graduates (Table 99), and a linear trend was seen for burnout and secondary traumatic stress
across graduation year cohorts with the older graduates reporting lower scores than recent
graduates (Table 109 and Table 119). The mean sum of burnout scores was 2.2 points lower for
Equine than AVMA, and in the low-normal (better) end of the results reported across all
professions. However, 5.8 percent of Equine and 9.2 percent of AVMA respondents had
burnout scores over 35, indicating the need of intervention (Figure 132). The data showed that
females had higher burnout (Table 110) and secondary traumatic stress scores (Table 120), and
lower compassion satisfaction scores than males (Table 100). Based on the demographics of the
Equine cohort, this was not unexpected. Female practitioners are mostly those with fewer years
of experience, have high educational debt, earn low salaries, and are less likely to be practice
owners. The data showed that practice ownership, higher incomes, and increased years of
experience were associated with better scores, and debt was associated with less positive
scores.
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The survey section on the veterinary market concluded with questions relating to well-being
that were specific to the equine sector of veterinary medicine. The survey broke down
respondent answer trends by gender. Questions relating to feeling satisfied when learning new
information or skills, or noting a positive patient outcome tended to have similar positive
ratings from male and female respondents. Questions relating to the level of stress felt while on
call, or handling multiple priorities, or feeling exhausted or irritated while on the job tended to
have different ratings between genders, with females indicating higher levels of stress,
irritation or exhaustion than males (Table 129).
THE MARKET FOR VETERINARY SERVICES
The report on the market for veterinary services includes information on the supply of equids in
the United States, private practice equine veterinary services, and the demand for equine
veterinary services. Many factors drive the market for equine veterinary services. As the
demand for veterinary services increases, the price of veterinary services increases in parallel,
other things being equal. Conversely, a decline in the number of clients, animals per client, or
services demanded per animal will typically reduce the demand for veterinary services and thus
the overall revenue of equine veterinary practices for service. In addition, there has been an
increased shift of horse owners utilizing outside resources to provide some of these services
through non-veterinary providers.
Data from the U.S. Department of Agriculture Census of Agriculture and the 2016 AVMA Pet
Demographic Survey (PDS) demonstrate a downward trend of equine numbers in the country.
The American Horse Council estimated 9.2 million equids in the United States in 2005. The
American Horse Council Economic Impact Study released in early 2018 estimated the current
U.S. equine population at 7.2 million. Conversely, the Brakke Equine Mega Study in 2014
reported an estimated U.S. horse population of 6 million, clearly demonstrating the uncertainty
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of current equine population numbers. The 2012 census by the USDA, PDS and American Horse
Council may shed a more accurate light on what can best be described as a very volatile market
place for the equine industry since the 2007 economic recession.
Horse-owning households surveyed by the AVMA Pet Demographic Survey reported that 65
percent of primary equine caretakers were female; of these households, 47 percent regarded
their horses as family members, 42 percent as pets or companions and 11 percent as livestock
or property. This demographic of horse owners’ purchases of veterinary services is parallel to
their disposable household income; almost half (44 percent) of horse-owning households
surveyed by the AVMA Pet Demographic Survey reported that their horse(s) did not receive any
care from a veterinarian in 2016, likely reflecting the direct relationship of disposable income to
veterinary service demand. The remaining households surveyed had between one and more
than four visits.
According to the 2012 AAEP Owner Trainer Survey, one of the top three reasons that clients
choose a veterinarian is the ability to provide on-the-farm ambulatory emergency care 24 hours
a day, seven days a week. Interestingly, less than 10 percent of the respondents chose low fees
as a top reason to choose a veterinarian. More than half (55 percent) of the owners reported
they had been using their primary veterinarian for at least six years; the average was nine years
suggesting that market demand, while impacted by economics, remains fairly stable in
professional services and the related relationships.
A PORTRAIT OF THE EQUINE VETERINARY PRACTICE
This section of the report examines the multiple sectors of equine veterinary practice,
communication, ambulatory service calls, utilization of practice staff, competition from
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alternative service providers, practice ownership, practice revenue trends, motivation factors
for becoming an equine veterinarian, and satisfaction with the equine veterinary career.
Sectors of equine practice
Equine veterinary practices have much in common with other types of veterinary practices in
the delivery of veterinary medical services. Equine practices, however, have several
characteristics that distinguish them from other types of practices, such as varying foci on
individual equine subsectors within the equine industry. More than 60 percent of AAEP
respondents at the time of the survey worked in general equine practice serving multiple
sectors. These individuals typically work with many different types of horses in different equine
sectors throughout the day. Of the remaining respondents, 15.6 percent worked in English
performance, 5.7 percent worked in Thoroughbred racing, 5.7 percent worked in the
reproductive sector, 4.7 percent worked primarily with equine companions, and the remainder
(each under 4 percent) in gaited breeds, Quarter Horse and Standardbred racing, ranch or
working, and Western performance (Figure 141).
Communication
Equine veterinarians communicate with multiple individuals about the diagnosis and treatment
of an individual patient and do so in a variety of ways. Almost 70 percent of AAEP respondents
most frequently contacted the owners of the patient. Next in the contact order were farm
trainers (majority-ranked second) and farm employees (majority-ranked third) (Figure 144).
Communication varied depending on the sector. Respondents in the racing industries
interfaced with owners about a patient the least of all sectors. Most respondents in racing
sectors serving Thoroughbreds (80.0 percent), Standardbreds (71.4 percent), and Quarter
Horses (100.0 percent) utilized trainers and farm managers as the primary contact (Figure 144).
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Respondents in the Quarter Horse racing industry communicated with trainers on average 97.0
percent of the time, and owners 10.6 percent of the time. In the Thoroughbred racing industry,
respondents reported that they communicated 75 percent of the time with trainers and 22.9
percent of the time with owners. Respondents in the English performance sector indicated that
they communicated with owners 58.2 percent and trainers 57.7 percent of the time (Table
134).
Over time, the equine veterinary industry has adopted new technologies and channels through
which to communicate. While slightly more than half of the respondents ranked in-person
communication first, cell phone communication was a close second (46.9 percent), followed by
email and text messaging (Figure 145).
Full-Time Equivalent Veterinarians and Staff Support
In the AAEP sample, 38.5 percent of respondents reported a one-veterinarian practice, 14.3
percent a two-veterinarian practice, 12.6 percent a three-veterinarian practice, 7.8 percent a
four-veterinarian practice, 6.1 percent a five-veterinarian practice, and 20.6 percent a six-or-
more-veterinarian practice (Figure 146).
On average, there were 1.7 FTE support staff for every FTE veterinarian employed at the AAEP
respondents’ place of employment in 2015. About 25 percent of respondents reported two to
four, an additional 25 percent reported five to nine positions at their practice in 2015, and 16
percent reported no support staff positions (Figure 147). A total of 72 solo practitioner
respondents reported no support staff positions. Of the respondents reporting additional
owner, associate and staff positions in their place of employment in 2015, the mean number of
FTE associates per FTE owner veterinarian was 1.89, or about two associates for every owner in
a practice (Table 136), and approximately one part-time staff position for each veterinarian in a
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practice. These positions included 0 .37 interns, 0.57 credentialed veterinary technicians, 0.80
non-credentialed veterinary technicians, 0.80 veterinary assistants, 0.67
receptionist/information clerks, and 0.89 barn/hospital animal caretakers per veterinarian
(Table 137).
Staff Utilization
More than one-third of AAEP respondents (35.2 percent) reported that veterinary technicians
and/or other support staff were used routinely on ambulatory calls (Figure 148). Nearly half of
the respondents indicated that support staff were not used after business hours (Figure 149),
compared to almost one-quarter of respondents who said support staff were used after normal
business hours on ambulatory calls, but only if needed.
Among AAEP respondent practices, more non-licensed technicians were used than licensed
technicians at the respondents’ place of employment. 55.7 percent of AAEP respondents
reported that they did not have a licensed technician in the workplace, compared to 21.5
percent who said they did not have a non-licensed technician/veterinary assistant in the
workplace. This finding may be because licensed veterinary technicians with equine experience
could be more difficult to find than non-licensed assistants, as the curriculum for veterinary
technology is heavily concentrated on companion animal skills, and employment opportunities
and salaries in companion animal practice are often more attractive than those in equine
practice.
Primary Business Model
Among AAEP respondents, 36.5 percent reported being in an ambulatory practice. The
distribution also included: 35.4 percent ambulatory with a haul-in facility; 16.1 percent full-
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service specialty/referral hospital with an ambulatory division; 1.3 percent haul-in facility; and
1.7 percent full-service specialty/referral hospital with no ambulatory division (Figure 152).
More than 90 percent of AAEP respondents said they charged a farm call or trip fee, and nearly
the same amount (89.4 percent) reported that they charged an emergency fee in addition to a
trip charge for emergency calls. A modest number of respondents (4.9 percent) said they did
not offer emergency services.
The majority (77.4 percent) of AAEP respondents reported a service area radius of between
zero and 60 miles, with the remainder of respondents (22.6 percent) covering more than 61
miles (Figure 153). Almost half (47 percent) of AAEP respondents reported that they drove
between 25,001 and 50,000 miles annually while practicing veterinary medicine as an equine
practitioner, followed by 29 percent who traveled between 12,501 and 25,000 miles a year
(Figure 154).
Parallel Service Providers and Competition
There are many non-veterinarian providers of equine services – including dentistry, podiatry,
sports medicine, integrative therapies, reproduction, and pharmaceutical services – that were
once deemed solely the market of veterinarians. These non-veterinarian providers of equine
services can be referred to as parallel service providers. The top services that AAEP respondents
believed affected their revenue stream were dentistry (62.5 percent), internet pharmacy sales
(54.7 percent), lay practitioners performing chiropractic, acupuncture and massage services
(47.1 percent), transient show veterinarians who followed a show circuit (31.2 percent) and
traveling pharmacies with a physical presence at horse shows (16.6 percent) (Figure 155).
AAEP respondents face competition not only from parallel service providers but from other
veterinarians within their service areas as well: 26.5 percent of AAEP respondents stated that
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there were one to five other equine veterinarians in their service area, followed by 24.6 percent
with six to 10 veterinarians, 23.6 percent with 11 to 20 veterinarians, 11.6 percent with 21 to 30
veterinarians and 13.7 percent with 31 or more veterinarians (Figure 157).
Practice Ownership and Ownership Transitions
Practice owners accounted for 334 (34.3 percent) of the Equine respondents who revealed their
employment status at the end of 2015. Of the respondents who were practice owners, 49.7
percent were sole proprietors, 36.5 percent were a partner/shareholder in an S-Corp or C-Corp,
and 13.8 percent were a partner in a Limited Liability Corporation (LLC) or other type of practice
ownership structure (Figure 159).
Of the 225 AAEP respondents who shared their perspective on selling ownership shares, 4
percent indicated that they would like to sell some or all of their shares before retirement, 28.4
percent would like to sell at the time of retirement, and 67.6 percent indicated selling shares
both before and at the time of retirement. In the AAEP sample, more than half (50.4 percent) of
relief and associate veterinarian respondents were interested in purchasing a practice; this
number is more than twice the interest reported by the AVMA sample (21.7 percent).
Although owners wish to sell and associates wish to buy, more than 64 percent of AAEP
respondents were not very confident, to not at all confident, or unsure about obtaining practice
ownership. More than half (56 percent) of AAEP respondent owners stated they were not very
confident, not at all confident, or not sure about being able to successfully sell their ownership
interest (Figure 162). An assessment of the confidence level of owners in selling interest in their
practice with respect to their practice size indicated that owners were more confident in selling
their ownership interest if they had more staff members in their practice (Figure 163).
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In considering who would buy their practice interest, 36.7 percent of AAEP respondent owners
were not sure who might succeed them, 26.9 percent indicated that they were looking to
current associates to purchase the practice, followed by nearly the same number of
respondents (26.6 percent) who cited a veterinarian not currently working at their practice as a
future successor. Of the remainder, 7.9 percent of AAEP respondents had some other person in
mind, and 2 percent of respondents reported that a corporate entity was most likely to
purchase their ownership interest (Figure 165).
Only 18.4 percent of respondents reported having a buy-sell agreement in place to provide
structure for departure of partners due to retirement, disability, or death.
Compensation Methods
Data showed that 39.2 percent of AAEP respondent owners were compensated with no
differentiation between pay for effort as a veterinarian and pay as an owner (Table 149).
Because practices are valued based on their profitability, when owners’ pay for being a
veterinarian is not separated from their return on investment as a business owner, true
profitability is not readily visible on financial reports. The compensation model recommended
by business consultants includes pay for each of these aspects of ownership: effort as a
veterinarian, effort as a practice manager, return on real estate, and return on ownership
investment. Thus, an owner is paid for their effort as a veterinarian with the same formula as
any other veterinarian employed by the practice. For practice management, a budget of 1 to 3
percent of gross revenue is set aside each year for all expenses related to practice
management, such as an office manager’s salary and benefits, membership in a management
study group, or education in management. The remainder is split among owners as a stipend
for management duties, paid in proportion to their efforts in this area. For practice owners with
real estate ownership shares of a practice facility, return from lease payments is a third
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component of compensation. Lastly, the net profit of the practice is split among owners in
accordance with their proportion of ownership or contribution to production of revenue.
For AAEP respondent associates, 49.3 percent reported that they were on a salary with
opportunity for production-based compensation, followed by 29.5 percent who were paid
salary only (Table 149). 68 percent of associate veterinarian respondents reported they
preferred a mix of base salary with the opportunity for additional production-based
compensation, followed by 21.2 percent that preferred straight salary (Figure 166).
Those AAEP respondents, both owners and associates, who were paid based on revenue
production, (46.3 percent and 62.4 percent, respectively) were asked to indicate how the
compensation was calculated: 14.6 percent of owners and 22.9 percent of associates were
compensated based on a consistent percentage of gross production/sales revenue for all
services, medical supplies, and pharmaceuticals; among associate respondents, 24.3 percent
reported that compensation was derived from a higher percentage of gross production/sales
revenue for services and a lower percentage of sales of medical supplies and pharmaceuticals.
Less than 10 percent of either group of respondents was paid on net production, or a variable
commission rate depending on the nature of the services performed (Table 154). Of the AAEP
respondents who had practice management duties, 340 (64.4 percent) reported that they did
not receive compensation for these services.
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Percentage of Household Income
When asked what percentage of household income was contributed by the respondent, 65.4
percent of male AAEP respondents reported that they contributed 76 percent to 100 percent
toward their total household income, compared to 42.2 percent of female AAEP respondents
(Figure 168). This is not surprising considering the increase in dual career couples in the last
several decades, and the fact that the median age of Equine male respondents was 58 years,
compared to 35 years for females.
Gross Revenue Production
The median personal gross revenue from production for Equine practice owner respondents
was $385,832, and for associates was $356,500. For AVMA respondents, the median personal
gross revenue from production was $500,000 for owners and $450,000 for associates (Table
156).
The mean personal gross revenue of production among Equine respondents by graduation year
showed a gradual increase in revenue production until after 20 years of practicing veterinary
medicine was reached. Respondents less than five years after graduation reported mean gross
revenue production of $306,019, while respondents who had been practicing for more than 30
years produced a mean of $411,528. AVMA respondents showed similar means with respect to
respondents who recently graduated bringing in less revenue than those with more experience
(Table 157).
The mean personal gross revenue from production among Equine respondents by gender was
$477,929 for males, and $346,638 for females. Among AVMA respondents, the mean personal
gross revenue was $515,159 for males and $451,108 for females (Table 158). The distribution of
personal gross revenue from production by gender is presented in Figure 174. It is important to
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notewhen interpreting this datathat the mean experience (years since graduation) of male
respondents (29 years) in this study was more than twice that of females (12.3 years).
The higher the median personal gross revenue of production reported by Equine and AVMA
respondents, the higher the income bracket a respondent reported (Table 159). Overall, Equine
or AVMA respondents who brought more revenue into the practice reported higher trends in
personal take-home income (Figure 175).
Respondents’ median personal gross revenue from production, in general, consistently
increased as the number of veterinarians in a practice increased until reaching a three-FTE
veterinarian practice. AAEP respondents in a one-veterinarian practice with no support staff
reported producing a median of $205,000 in gross revenue. Those in a one-veterinarian
practice with support staff produced a median of $330,000 and those in a veterinary practice of
two FTE veterinarians produced a median of $400,000 (Table 160). The general trend among
AAEP respondents was that the larger the practice size, the higher the number of respondents
who produced revenue of more than $300,000 (Figure 176). A greater percent of respondents
from five- and six-doctor practices earned revenue of more than $500,000 than did those from
four-doctor and smaller practices.
Revenue and Income Contraction and Expansion of Equine Practices
AAEP respondents who were practice owners were asked specifically about whether their
practices’ gross revenue production expanded (increased) or contracted (decreased) in 2015
compared to 2014. Overall, 64.1 percent of owner respondents reported an expansion in
practice gross revenue in 2015 compared to 2014; 13.1 percent reported a contraction, 16.6
percent of respondents reported that their revenue stayed the same, and 6.3 percent were
unsure.
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Expenses
The survey responses indicated that, in general, the more veterinarians there were in a
practice, the lower the practice expenses and deductions per veterinarian (at the median)
(Table 164).
The current ratio (current assets to current liabilities) is a measure of the practice’s ability to
meet short-term obligations. The median current ratio of AAEP owner respondent’s equine
practices was 5.74, with a range of less than .01 to 61.6. These data mean that the median
veterinary practice has $5.67 of current assets for each $1 of current liabilities. Minimal
acceptable current ratios vary from industry to industry and are generally between 1.5 and 3
for healthy businesses (The University of Adelaide, 2014; Gallo, 2015).
Profit Centers/Activity Centers
Multiple different activities in equine practice are revenue generators for veterinarians. The
highest mean percent of revenue for AAEP respondents was reported to be preventative
medicine (14.8 percent), followed by pharmacy sales (11.2 percent), lameness examinations
(10.5 percent), imaging (9.9 percent), physical examinations (9.0 percent), dentistry (8.4
percent), and laboratory testing (7.0 percent). Farm calls accounted for an average 6.8 percent
of revenue, internal medicine contributed 5.9 percent, and reproductive services 5.1 percent.
Integrative therapies made up a mean of 4.4 percent of revenues, while the smallest sources of
revenue reported were for surgery (4.2 percent) and pre-purchase exams (2.9 percent) (Table
172).
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ECONOMIC IMPACTS OF THE EQUINE VETERINARY INDUSTRY
Economic impact analysis (EIA) provides a comprehensive assessment of the economic impacts
of the profession on the U.S. economy. The objective of the EIA in this report is to determine
the economy-wide impacts of equine veterinary industry activities at the regional and national
levels. The report presents a look at the direct, indirect, induced, and total effects of veterinary
practices on the economies of each of the U.S. regions defined by the U.S. Postal Service.
IMPLAN software is the economic tool that is most widely used for economic analysis. The
IMPLAN system combines data from different sources including the U. S. Department of
Commerce, the U.S. Bureau of Labor Statistics, and other Federal and state government
agencies to compute multipliers that are used to estimate the impacts of outside factors on the
local economy. Data in IMPLAN are collected for every geographic region in the United States,
from small cities to the entire nation. The IMPLAN system estimates the multiplier effects of
changes in final demand for one sector on all other industries within a local area and provides
the results in terms of total changes in employment, income, output and value added.
In an economic impact analysis, three different results are presented: direct effects, indirect
effects and induced effects. Putting the results in the context of an equine veterinary practice,
the direct effect refers to the impacts created directly by the practice’s activity. This translates
into an increase in the total gross output of all businesses in the community and the creation of
jobs. The indirect effect refers to those effects generated by the producers of intermediate
goods and services purchased. Industries affected by veterinary practice and part of the
indirect effect may include utilities, construction, landscaping, delivery services and other
businesses that provide services to the practice. The induced effect refers to the subsequent
spending in the local economy made by the employees of equine veterinary practice and those
of the intermediate input suppliers.
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An economic impact analysis was performed for each of the 10 regions in the United States
utilizing an approximate number of equine veterinarians and employees, the mean practice
revenue of each region and an assumption that the production of a veterinary service by any of
these regions required the same set of inputs. Once the impact per practice was determined,
the impact for the entire industry was aggregated by multiplying the impact of an individual
practice by the total number of establishments in the region.
The employment effects indicated that at the national level the equine veterinary industry
generates an estimated 18,658 direct jobs, supports 5,497 indirect jobs, and induces 8,925
other jobs for an estimated total of 33,080 jobs for the entire economy (Table 175). The total
direct economic impact on labor income (employment) at a national level was estimated at
$1.14 billion. The total indirect effects were estimated at $301 million and the induced effects
at the national level were equivalent to $432 million. The aggregated effects were estimated at
$1,875 billion for the U.S. economy (Table 176).
The value added represents the increase in the gross revenue of production generated by an
industry. The direct contributions of equine practice to the gross revenue of production by
region varied, but at the national level the direct effects were estimated at $2.7 billion. The
total indirect effects were estimated at $538 million and the induced effects at the national
level were equivalent to $761 million. The aggregated effects were estimated at $3.97 billion
for the U.S. economy (Table 177).
The total dollar value of the equine veterinary services sold to consumers by equine veterinary
practices was estimated at $3.55 billion. The total indirect and induced effects at the national
level were $944 million and $1.31 billion respectively. The aggregated effect for the entire
economy was estimated at nearly $5.81 billion (Table 178).
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Equine veterinary practices pay tax to the local, state and Federal governments through
different channels for a total of an estimated $700 million. The Federal government received
$144 million on employee compensation, $20 million on production and imports, $143 million
on household service expenditures, $137 million for corporate earnings and an estimated $26
million as tax on proprietor income (Table 180).
On state and local levels (combined), taxes totaled $2.5 million for payroll, $160 million on
production and imports, $48 million on household service expenditures, $19.3 million on
corporate earnings and $26.5 million on proprietor income (Table 179).
In conclusion, equine veterinary practice, although a small slice of veterinary medicine as a
whole, has a significant impact on regional and national economies and merits solid
consideration in government, industry and stakeholder discussions.
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DATA SOURCES AND METHODS
The survey that is the focus of this report drew upon responses from AAEP members. Data used
in this report were collected from several sources including the AVMA-AAEP 2016 Survey of
Equine Practitioners, the AAEP membership database, and the AVMA 2016 Census of
Veterinarians. At the time of the survey, more than half of the AAEP member-respondents were
in private practice restricted to equines; other members held positions in a college or
university, government, not-for-profit organization, or industry setting; some were pursuing an
advanced education degree, and others were practicing in mixed, food animal, companion
animal or other veterinary setting. The AVMA-AAEP 2016 Survey of Equine Practitioners
commenced at the beginning of August 2016. Using the AAEP membership list, 5,885 active
members of the organization were initially selected to complete the survey. After accounting
for 228 invalid e-mail addresses from the initial sample that were returned to sender or failed
electronic delivery, a total of 5,657 members with valid email addresses received the survey. In
addition, 56 other AAEP members personally requested to fill out the survey, bringing the total
number of members who received the survey to 5,713. A reminder email was sent every week
until the close of the survey. The survey officially closed on September 6, 2016. In total, of
5,713 members who received the survey, 986 members completed the survey. After removing
11 respondents who were still in veterinary school, the number of respondents totaled 975,
yielding a response rate of 17 percent.
In addition to the 975 respondents, 81 veterinarians who identified themselves as equine
practitioners when responding to the AVMA’s 2016 Census of Veterinarians, but who were not
among the AAEP survey sample (and therefore not represented in the AAEP dataset), were
included in a second dataset that was combined with the AAEP member respondents from the
AVMA-AAEP 2016 Survey of Equine Practitioners. Some of the questions from the AVMA’s 2016
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Census of Veterinarians were similar to the AVMA-AAEP 2016 Survey of Equine Practitioners.
Responses to these questions were combined to form this second dataset. After integrating
these 81 veterinarians’ responses with the 975 into the second dataset sample, the AAEP
dataset was analyzed and compared to the combined dataset to evaluate the similarities and
differences between the samples. The combined sample was found to be similar. As a result, for
all those questions that were the same between the AVMA-AAEP 2016 Survey of Equine
Practitioners and the AVMA’s 2016 Census of Veterinarians, the combined dataset was used for
reporting responses.
All veterinarians in the AVMA-AAEP 2016 Survey of Equine Practitioners who were included in
the analysis were either 1) employed in clinical veterinary medicine, 2) employed, but not in
clinical veterinary medicine, 3) retired from the general workforce, or 4) unemployed.
Depending on their current life situation, survey subjects were asked a specific set of questions
relating to their employment status. Questions in the survey explored demographics,
education, educational debt, internship and residency participation, employment,
underemployment, unemployment, retirement, career satisfaction, staff utilization,
compensation, practice ownership, the business environment, finances, health and wellness,
and specific equine industry factors.
In this report, the following datasets were analyzed:
1. The AAEP membership database was utilized to develop aggregate gender, age and ZIP code
information. Only aggregate statistics from this dataset are reported. This information was used
to determine the “weights” required to adjust responses to align with the demographics for
equine practitioners. This database can be found in the “Demographics “and “Geographic
Distribution of Equine Practitioners” sections of this report. These data are referred to as “AAEP
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Members” in this section of the report. The number of observations in the AAEP membership
database was N=7,432.
2. The AVMA-AAEP 2016 Survey of Equine Practitioners, which comprises survey responses from
AAEP members, is referred to as “AAEP” throughout the report. The number of AAEP
observations (respondents) was N=975.
3. The AVMA’S 2016 Census of Veterinarians, which comprises survey responses from AVMA
members, is referred to as “AVMA” throughout the report. The number of AVMA observations
(respondents) was N=2,545.
4. The combined dataset of AAEP (N=975) and the self-identified equine practitioners from the
AVMA (N=81), is collectively called “Equine.” The number of such combined Equine
observations (respondents) was N=1,056.
In the analysis, the demographics of the AAEP sample and the equine practitioners from the
AVMA sample are both strongly correlated to the AAEP membership. Thus the combined
Equine sample is representative of the AAEP members. As such, the Equine sample is compared
to the AVMA sample (in cases where they can be compared) unless otherwise noted.
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Table of Contents
Objective ......................................................................................................................................... 3
Introduction .................................................................................................................................... 5
Executive Summary....................................................................................................................... 11
General Economic Conditions ................................................................................................... 13
Demographics of Equine Practitioners ..................................................................................... 13
The Market for Veterinary Education ....................................................................................... 17
The Market for Veterinarians ................................................................................................... 27
The Market for Veterinary Services .......................................................................................... 43
A Portrait of the Equine Veterinary Practice ............................................................................ 44
Economic Impacts of the Equine Veterinary Industry .............................................................. 55
Data Sources and Methods ........................................................................................................... 58
List of Figures ................................................................................................................................ 66
List of Tables.................................................................................................................................. 79
Section 1: General Economic Conditions ...................................................................................... 90
1.1 Business Cycle Index ........................................................................................................... 91
1.2 Index of Leading Economic Indicators ................................................................................ 94
Section 2: Demographics ............................................................................................................ 100
2.1 Demographics of Respondents ......................................................................................... 100
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2.1.1 Year of Graduation and Age........................................................................................... 100
2.1.2 Veterinary Medical College Attended............................................................................ 102
2.1.3 Gender............................................................................................................................ 104
2.1.4 Type of Employment ...................................................................................................... 107
2.1.5 Racial/Ethnic Group ....................................................................................................... 108
2.1.6 Regional Distribution ..................................................................................................... 110
2.1.7 Living Environment and Work Location ......................................................................... 113
2.1.8 Marital Status ................................................................................................................. 115
Section 3: The Market for Veterinary Education ........................................................................ 116
3.1 Supply of Veterinary Education ........................................................................................ 116
3.2 North American Veterinary Licensing Exam ..................................................................... 118
3.3 Supply of Seats from AVMA-Accredited Schools .............................................................. 119
3.4 The Cost of Veterinary Education ..................................................................................... 120
3.5 Distribution of New Veterinarians .................................................................................... 122
3.6 Veterinary College Outcomes of Veterinarians in the Equine Profession ........................ 125
3.6.1 Externship Participation ................................................................................................. 125
3.6.2 Internship Participation ................................................................................................. 126
3.6.3 Residency Participation.................................................................................................. 166
3.6.4 College Preparedness..................................................................................................... 176
3.6.5 Most Important Skills for New Veterinarians ................................................................ 178
3.6.6 Equine Veterinarians Leaving the Equine Profession .................................................... 185
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3.6.7 New Veterinarian Starting Salaries ................................................................................ 191
3.7 Educational Debt of New Veterinarians ........................................................................... 198
3.7.1 Summary Statistics ......................................................................................................... 199
3.7.2 Difference in Student Debt for Selected Characteristics ............................................... 204
3.7.3 Factors Affecting Veterinary Educational Student Debt upon Graduation ................... 216
3.8 Expectations before Entering Profession.......................................................................... 220
3.9 Key Performance Indicator: Debt-To-Income Ratio (DIR) of New Veterinarians ............. 223
3.9.1 Factors Affecting Debt-to-Income Ratio ........................................................................ 225
Section 4: The Market for Veterinarians..................................................................................... 230
4.1 Equine Veterinary Profession Incomes ............................................................................. 230
4.1.1 Summary Statistics ......................................................................................................... 231
4.1.2 Differences in Professional Income for Selected Characteristics .................................. 235
4.1.3 Factors Affecting Income ............................................................................................... 250
4.2 Fringe Benefits Received................................................................................................... 257
4.3 Family Status ..................................................................................................................... 261
4.4 Market Key Performance Indicator: Net Present Value ................................................... 266
4.4.1 Age Earnings Profile ....................................................................................................... 266
4.4.2 Net Present Value (NPV) of the DVM Degree................................................................ 268
4.5 Equine Veterinary Profession Employment ...................................................................... 276
4.5.1 Full-Time and Part-Time Employment ........................................................................... 280
4.5.2 Summary Statistics ......................................................................................................... 287
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4.5.3 Employment Satisfaction ............................................................................................... 289
4.5.4 Retirement ..................................................................................................................... 320
4.6 Equine Veterinary Profession Unemployment ................................................................. 324
4.6.1 Summary Statistics ......................................................................................................... 325
4.6.2 Factors Affecting Unemployment .................................................................................. 328
4.7 Equine Veterinary Profession Underemployment............................................................ 331
4.7.1 Veterinarians Who Wish to Work More (Underemployment) ...................................... 348
4.7.2 Veterinarians Who Wish to Work Less (Negative Underemployment)......................... 353
4.7.3 Factors Correlated with Underemployment.................................................................. 359
4.8 Health and Wellness ......................................................................................................... 366
4.8.1 Physical and Mental Health ........................................................................................... 366
4.8.2 Professional Quality of Life ............................................................................................ 389
4.9 Geographic Distribution of Equine Practitioners .............................................................. 431
Section 5: Market for Veterinary Services .................................................................................. 434
5.1 Supply of Equids in the United States ............................................................................... 436
5.1.1 Number of Equine-Pet-Owning Households.................................................................. 438
5.1.2 Location.......................................................................................................................... 439
5.1.3 Veterinary Visits ............................................................................................................. 440
5.2 Demand for Equine Private Practice Veterinary Services ................................................. 442
Section 6: Equine Practice........................................................................................................... 444
6.1 Equine Sectors................................................................................................................... 445
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6.2 Staff Utilization.................................................................................................................. 460
6.3 Service Calls....................................................................................................................... 470
6.4 Parallel Service Providers .................................................................................................. 479
6.5 Practice Ownership ........................................................................................................... 488
6.6 Compensation Methods.................................................................................................... 500
6.7 Returns to Equine Veterinary Practice.............................................................................. 518
6.7.1 Personal Gross Revenue of Production for 2015........................................................... 518
6.7.2 Total Practice Gross Revenue of Production ................................................................. 532
6.7.3 Average Gross Collected Revenue ................................................................................. 536
6.7.4 Revenue and Income Contraction and Expansion of Equine Practices ......................... 542
6.7.5 Total Practice Expenses/Deductions for 2015 ............................................................... 549
6.7.6 Current Ratio .................................................................................................................. 555
6.7.7 Profit Centers/Activity Centers ...................................................................................... 559
Section 7: ECONOMY-WIDE IMPACTS of Equine Practices......................................................... 566
7.1 IMPLAN software and Input/Output Analysis .................................................................. 566
7.2 Results and Discussion ...................................................................................................... 568
Recognition of Authors ............................................................................................................... 574
References................................................................................................................................... 575
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LIST OF FIGURES
Figure 1: Distribution of Equine Respondents' Age by Gender .................................................... 15
Figure 2: Distribution of Equine Respondents' Years of Experience by Gender .......................... 15
Figure 3: Economy Key Performance Indicator - Real Gross Domestic Product, 1930-2017 ....... 91
Figure 4: Real Median Household Income in the United States, 1984-2016 ............................... 94
Figure 5: The Conference Board's Leading Economic Index ......................................................... 96
Figure 6: Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 1982-
2017............................................................................................................................................... 97
Figure 7: Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 2009-
2017............................................................................................................................................... 98
Figure 8: Congressional Budget Office 10-Year Baseline Forecast of U.S. GDP............................ 99
Figure 9: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by
Graduation Year .......................................................................................................................... 101
Figure 10: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by Age
..................................................................................................................................................... 102
Figure 11: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by
Gender......................................................................................................................................... 104
Figure 12: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by
Gender and Age .......................................................................................................................... 106
Figure 13: Distribution of Equine and AVMA Respondents by Type of Employment ................ 107
Figure 14: Distribution of Equine and AVMA Respondents by Racial/Ethnic Group.................. 108
Figure 15: Distribution of Equine and AVMA Respondents by Age and Racial/Ethnic Group ... 110
Figure 16: U.S. Postal Service Regions of the United States....................................................... 111
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Figure 17: Distribution of Equine and AVMA Respondents by U.S. Region of Employment...... 112
Figure 18: Distribution of Equine and AVMA Respondents by Living Environment/Community
..................................................................................................................................................... 113
Figure 19: Distribution of Equine and AVMA Respondents by Marital Status ........................... 115
Figure 20: Association of American Veterinary Medical Colleges (AAVMC) Veterinary School
Applicant Figures, AAVMC Internal Data Reports, 1980-2018 .................................................. 117
Figure 21: North American Veterinary Licensing Exam National Pass Rate ............................... 118
Figure 22: U.S. Veterinary Graduates, All Sources, 1980-2025 .................................................. 119
Figure 23: Distribution of Veterinary School Applicants and Their Desired Career Path ........... 123
Figure 24: Distribution of New Veterinarians in Equine Private Practice................................... 124
Figure 25: Distribution of New Veterinarians in Private Practice ............................................... 124
Figure 26: Distribution of AAEP Respondents by Externship Participation ................................ 126
Figure 27: Distribution of Equine and AVMA Respondents by Internship Participation ........... 128
Figure 28: Distribution of Equine and AVMA Respondents Internship Participation by Gender129
Figure 29: Distribution of Equine and AVMA Respondents by Year of Completed Internship .. 130
Figure 30: Distribution of Equine and AVMA Respondents by Internship Program .................. 131
Figure 31: Distribution of Equine and AVMA Respondents by Internship Program and Gender
..................................................................................................................................................... 132
Figure 32: Distribution of AAEP Respondents by Internship Compensation Package Which
Includes/Included Free Housing ................................................................................................. 139
Figure 33: Distribution of AAEP Respondents’ Vacation Days Allotted for Internships by
Graduation Year .......................................................................................................................... 144
Figure 34: Distribution of Equine and AVMA Respondents’ First Post-Internship Salary by Year of
Graduation .................................................................................................................................. 145
Figure 35: Distribution of Equine and AVMA Respondents’ Program Focus of Internship ........ 147
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Figure 36: Distribution of Equine and AVMA Respondents’ Program Focus of Internship by
Gender......................................................................................................................................... 149
Figure 37: Distribution of Equine and AVMA Respondents by Species Focus of Internship ...... 152
Figure 38: Distribution of Equine and AVMA Respondents’ Internship Satisfaction by Gender 154
Figure 39: Distribution of Equine and AVMA Respondents’ by Satisfaction with Specific
Internship Expectations .............................................................................................................. 159
Figure 40: Distribution of Equine Respondents by Likelihood of Future Internship Participation
..................................................................................................................................................... 160
Figure 41: Distribution of Equine and AVMA Respondents’ Participation in a Residency ......... 167
Figure 42: Distribution of AAEP Respondents (Who Applied or Attempted to Participate in a
Residency) by Residency Participation ....................................................................................... 168
Figure 43: Distribution of Equine and AVMA Respondents by Year of Completed (or Future
Completion) Residency ............................................................................................................... 169
Figure 44: Distribution of Equine and AVMA Respondents Who Participated in a Residency by
Gender......................................................................................................................................... 170
Figure 45: Distribution of Equine and AVMA Respondents Who Stated They Were Participating
in an Internship because They Planned to Apply for a Residency, and Their Residency
Completion Status by Gender ..................................................................................................... 171
Figure 46: Distribution of Equine and AVMA Respondents by Program Focus of Residency .... 172
Figure 47: Distribution of Equine and AVMA Respondents by Species Focus of Residency ...... 173
Figure 48: Distribution of Equine and AVMA Respondents’ Attitudes about College Education
Preparation by Graduation Year ................................................................................................. 178
Figure 49: AAEP Membership Attrition by Graduation Year, 2000-2012 ................................... 186
Figure 50: Distribution of Equine Respondents Leaving the Equine Profession by Timeframe of
Departure .................................................................................................................................... 187
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Figure 51: Distribution of Equine Respondents Who Reported Leaving the Equine Profession
within Five Years after Graduation by Graduation Year ............................................................. 188
Figure 52: Mean Starting Salaries of New Veterinarians ............................................................ 192
Figure 53: Mean Starting Salaries of New Veterinarians — Private Practice ............................. 193
Figure 54: Real Mean Debt for New Graduates in the Equine Profession vs. All Other Veterinary
Fields ........................................................................................................................................... 198
Figure 55: Distribution of Equine and AVMA Respondents’ Pre-Veterinary Educational Debt by
Gender......................................................................................................................................... 200
Figure 56: Distribution of Equine and AVMA Respondents’ Pre-Veterinary Educational Debt by
Graduation Year .......................................................................................................................... 201
Figure 57: Distribution of Equine and AVMA Respondents’ Gross Annual Compensation that
Debt Repayment Requires .......................................................................................................... 203
Figure 58: Mean Debt-to-Income Ratio of New AVMA Equine Veterinarians and All New AVMA
Veterinarians by Graduation Year .............................................................................................. 224
Figure 59: Distribution of Respondents’ Mean Income by DVMs .............................................. 232
Figure 60: Distribution of Respondents’ Mean Income by Gender and Full-Time vs. Part-Time
Employment ................................................................................................................................ 233
Figure 61: Distribution of AAEP Mean Veterinary Income by Practice Size (Veterinarians and
Support Staff) .............................................................................................................................. 234
Figure 62: Distribution of Respondents' Mean Income and Internship Participation by
Graduation Year .......................................................................................................................... 240
Figure 63: Map of U.S. Regions with Respect to Mean Annual Income of Equine and AVMA
Respondents ............................................................................................................................... 246
Figure 64: Distribution of AAEP Respondents’ Children Status .................................................. 261
Figure 65: Distribution of Equine and AVMA Respondents’ Age of Children in Household ...... 262
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Figure 66: Distribution of AAEP Respondents’ Number of Weeks of Maternity/Paternity Leave
Offered by Employer (Paid or Unpaid) ....................................................................................... 263
Figure 67: Distribution of AAEP Respondents’ Maternity/Paternity Leave That Is Eligible for
Compensation ............................................................................................................................. 264
Figure 68: Distribution of AAEP Respondents’ Employer That Continues to Provide Benefits
during Maternity/Paternity Leave .............................................................................................. 265
Figure 69: Distribution of AAEP Respondents’ Length of Time Their Employer Provides Benefits
during Maternity/Paternity Leave .............................................................................................. 265
Figure 70: Distribution of AAEP Respondents and Whether or Not Maternity/Paternity Leave
Policy Has Been Well Addressed in Employment Contracts....................................................... 266
Figure 71: Equine Practitioner and General Veterinary Practitioner Age-Earnings Profiles by
Gender......................................................................................................................................... 268
Figure 72: Net Present Value of the DVM Degree of General Veterinary Practitioners by Gender
..................................................................................................................................................... 270
Figure 73: Net Present Value of the DVM Degree of Equine Practitioners by Gender .............. 271
Figure 74: Distribution of Equine and AVMA Respondents’ Number of Hours Worked per Week
(Regular and Emergency Hours) by Gender ............................................................................... 279
Figure 75: Distribution of Equine and AVMA Respondents Full- and Part-Time Employment
Status in Clinical Veterinary Medicine ........................................................................................ 280
Figure 76: Distribution of Equine and AVMA Respondents’ Regular Hours Worked per Week in
Clinical Veterinary Medicine ....................................................................................................... 281
Figure 77: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked per Week
in Clinical Veterinary Medicine as a Percentage of Total Hours Worked ................................... 282
Figure 78: Distribution of Equine and AVMA Respondents’ Part-Time Regular Hours Worked per
Week in Clinical Veterinary Medicine ......................................................................................... 284
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Figure 79: Distribution of Equine and AVMA Respondents’ Part-Time Emergency Hours Worked
per Week in Clinical Veterinary Medicine .................................................................................. 285
Figure 80: Distribution of Equine Respondents and the Percentage of the Total Amount of On-
Call/Emergency Duty That They Perform at Their Place of Employment................................... 286
Figure 81: Distribution of Equine Respondents and the Percentage of the Total Amount of On-
Call/Emergency Duty That They Perform at Their Place of Employment by Number of
Veterinarians at Their Place of Employment .............................................................................. 287
Figure 82: Distribution of Equine and AVMA Respondents by Years with Current Employer ... 288
Figure 83: Distribution of AAEP Respondents’ Likelihood That They Will Choose to Remain
Employed at Their Organization over the Next Five Years by Gender ....................................... 297
Figure 84: Distribution of AAEP Respondents' Likelihood That They Will Choose to Remain
Employed at Their Organization over the Next Five Years by Graduation Year......................... 298
Figure 85: Distribution of AAEP Respondents' Length of Time with Most Recent Previous Place
of Employment............................................................................................................................ 299
Figure 86: Distribution of AAEP Respondents' Level of Satisfaction with Most Recent Previous
Place of Employment by Gender ................................................................................................ 300
Figure 87: Distribution of AAEP Respondents’ Level of Satisfaction with Most Recent Previous
Place of Employment by Graduation Year .................................................................................. 301
Figure 88: Distribution of Equine and AVMA Respondents’ Desire to Change the Veterinary
Sector in Which They Currently Work (if they could) by Current Employment Satisfaction ..... 303
Figure 89: Distribution of Equine and AVMA Respondents’ Desire to Change the Veterinary
Sector in Which They Currently Work (if they could) by Graduation Year................................. 304
Figure 90: Distribution of Equine and AVMA Respondents’ Desire to Change the Geographic
Location in Which They Currently Work (if they could) by Current Employment Satisfaction .. 310
Figure 91: Distribution of Equine and AVMA Respondents’ Desire to Change the Geographic
Location in Which They Currently Work (if they could) by Graduation Year ............................. 311
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Figure 92: Distribution of Equine and AVMA Respondents’ Number of Miles They Are Willing to
Relocate for Better Career Opportunities .................................................................................. 316
Figure 93: Distribution of Equine and AVMA Respondents’ Preferred Workplace Size by
Graduation Year .......................................................................................................................... 318
Figure 94: Distribution of Equine and AVMA Respondents’ Preference for Community Size by
Gender......................................................................................................................................... 319
Figure 95: Distribution of Equine and AVMA Respondents Who Retired with Respect to Number
of Years since Retirement ........................................................................................................... 320
Figure 96: Distribution of Equine and AVMA Respondents’ Anticipated Years to Retirement.. 321
Figure 97: Distribution of Unemployed Equine and AVMA Respondents by Graduation Year.. 325
Figure 98: Distribution of Unemployed Equine and AVMA Respondents by Type of
Employment/Enrollment Area They Are Seeking ....................................................................... 326
Figure 99: Distribution of Equine and AVMA Respondents’ Preference in Work Hours............ 332
Figure 100: Distribution of Equine and AVMA Respondents’ Preference in Hours Worked by
Gender......................................................................................................................................... 333
Figure 101: Distribution of Equine and AVMA Respondents’ Current Hours Worked and Desire
to Change Hours Worked............................................................................................................ 335
Figure 102: Distribution of Equine and AVMA Respondents’ Change in Hours Desired by Gender
..................................................................................................................................................... 336
Figure 103: Distribution of Equine and AVMA Respondents’ Net Hours Desired by Gender .... 338
Figure 104: Distribution of Female Equine and AVMA Respondents’ Work Hour Preference by
Number of Years since DVM/VMD Graduation .......................................................................... 339
Figure 105: Distribution of Male Equine and AVMA Respondents’ Work Hour Preference by
Number of Years since DVM/VMD Graduation .......................................................................... 341
Figure 106: Distribution of Equine and AVMA Respondents’ Desired Work Hour Preference by
Type of Employment ................................................................................................................... 343
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Figure 107: Distribution of Equine and AVMA Respondents’ Work Preference — Practice
Owners vs. Non-Practice Owners ............................................................................................... 344
Figure 108: Distribution of AAEP Respondents’ Work Preference by Primary Equine Sector ... 345
Figure 109: Distribution of AAEP Respondents’ Work Preference by Business Model.............. 347
Figure 110: Distribution of Equine and AVMA Respondents’ Underemployment by Gender ... 349
Figure 111: Distribution of Equine and AVMA Respondents’ Underemployment by Region .... 350
Figure 112: Distribution of Equine Respondents’ Underemployment by Primary Equine Sector
..................................................................................................................................................... 351
Figure 113: Distribution of Equine Respondents’ Underemployment by Business Model ........ 352
Figure 114: Distribution of Equine and AVMA Respondents’ Negative Underemployment by
Gender......................................................................................................................................... 354
Figure 115: Distribution of Equine and AVMA Respondents’ Negative Underemployment by
Region ......................................................................................................................................... 355
Figure 116: Distribution of Equine Respondents’ Negative Underemployment by Primary Equine
Sector .......................................................................................................................................... 356
Figure 117: Distribution of Equine Respondents’ Negative Underemployment by Business Model
..................................................................................................................................................... 357
Figure 118: Distribution of AAEP Respondents’ Physical and Mental Health Condition by Gender
..................................................................................................................................................... 367
Figure 119: Distribution of AVMA Respondents’ Health Condition by Gender ......................... 368
Figure 120: Distribution of AAEP and AVMA Respondent Associates’ Physical and Mental Health
Condition by Gender ................................................................................................................... 370
Figure 121: Distribution of AAEP and AVMA Respondent Owners’ Physical and Mental Health
Condition by Gender ................................................................................................................... 371
Figure 122: Distribution of AAEP Respondents’ Physical and Mental Health Condition by
Graduation Year .......................................................................................................................... 373
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Figure 123: Distribution of AAEP Respondents’ Physical and Mental Health Limitations on Daily
Activities ...................................................................................................................................... 374
Figure 124: Distribution of AAEP Respondents' Number of Days out of Work Related to Injury
Suffered at Work (select all that apply) ...................................................................................... 376
Figure 125: Distribution of AAEP Respondents' Number of Injuries Incurred While Practicing
Veterinary Medicine That Caused Missed Work Time ............................................................... 377
Figure 126: Distribution of AAEP Respondents' Result of a Work-Related Injury by Gender .... 378
Figure 127: Distribution of How AAEP Respondents’ Health Limited Vigorous Activities by
Gender......................................................................................................................................... 379
Figure 128: Distribution of How AAEP Respondents’ Health Limited Moderate Activities by
Gender......................................................................................................................................... 380
Figure 129: Distribution of AAEP Respondents’ Level of Bodily Pain during the Past Four Weeks
by Graduation Year ..................................................................................................................... 387
Figure 130: Distribution of AAEP Respondents’ Level of Pain Interference during the Last Past
Four Weeks by Graduation Year ................................................................................................. 388
Figure 131: Distribution of Equine and AVMA Respondents’ Compassion Satisfaction Score .. 394
Figure 132: Distribution of Equine and AVMA Respondents’ Burnout Score ............................ 407
Figure 133: Distribution of Equine and AVMA Respondents’ Secondary Traumatic Stress Score
..................................................................................................................................................... 418
Figure 134: Concentration of Equine Respondents in the United States, 2016 ......................... 431
Figure 135: Concentration of AAEP Members in the United States, 2016 ................................. 432
Figure 136: Concentration of AVMA Respondents in the United States, 2016.......................... 433
Figure 137: Total Number of Farm Mules, Burros and Donkeys in the United States ............... 436
Figure 138: Total Number of Farm Horses and Ponies in the United States.............................. 437
Figure 139: Total Number of Pet Equids in the United States, 1981-2016 ................................ 438
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Figure 140: Percentage and Number of Households That Owned a Horse, Dec. 31, 1991-2016
..................................................................................................................................................... 439
Figure 141: Distribution of AAEP Equine Practitioner Respondents and the Type of Equine
Sector They Primarily Serve ........................................................................................................ 446
Figure 142: Concentration of Equine Respondents by Primary Equine Industry Sector, 2016 .. 447
Figure 143: Distribution of AAEP Respondent’s Frequent Primary Contact for Horse Patient .. 451
Figure 144: Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient by
Primary Equine Sector................................................................................................................. 455
Figure 145: Distribution of AAEP Respondents’ Ranking of Communication Method with Clients
..................................................................................................................................................... 459
Figure 146: Distribution of Full-Time Equivalent (FTE) Veterinarians at a Practice ................... 461
Figure 147: Distribution of Number of FTE Employees in a Practice.......................................... 462
Figure 148: Distribution of the Utilization of Veterinary Technicians and Other Support Staff on
Ambulatory Calls ......................................................................................................................... 464
Figure 149: Distribution of the Utilization of Veterinary Technicians and Other Support Staff
after Business Hours ................................................................................................................... 465
Figure 150: Distribution of the Utilization of Veterinary Technicians and Other Support Staff on
Ambulatory Calls by Number of FTE Veterinarians at a Practice ............................................... 466
Figure 151: Distribution of the Utilization of Veterinary Technicians and Other Support Staff
after Business Hours by Number of FTE Veterinarians at a Practice.......................................... 467
Figure 152: Distribution of AAEP Respondents’ Primary Practice Business Model In 2015....... 471
Figure 153: Distribution of AAEP Respondents’ Primary Practice Service Area Radius (in miles)
..................................................................................................................................................... 475
Figure 154: Distribution of AAEP Respondents Miles Traveled for Work Each Year While
Practicing Equine Medicine......................................................................................................... 477
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Figure 155: Do you think your practice’s revenue stream has been reduced by services provided
by any of the following types of parallel service providers? (select all that apply) ................... 480
Figure 156: Maps of Parallel Veterinary Service Providers Affecting AAEP Respondents’ Revenue
..................................................................................................................................................... 484
Figure 157: Distribution of the Number of Equine Veterinarians Competing in AAEP
Respondents’ Service Area ......................................................................................................... 485
Figure 158: Distribution of Competing Equine Veterinarians in an AAEP Respondent’s Service
Area ............................................................................................................................................. 486
Figure 159: Distribution of AAEP Respondent Owners by Practice Ownership Structure ......... 488
Figure 160: Distribution of AAEP and AVMA Respondents’ Interest in Buying Shares or Becoming
a Practice Owner by Gender ....................................................................................................... 490
Figure 161: Distribution of AAEP Respondents' Confidence Level in Obtaining Practice
Ownership Interest in a Practice within the Next 18 Months .................................................... 491
Figure 162: Distribution of AAEP Respondent Owners’ Confidence Level Who Want to Sell Their
Ownership Interest ..................................................................................................................... 492
Figure 163: Distribution of AAEP Respondent Owners Who Want to Sell Their Practice Interest:
Confidence in Ability to Sell Shares by Practice Size .................................................................. 493
Figure 164: Distribution of AAEP Respondent Owners Who Want to Sell Their Practice:
Confidence in Ability to Sell by Gross Collected Practice Revenue (per Year in the Last Three
Years)........................................................................................................................................... 494
Figure 165: Distribution of AAEP Respondents' Entity That Is Most Likely to Purchase Ownership
Interest ........................................................................................................................................ 495
Figure 166: Distribution of AAEP Respondent Associates’ Preferred Method of Compensation
..................................................................................................................................................... 504
Figure 167: Distribution of AAEP Respondents’ Owner Compensation with Differentiation and
with No Differentiation between Pay for Effort as a Veterinarian and Pay as an Owner .......... 510
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Figure 168: Percentage of Equine and AVMA Respondents’ Household Income Contribution by
Gender......................................................................................................................................... 513
Figure 169: Percentage of Equine and AVMA Respondents’ Household Income Contribution by
Graduation Year .......................................................................................................................... 514
Figure 170: Distribution of AAEP Respondents’ Compensation of Practice Management Duties
by Gender.................................................................................................................................... 515
Figure 171: Distribution of AAEP Respondents’ Compensation for Practice Management Duties
by Graduation Year ..................................................................................................................... 516
Figure 172: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue
of Production by Employment Status ......................................................................................... 520
Figure 173: Distribution of Equine and AVMA Respondents' 2015 Total Personal Gross Revenue
of Production by Graduation Year .............................................................................................. 523
Figure 174: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue
of Production by Gender............................................................................................................. 525
Figure 175: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue
of Production by Income............................................................................................................. 529
Figure 176: Distribution of AAEP Respondents’ 2015 Total Personal Gross Revenue of
Production by FTE Veterinarians in a Practice ............................................................................ 531
Figure 177: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned
per Year for Their Practice (over the last three years) by Practice Ownership Type ................. 537
Figure 178: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned
per Year for Their Practice (over the last three years) by Number of FTE Veterinarians in a
Practice........................................................................................................................................ 538
Figure 179: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned
per Year for Their Practice (over the last three years) by Equine Sector ................................... 539
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Figure 180: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned
per Year for Their Practice (over the last three years) by Business Model ................................ 541
Figure 181: Distribution of AAEP Respondents’ Practice Gross Revenue Change in 2015
Compared to 2014 ...................................................................................................................... 543
Figure 182: Distribution of AAEP Respondents’ Practice Gross Revenue Contraction from 2014-
2015............................................................................................................................................. 544
Figure 183: Distribution AAEP Respondents’ Practice Gross Revenue Expansion from 2014-2015
..................................................................................................................................................... 545
Figure 184: Distribution of AAEP Respondents’ Net Income Change in 2015 Compared to 2014
..................................................................................................................................................... 547
Figure 185: Distribution of AAEP Respondents’ Practice Net Income Contraction from 2014-
2015............................................................................................................................................. 548
Figure 186: Distribution AAEP Respondents’ Practice Net Income Expansion from 2014-2015 549
Figure 187: Equine Practice Profit Centers (Largest to Smallest) ............................................... 560
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LIST OF TABLES
Table 1: Length of U.S. Business Cycles, 1953-2009 ..................................................................... 92
Table 2: Distribution of Equine and AVMA Respondents by Veterinary College ....................... 103
Table 3: Distribution of Equine and AVMA Respondents by Desire to Change Living
Environment/Community ........................................................................................................... 114
Table 4: Tuition/Fees and Total Cost of a DVM Degree by Veterinary School ........................... 121
Table 5: Distribution of Veterinary School Applicants’ Age When They Develop an Interest in
Veterinary Medicine ................................................................................................................... 122
Table 6: Distribution of Equine and AVMA Respondents by Internship Program and Graduation
Year ............................................................................................................................................. 133
Table 7: Distribution of Equine and AVMA Respondents’ Reasons for Undertaking an Internship
by Gender and Graduation Year ................................................................................................. 135
Table 8: Distribution of Elements Included in Equine Internships, Selecting All That Applied to
AAEP Respondents ...................................................................................................................... 137
Table 9: Distribution of Equine and AVMA Respondents’ Internship Stipends/Salaries by Gender
..................................................................................................................................................... 138
Table 10: Distribution of Equine and AVMA Respondents’ Internship Stipends/Salaries by
Graduation Year .......................................................................................................................... 138
Table 11: Distribution of AAEP Respondents’ Internship Housing Status with Respect to Intern
Salaries and Graduation Year...................................................................................................... 140
Table 12: Means of Equine Monthly Value of Housing per Month ............................................ 141
Table 13: Percentage of Benefits Provided by Equine First, or Only, Internship ....................... 142
Table 14: Percentage of Benefits Provided by Equine First, or Only, Internship by Graduation
Year ............................................................................................................................................. 143
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Table 15: Mean Distribution of Equine and AVMA Respondents’ Post-Internship Salary by
Gender and Graduation Year ...................................................................................................... 146
Table 16: Distribution of Equine and AVMA Respondents’ Program Focus of Internship by
Gender and Graduation Year ...................................................................................................... 150
Table 17: Distribution of Equine and AVMA Respondents by Primary Focus of Internship....... 153
Table 18: Distribution of Equine and AVMA Respondents’ Internship Satisfaction by Graduation
Year ............................................................................................................................................. 155
Table 19: Factors That Are Significant in Explaining the Population of Veterinarians Who
Participated in an Internship After Graduation .......................................................................... 163
Table 20: Distribution of Equine and AVMA Respondents by Primary Focus of Residency ....... 174
Table 21: Distribution of Board-Certified Equine and AVMA Respondents by AVMA-Recognized
Veterinary Specialty Organizations ............................................................................................. 175
Table 22: Distribution of AAEP Respondents and the Importance of Specific Procedures for New
Associates to Have Mastery of.................................................................................................... 179
Table 23: Distribution of AAEP Respondents and the Importance of Specific Procedures for New
Associates to Have Mastery by Years of Experience .................................................................. 181
Table 24: Distribution of AAEP Respondents’ Important Competencies of New Associates ..... 185
Table 25: Factors That Are Significant in Explaining the Population of Veterinarians Who Have
Left the Equine Profession within Five Years of Entering the Profession After Graduation ...... 191
Table 26: Factors Affecting Starting Salaries of New Veterinarians ........................................... 196
Table 27: Distribution of Equine and AVMA Respondents’ Mean Student Debt ....................... 201
Table 28: Percentage of Equine and AVMA Respondents’ Annual Compensation Used to Service
Student Loan Debt by Graduation Year ...................................................................................... 204
Table 29: Mean Student Debt with Respect to the Number of Years since Graduation........... 205
Table 30: Mean Student Debt with Respect to Additional Degree ............................................ 206
Table 31: Mean Student Debt with Respect to Internship Participation ................................... 207
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Table 32: Mean Student Debt with Respect to Residency Participation.................................... 208
Table 33: Mean Student Debt with Respect to Board Certificate .............................................. 208
Table 34: Mean Student Debt with Respect to Gender.............................................................. 209
Table 35: Mean Student Debt with Respect to Type of Employment ........................................ 210
Table 36: Mean Student Debt with Respect to Work Region..................................................... 212
Table 37: Mean Student Debt with Respect to Practice Ownership by Years from Graduation
..................................................................................................................................................... 213
Table 38: Mean Student Debt with Respect to Type of Community .......................................... 214
Table 39: Mean Student Debt with Respect to Primary Equine Sector...................................... 215
Table 40: Mean Student Debt with Respect to Size of Community ........................................... 216
Table 41: Factors Affecting Educational Student Debt upon Graduation .................................. 218
Table 42: Competency Scores by College Preparedness ............................................................ 221
Table 43: Distribution of Weighted New Veterinarian Debt-to-Income Ratio ........................... 223
Table 44: Factors Affecting Debt-to-Income Ratio ..................................................................... 227
Table 45: Mean Annual Income with Respect to the Number of Years since DVM Graduation 237
Table 46: Mean Annual Income with Respect to Additional Degree Graduation ...................... 238
Table 47: Mean Annual Income with Respect to Internship Participation................................. 239
Table 48: Mean Annual Income with Respect to Residency Participation ................................. 241
Table 49: Mean Annual Income with Respect to Gender ........................................................... 242
Table 50: Mean Annual Income with Respect to Type of Employment ..................................... 243
Table 51: Mean Annual Income with Respect to Region............................................................ 244
Table 52: Mean Annual Income with Respect to Practice Ownership ....................................... 247
Table 53: Mean Annual Income with Respect to Board-Certified Practice Owners and Board-
Certified Associates..................................................................................................................... 248
Table 54: Mean Annual Income with Respect to Primary Equine Sector ................................... 249
Table 55: Factors Affecting Income ............................................................................................ 252
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Table 56: Fringe Benefits Received ............................................................................................. 257
Table 57: Fringe Benefits Received with Respect to Gender, Excluding True Solo Practitioners
..................................................................................................................................................... 258
Table 58: Distribution of Equine Primary Assets for Retirement ............................................... 260
Table 59: Distribution of Assets for Retirement among Respondents (select all that apply) .... 260
Table 60: Mean Number of Children in Equine and AVMA Respondents’ Household............... 262
Table 61: Mean Veterinary Educational Debt and Mean Starting Salary of Graduating Seniors,
2010 - 2016 ................................................................................................................................. 272
Table 62: Debt-to-Income and Net Present Value by Gender .................................................... 273
Table 63: Distribution of Equine and AVMA Respondents by Employment Status ................... 277
Table 64: Distribution of Equine and AVMA Respondents by Type of Position in a Non-Clinical
Veterinary Medicine Role ........................................................................................................... 277
Table 65: Mean Number of Hours Worked per Week (Regular and Emergency Hours) by Equine
and AVMA Respondents by Gender ........................................................................................... 278
Table 66: Distribution of Full-Time Employee Equine and AVMA Respondents’ Regular Hours
Worked per Week in Clinical Veterinary Medicine..................................................................... 281
Table 67: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked during a
Typical Week ............................................................................................................................... 282
Table 68: Distribution of Equine and AVMA Respondents’ Part-Time Regular Hours Worked per
Week in Clinical Veterinary Medicine Emergency Hours ........................................................... 283
Table 69: Distribution of Part-Time Equine and AVMA Respondents’ Type of Employment (select
all that apply) .............................................................................................................................. 284
Table 70: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked during a
Typical Week ............................................................................................................................... 285
Table 71: Mean Number of Weeks It Took Equine and AVMA Respondents to Find Their Current
Job ............................................................................................................................................... 287
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Table 72: Distribution of Equine and AVMA Respondents’ Number of Job Offers Received before
Choosing Their Current Employment ......................................................................................... 288
Table 73: Distribution of Equine and AVMA Respondents’ Number of Weeks Worked in 2015289
Table 74: Distribution of Equine and AVMA Respondents’ Satisfaction with Current Employment
by Gender.................................................................................................................................... 289
Table 75: Effect of Equine and AVMA Respondents’ Employment Satisfaction by Gender....... 290
Table 76: Distribution of Equine and AVMA Respondents’ Employment Satisfaction by
Graduation Year .......................................................................................................................... 290
Table 77: Mean Employment Satisfaction of Equine and AVMA Respondents by Year of
Graduation .................................................................................................................................. 291
Table 78: Distribution of Equine and AVMA Respondents’ Employment Satisfaction by Practice
Owners and Associates ............................................................................................................... 292
Table 79: Mean Employment Satisfaction of Equine and AVMA Respondents by Practice Owners
and Associates............................................................................................................................. 292
Table 80: Effect of Employment Satisfaction.............................................................................. 294
Table 81: Factors Affecting Respondents’ Desire to Change Current Veterinary Sector (if they
could) .......................................................................................................................................... 306
Table 82: Factors Affecting a Respondents’ Desire to Change the Geographic Location Where
They Work ................................................................................................................................... 314
Table 83: Distribution of Equine and AVMA Respondents’ Retirement Choice......................... 321
Table 84: Distribution of Equine and AVMA Respondents’ Reasons for Retiring Earlier from
Clinical Veterinary Medicine than Anticipated ........................................................................... 322
Table 85: Distribution of Equine and AVMA Respondents’ Reasons for Delaying Their
Retirement .................................................................................................................................. 324
Table 86: Distribution of Equine and AVMA Respondents’ Type of Employment They Are
Primarily Seeking......................................................................................................................... 327
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Table 87: Factors Affecting Unemployment ............................................................................... 330
Table 88: Distribution of Equine and AVMA Respondents’ Work Preference by Work Region. 333
Table 89: Reasons Equine and AVMA Respondents Want to Work Less (select all that apply) 358
Table 90: Factors Affecting Underemployment.......................................................................... 362
Table 91: Distribution of AAEP Respondents’ Hospitalization and Surgery as a Result of
Performing Work as a Veterinarian by Gender .......................................................................... 378
Table 92: Distribution of How AAEP Respondents’ Health Limited Vigorous and Moderate
Activities by Graduation Year...................................................................................................... 380
Table 93: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in
Work and Other Activities as a Result of Their Physical Health by Gender................................ 381
Table 94: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in
Work and Other Activities as a Result of Their Physical Health by Graduation Year ................. 382
Table 95: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in
Work and Other Activities as a Result of Their Emotional State by Gender .............................. 384
Table 96: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in
Work and Other Activities as a Result of Their Emotional State by Graduation Year ................ 385
Table 97: Distribution of AAEP Respondents’ Bodily Pain and Pain Interference during the Past
Four Weeks by Gender................................................................................................................ 386
Table 98: Raw Scores to ProQOL T-Score Conversion Chart ...................................................... 390
Table 99: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Graduation
Year ............................................................................................................................................. 395
Table 100: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Gender 395
Table 101: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Internship
..................................................................................................................................................... 396
Table 102: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Practice
Ownership ................................................................................................................................... 397
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Table 103: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Board
Certification................................................................................................................................. 398
Table 104: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by
Professional Income.................................................................................................................... 399
Table 105: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Veterinary
Educational Debt......................................................................................................................... 400
Table 106: Mean AAEP Respondents’ Compassion Satisfaction Score by Primary Equine Sector
..................................................................................................................................................... 400
Table 107: Mean AAEP Respondents’ Compassion Satisfaction Score by Business Model ....... 401
Table 108: Factors Affecting Compassion Satisfaction ............................................................... 404
Table 109: Mean Equine and AVMA Respondents’ Burnout Score by Graduation Year ........... 408
Table 110: Mean Equine and AVMA Respondents’ Burnout Score by Gender .......................... 408
Table 111: Mean Equine and AVMA Respondents’ Burnout Score by Internship ..................... 409
Table 112: Mean Equine and AVMA Respondents’ Burnout Score by Practice Ownership ...... 410
Table 113: Mean Equine and AVMA Respondents’ Burnout Score by Board Certification ....... 410
Table 114: Mean Equine and AVMA Respondents’ Burnout Score by Professional Income ..... 411
Table 115: Mean Equine and AVMA Respondents’ Burnout Score by Veterinary Educational
Debt............................................................................................................................................. 412
Table 116: Mean AAEP Respondents’ Burnout Score by Primary Equine Sector ....................... 412
Table 117: Mean AAEP Respondents’ Burnout Score by Business Model ................................. 413
Table 118: Factors Affecting Burnout ......................................................................................... 415
Table 119: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by
Graduation Year .......................................................................................................................... 419
Table 120: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Gender
..................................................................................................................................................... 419
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Table 121: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by
Internship .................................................................................................................................... 420
Table 122: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Practice
Ownership ................................................................................................................................... 421
Table 123: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Board
Certification................................................................................................................................. 421
Table 124: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by
Professional Income.................................................................................................................... 422
Table 125: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by
Veterinary Educational Debt....................................................................................................... 423
Table 126: Mean AAEP Respondents’ Secondary Traumatic Stress Score by Primary Equine
Sector .......................................................................................................................................... 423
Table 127: Mean AAEP Respondents’ Secondary Traumatic Stress Score by Business Model .. 424
Table 128: Factors Affecting Secondary Traumatic Stress.......................................................... 426
Table 129: Mean AAEP Respondents’ Equine Quality of Life Questions by Gender .................. 429
Table 130: Distribution of AAEP Respondent Equine Practitioners and the Secondary Equine
Sector They Served ..................................................................................................................... 448
Table 131: Distribution of AAEP Respondent Equine Practitioners’ Average Number of Unique
Horse Patients Serviced in 2015 with Respect to Primary Equine Sector .................................. 449
Table 132: Distribution of AAEP Respondent Equine Practitioners’ Average Number of Unique
Horse Patients Serviced in 2015 That Were Specifically Mares with Respect to Primary Equine
Sector .......................................................................................................................................... 450
Table 133: Which of the following people do you routinely communicate with about clinical
findings in providing care for your patients?.............................................................................. 456
Table 134: Mean Percentage of AAEP Respondents Who Communicate with Type of Client by
Primary Equine Sector................................................................................................................. 457
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Table 135: Percent of Clients Invoiced by AAEP Respondents for Patient Care ........................ 458
Table 136: Mean FTE Associates per Owner Veterinarians at a Practice ................................... 463
Table 137: Mean FTE Staff Support per FTE Veterinarians (Owners plus Associates) ............... 463
Table 138: Distribution of Duties Assigned to Licensed Technicians and Non-Licensed
Technicians at an AAEP Respondents’ Place of Work (select all that apply).............................. 469
Table 139: Distribution of AAEP Respondents’ Primary Practice Business Model In 2015 by
Primary Equine Sector................................................................................................................. 471
Table 140: Distribution of AAEP Respondents’ Billing of Ambulatory Farm Calls by Primary
Equine Sector .............................................................................................................................. 473
Table 141: Distribution of AAEP Respondents’ Billing of Ambulatory Farm Calls by Business
Model .......................................................................................................................................... 474
Table 142: Mean of AAEP Respondents’ Primary Practice Service Area Radius (in miles) by
Primary Equine Sector................................................................................................................. 475
Table 143: Mean of AAEP Respondents’ Primary Practice Service Area Radius (in miles) by
Business Model ........................................................................................................................... 476
Table 144: Distribution of AAEP Respondents’ Miles Traveled for Work Each Year While
Practicing Equine Medicine by Primary Equine Sector ............................................................... 477
Table 145: Distribution of AAEP Respondents’ Miles Traveled for Work Each Year While
Practicing Equine Medicine by Business Model ......................................................................... 478
Table 146: Distribution of the Number of Competing Veterinarians in a Service Area by Primary
Equine Sector .............................................................................................................................. 487
Table 147: Distribution of AAEP Respondent Owners’ Buy-Sell Agreement by Practice Size .... 495
Table 148: Factors Affecting Interest in Practice Ownership ..................................................... 498
Table 149: Distribution of AAEP Respondents’ Method of Compensation for Their Work as a
Veterinarian ................................................................................................................................ 501
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Table 150: Distribution of AAEP Respondents’ Compensation Method of Associates by Primary
Equine Sector .............................................................................................................................. 502
Table 151: Distribution of AAEP Respondents’ Compensation Method of Associates by Business
Model .......................................................................................................................................... 503
Table 152: Distribution of AAEP Respondent Compensation Method of Owners by Primary
Equine Sector .............................................................................................................................. 505
Table 153: Distribution of AAEP Respondent Compensation Method of Owners by Business
Model .......................................................................................................................................... 507
Table 154: Distribution of AAEP Respondents’ Revenue Production Compensation ................ 511
Table 155: Distribution of AAEP Respondents’ Compensation of Practice Management Duties by
Practice Type ............................................................................................................................... 517
Table 156: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by
Owner and Associate .................................................................................................................. 519
Table 157: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by
Graduation Year .......................................................................................................................... 521
Table 158: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by
Gender......................................................................................................................................... 524
Table 159: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by
Income......................................................................................................................................... 526
Table 160: Mean Personal Gross Revenue of Production of AAEP Respondents by Number of
FTE Veterinarians in a Practice ................................................................................................... 530
Table 161: Mean Practice Gross Revenue of Production of AAEP Respondents by Practice Type
..................................................................................................................................................... 533
Table 162: Practice Gross Revenue of Production of AAEP Respondents by Primary Equine
Sector .......................................................................................................................................... 534
Table 163: Practice Gross Revenue of Production of AAEP Respondents by Business Model... 535
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Table 164: Median 2015 Practice Expenses/Deductions of AAEP Respondents by Practice Type
..................................................................................................................................................... 551
Table 165: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Number of FTE
Veterinarians in a Practice .......................................................................................................... 552
Table 166: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Primary Equine
Sector .......................................................................................................................................... 553
Table 167: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Business Model
..................................................................................................................................................... 554
Table 168: Mean Current Ratio of AAEP Respondents by Practice Type ................................... 556
Table 169: Mean Current Ratio of AAEP Respondents by Number of FTE Veterinarians in a
Practice........................................................................................................................................ 557
Table 170: Mean Current Ratio of AAEP Respondents by Primary Equine Sector ..................... 558
Table 171: Mean Current Ratio of AAEP Respondents by Business Model................................ 559
Table 172: Mean Percent Revenue Received from Services Performed by AAEP Respondents 561
Table 173: Mean Percent Revenue Received from Services Performed by AAEP Respondents by
Primary Equine Sector................................................................................................................. 562
Table 174: Mean Percent Revenue Received from Services Performed by AAEP Respondents by
Business Model ........................................................................................................................... 564
Table 175: Economic Impacts of Equine Veterinary Practice on Employment .......................... 569
Table 176: Economic Impacts of Equine Veterinary Practice on Labor Income ......................... 570
Table 177: Economic Impacts of Equine Veterinary Practice on Total Value Added ................. 571
Table 178: Economic Impacts of Equine Veterinary Practice on Output ................................... 572
Table 179: Economic Impacts of Equine Veterinary Practice on State and Local Tax Revenues 573
Table 180: Economic Impacts of Equine Veterinary Practice on Federal Tax Revenues............ 573
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SECTION 1: GENERAL ECONOMIC CONDITIONS
Animal owners are the driving force for demand in the veterinary services markets. Like all
consumers, their willingness to pay for goods and services is influenced by their level of income.
Assuming that animal owners’ demographic characteristics cannot be distinguished from those
of non-animal owners, national information on disposable income and personal consumption
expenditures provides us with an accurate picture of their economic condition. Because there is
generally a very close relationship between growth in the general economy and growth in
household disposable income and personal consumption expenditures, changes to the general
U.S. economy over a long period of time serve as an important indicator of changes to the
demand for veterinary services.
The performance of the U.S. economy, specifically the U.S. economy’s ability to create
disposable income for residents of the United States, has a major impact on the performance of
the veterinary profession. At the end of 2017, the Gross Domestic Product (GDP) for the U.S.
economy stood at $19.754 trillion, a growth of 4.1 percent over the same period in 2016, but
only a 2.3 percent increase after adjusting for inflation. The real growth in the GDP is the key
performance indicator (KPI) for the U.S. economy, and over the last six years (since the recovery
began in 2012) the average annual rate of growth has been 2.2 percent – a rate that can be
seen as low in comparison to previous economic expansions (Figure 3). Expenditures on goods
and services accounted for $13.654 trillion, with services alone accounting for $9.252 trillion.
Gross private domestic spending accounted for $3.295 trillion of total GDP, while government
spending and investments accounted for $3.406 trillion. Net exports of goods and services
accounted for the remainder of total GDP (Bureau of Economic Analysis).
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Figure 3: Economy Key Performance Indicator - Real Gross Domestic Product, 1930-20174
1.1 BUSINESS CYCLE INDEX
The U.S. economy and all sectors within it experience periods of contraction (recessions) and
expansion (growth). A contraction technically occurs when the economy experiences two
consecutive quarters of negative GDP growth and remains until the economy experiences a
quarter of positive GDP growth.
Historically, the average period of contraction has been 11 months and the average period of
expansion has been 61 months for an average length of cycle (peak to peak) of 72 months. The
last recession began in December of 2007 and ended in June of 2009 (18 months), making this
the longest recessionary period in the last 10 business cycles. The current expansion period has
reached 100 months (as of January 2017), well above the 61-month average period of
4 Source: Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/GDPC1
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
1930 1950 1970 1990 2010
Perc
ent C
hang
e fr
om P
revi
ous Y
ear
Year
Economy KPI
Real Gross Domestic Product, 1930-2017
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expansion but still below the expansion period of recent economic expansions. While the
length of the expansion should not be seen to be a predictor of a recession, the factors that
lead to a recession do appear to occur generally within a decade. At this point in the current
economic expansion, the probability of continued expansion will decline with each month
(Table 1).
Table 1: Length of U.S. Business Cycles, 1953-2009
Recession Periods Peak to trough Previous trough to this peak
July 1953 - May 1954 10 45 August 1957 - April 1958 8 39 April 1960 - February 1961 10 24 December 1969 - November 1970 11 106 November 1973 - March 1975 16 36 January 1980 - July 1980 6 58 July 1981 - November 1982 16 12 July 1990 - March 1991 8 92 March 2001 - November 2001 8 120 December 2007 - June 2009 18 78 Average, 1953-2009 (10 cycles) 11 61 Current Cycle 100 Predicted Cycle 112 - 120
Personal consumption expenditures comprise two-thirds of the U.S. economy, representing
$13.654 trillion of the $19.754 trillion economy in the the fourth quarter of 2017. As noted
earlier, services make up two-thirds of personal consumption expenditures at $9.252 trillion,
while goods comprise the remaining third at $4.402 trillion. Goods can be further
disaggregated into non-durable goods (e.g., food and clothing) and durable goods (e.g.,
automobiles and appliances). Non-durable goods represented $2.884 trillion of personal
consumption expenditures in the fourth quarter of 2017 and durable goods represented $1.518
trillion (Bureau of Economic Analysis). The durable goods component of the economy, while
relatively small, is an important component influencing the business cycle. Services and non-
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durable goods are items that consumers need continuously and thus are unable to eliminate
entirely during a recession. However, durable goods purchases can be minimized by extending
the life of current durable items through repairs.
The business cycle can be described simply as the build-up and draw-down of inventories. At
the bottom of a recession, businesses have more excess capacity than optimum. They may have
laid off employees or reduced employee hours in an attempt to reduce production until
accumulated inventories are drawn down. As inventories are reduced such that production plus
inventories can no longer meet demand, the business must begin to increase production. The
increased production will require increased work hours or number of employees, reducing the
amount of excess production capacity of the firm. The increasing number of employees and
hours worked stimulates the demand for more products and the business must increase
production again. During this economic expansion, firms work to fill orders, increasing
economic activity. Eventually, consumers have all the new durable goods they need and
inventories start to accumulate. This sends a signal to businesses to begin to cut back
production and a new economic contraction occurs. This business cycle is highly dependent on
the demand for durable goods and the amount of inventories of these goods relative to that
demand. As noted earlier, this demand depends on consumer or household incomes.
Real median household incomes rose sharply from the post-recession low of $52,666 to a high
of $59,039 in 2016. This number surpassed both the 2015 real median household income of
$56,516 and the pre-recession high of $57,909. The increasingly tight labor market, with an
unemployment rate reaching 4.1 percent at the end of 2017, suggests further advances in
median household incomes will occur. Increasing household incomes contribute to GDP
growth, and recessions only occur as household incomes fall. This would suggest that GDP will
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continue to grow through 2018 until household incomes reach a peak and then begin to
decline (Figure 4).
Figure 4: Real Median Household Income in the United States, 1984-20165
1.2 INDEX OF LEADING ECONOMIC INDICATORS
While the rate of growth in real GDP provides the best indicator of the current health of the
general economy, the Conference Board’s Leading Economic Index (LEI) may provide the best
indicator of the near future performance of the general economy.
5 Source: Federal Reserve Bank of St. Louis and the U.S. Census Bureau, https://fred.stlouisfed.org/series/MEHOINUSA672N
$57,909
$52,666
$59,039
$48,000 $49,000 $50,000 $51,000 $52,000 $53,000 $54,000 $55,000 $56,000 $57,000 $58,000 $59,000 $60,000
2015
CPI
-U-R
S Ad
just
ed D
olla
rs
Year
Real Median Household Income in the United States, 1984-2016
Periods of Recession
Estimate Relationship $1,000 RMHI = $1,800 Veterinary Income
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Following the Great Depression of the 1930s, economists were eager to identify an early
warning system that would enable businesses and governments to prepare for an impending
recession. In the mid-1940s several economists identified repeating periods of business
expansion and contraction and called them “business cycles.” The National Bureau of Economic
Research began to research the development of a Business Cycle Indicator (BCI) to predict
turning points in business cycles.
The Conference Board currently provides three BCIs. The Conference Board is a global
independent business membership and research association working in the public interest. The
three indicators leading, coincident and lagging provide a forward, current, and past look at
the performance of the economy, respectively.
The Composite Index of Leading Economic Indicators (LEI) incorporates data from 10 different
economic data time series that have been demonstrated to have peaked or bottomed in
advance of economic expansions or contractions. Each component of the 10 economic series is
weighted based on its relative predictive strength to produce the index of indicators. The
Conference Board produces a monthly value for the LEI and typically reports this on the third
Thursday of every month.
The chart below shows the LEI for the most recent 17-year period, with the gray vertical bars
indicating periods of recession. The most recent recession began in December 2007 and ended
June 2009. The LEI peaked in March 2006 and thus the decline in the LEI began 21 months prior
to the last recession. The LEI continued to advance through December 2017, exceeding the
peak before the last recession. However, the rate of increase in the LEI has declined over the
last two years and may foretell the apex in the business cycle. The continued rise in the LEI
through December of 2017 would indicate that the economy is likely to continue to expand into
2018; however, without some major change in the economy (e.g., government stimulus or
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increased exports) the probability of a recession is beginning to increase with each passing
month beyond the end of 2017 (Figure 5).
Figure 5: The Conference Board's Leading Economic Index
The Federal Reserve Bank has a leading economic indicator that is also used to predict turning
points in the business cycle. The post-recession movement of this indicator appears to be
relatively flat following the post-recession rise. Following previous post-recession periods the
Federal Reserve indicator maintained a value between 1 and 2 for the duration of the economic
expansion (Figure 6).
707580859095
100105110
Inde
x Va
lue,
200
4=10
0
Year
The Conference Board's Leading Economic Index (LEI)
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Figure 6: Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 1982-20176
On closer examination of the Federal Reserve indicator over the post-recession period, a
change in direction of the indicator can be seen to have occurred after reaching a peak in
August of 2014. Since then the indicator has been on a definitive downward path, suggesting
that the economic expansion may have reached or is reaching its peak and the growth rate in
GDP has been continuing to decline (Figure 7).
6 Source: Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/USSLIND
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00
Lead
ing
Inde
x
Year
Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 1982-2017
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Figure 7: Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 2009-20177
To estimate the change in economic factors in the veterinary markets (e.g., veterinary incomes)
we use the forecast of GDP, interest rates and other economic factors from the Congressional
Budget Office (CBO). The CBO is a non-partisan congressional support agency tasked with
producing a long-term (10-year) outlook of economic variables specifically for the use of
determining how changes in federal government policies may affect the federal budget. The
CBO examines current economic policies, factors and trends to develop an annual economic
forecast based on extended baseline projections.
CBO provides its 10-year forecast each January and a mid-term forecast in August of each year
and these forecasts are publically available. We have compared the last five 10-year CBO
forecasts to illustrate the difference between early expansion and current expectations. The
7 Source: Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/USSLIND
0.30
0.50
0.70
0.90
1.10
1.30
1.50
1.70
1.90
2.10
2.30
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Lead
ing
Inde
x
Year
Leading Index for the United States, Percent, Monthly, Seasonally Adjusted, 2009-2017
August 2014
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2013 forecast expected that, under current policies, the economic growth rate would
accelerate to 4.4 percent annual growth by 2016, and then decline by 0.6 percent in 2017 to 3.8
percent. Each year the forecast for 2017 was reduced until the January 2017 forecast expected
the 2017 annual GDP growth rate of 2.3 percent, well below the earlier prediction of 3.8
percent. This suggests that, based on historic responses to economic conditions and with the
economy not performing as expected under current policy, some historic economic
relationships were not sustained over the five years. Further, while the CBO’s 10-year forecast
predicted strong economic growth that moderated to a longer-term growth rate around 2.0
percent, the 2017 forecast indicates a decline in GDP growth rates below 2 percent in the near
term and lower longer-term growth rates. These lower estimates of future GDP growth rates
suggest slower growth in the demand for veterinary services and thus lower veterinary incomes
(Figure 8).
Figure 8: Congressional Budget Office 10-Year Baseline Forecast of U.S. GDP
3.8
3.0
2.52.6
2.3
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Real
GDP
Gro
wth
Rat
es
Year
Congressional Budget Office 10-Year Baseline Forecast of U.S. GDP
2013
2014
2015
2016
2017
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SECTION 2: DEMOGRAPHICS
Dataset Observations (n)
AAEP Membership database 7,432
AAEP - secondary sample 975
AVMA - comparative sample 2,545
Equine - main sample (81 equine respondents from AVMA + 975 AAEP) 1,056
2.1 DEMOGRAPHICS OF RESPONDENTS
Who are the equine practitioners? By comparing the population of AAEP members with the
AVMA sample, differences between the groups may be observed. While the demographics of
Equine are generally similar to the AVMA, some differences exist.
2.1.1 Year of Graduation and Age
The distribution of respondents by year of graduation is shown in Figure 9. Generations of
veterinarians from the 1950s to 2016 are included in this analysis; 59.6 percent of Equine
respondents graduated before 2007, and 40.4 percent after 2007. Considering just AAEP
members, 70.1 percent graduated before 2007, and 29.9 percent after 2007. In contrast, 55.7
percent of AVMA respondents graduated before 2007, and 44.3 percent after 2007.
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Figure 9: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by Graduation Year
The distribution of Equine respondents by age (Figure 10) differs from those of the AVMA.
There are more AAEP members over the age of 51 years (48.1 percent) than Equine
respondents (38.2 percent) or AVMA respondents (26.5 percent). The mean age of all three
groups is approximately 46 years (AAEP members: 48.6; Equine: 45.7; AVMA: 42.7). The
average age of male Equine respondents was 54.9 years, with a median of 58 years. In
comparison, female Equine respondents were an average of 39.2 years of age, with a median of
35 years. Mean years of experience were 29.0 for Equine males, and 12.3 for Equine females.
1966 orprior
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
AAEP (n=7,074) 3.0% 9.8% 18.2% 18.7% 20.4% 13.8% 16.2%Equine (n=1,040) 2.3% 8.9% 16.0% 16.4% 16.2% 17.2% 23.2%AVMA (n=7,074) 3.2% 4.4% 7.6% 14.5% 26.0% 20.3% 24.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
% o
f Res
pond
ents
Distribution of Respondents and AAEP Members by Graduation Year
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Figure 10: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by Age
2.1.2 Veterinary Medical College Attended
The distribution of respondents by veterinary medical college attended is shown in Table 2. A
strong majority of respondents (Equine: 90.4 percent; AVMA: 85.3 percent) graduated from a
U.S. veterinary college and the remaining graduated from an AVMA-accredited school outside
of the United States. A breakdown of the respondent sample by college of study finds that the
largest share of the Equine sample that graduated from veterinary colleges inside of the United
States was University of California-Davis (7.8 percent), followed by Colorado State University
(7.4 percent), with the least number of respondents reporting graduating from Tuskegee
University (0.8 percent). Likewise, the largest share of AVMA respondents that graduated from
veterinary colleges inside of the U.S. was The Ohio State University (5.5 percent), followed by
Texas A&M University (4.2 percent).
0.0%
10.0%
20.0%
30.0%
40.0%
25-30 31-40 41-50 51-60 61 + Missing
% o
f Res
pond
ents
Age
Distribution of Respondents and AAEP Membership by Age
AAEP Membership (n=7,432) Equine (n=1,056) AVMA (n=2,545)
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Table 2: Distribution of Equine and AVMA Respondents by Veterinary College
Veterinary College Equine AVMA
Auburn University 4.4% 3.3% Colorado State University 7.4% 4.1% Cornell University 4.8% 3.5% Iowa State University 3.1% 4.1% Kansas State University 4.6% 4.1% Louisiana State University 1.5% 2.3% Michigan State University 2.3% 4.1% Mississippi State University 1.1% 1.8% North Carolina State University 2.5% 2.6% Oklahoma State University 3.7% 2.0% Oregon State University 1.4% 1.3% Purdue University 2.5% 2.4% Texas A&M University 4.4% 4.2% The Ohio State University 5.4% 5.5% Tufts University 2.6% 3.0% Tuskegee University 0.8% 1.2% University of California-Davis 7.8% 4.0% University of Florida 3.1% 2.0% University of Georgia 3.2% 3.9% University of Illinois 2.8% 3.6% University of Minnesota 3.0% 3.4% University of Missouri-Columbia 3.3% 2.8% University of Pennsylvania 5.3% 4.1% University of Tennessee 1.1% 2.3% University of Wisconsin 2.3% 2.7% Virginia-Maryland College 2.3% 3.2% Washington State University 2.6% 2.6% Western University of Health Sciences 1.1% 1.2% Other 9.6% 14.7% Total 100.0% 100.0%
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2.1.3 Gender
58.4 percent of the Equine respondents were female, and 41.6 percent were male (Figure 11).
AAEP Members are 48.0 percent female and 52.0 percent male. The AVMA respondents show a
distribution of 67.8 percent female to 32.2 percent male.
Figure 11: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by Gender
The distribution of the Equine sample and AAEP members sample by age and gender of
respondents is provided in Figure 12. This shows an inverse relationship between gender and
age in both samples. Although the Equine sample was significantly smaller (1,046) than the
AAEP members database (7,262), the breakdown within the samples was quite similar. Equine
respondents over the age of 60 were predominantly men (81.5 percent). Females were
predominant among Equine respondents younger than 60, representing nearly 65 percent of
practitioners in the 30- to 60-year-old group, and 83 percent of practitioners younger than 30
years. This trend was also evident in the AVMA sample.
52.0% 48.0%41.6%
58.4%
32.2%
67.8%
Male Female
% o
f Res
pond
ents
Gender
Distribution of Respondents and AAEP Members by Gender
AAEP Membership (n=7,262) Equine (n=1,046) AVMA (n=2,390)
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17.0%
34.7%
81.5%83.0%
65.3%
18.5%
Less than 30 years 30 to 60 years Over 60 years% o
f Res
pond
ents
by
Gend
er
Age
Distribution of Equine Respondents by Gender and Age
Male (n=3,615) Female (n=3,433)
15.0%
44.0%
84.3%85.0%
56.0%
15.7%
Less than 30 years 30 to 60 years Over 60 years
% o
f Res
pond
ents
by
Gend
er
Distribution of AAEP Members by Gender and Age
Male (n=434) Female (n=610)
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Figure 12: Distribution of Equine Respondents, AVMA Respondents and AAEP Members by Gender and Age
18.8%27.3%
78.5%81.2%72.7%
21.5%
Less than 30 years 30 to 60 years Over 60 years
% o
f Res
pond
ents
by
Gend
erDistribution of AVMA Respondents by Gender and Age
Male (n=767) Female (n=1,617)
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2.1.4 Type of Employment
A wide range of practice types (Figure 13) was represented among the Equine respondents. The
majority were practicing as exclusively equine veterinarians (64.9 percent), while the majority
of AVMA respondents were in companion animal practice (63.9 percent). Of Equine
respondents who were not in an equine practice (exclusive or predominant), most were in
mixed animal practice (11.6 percent), with the second largest group in the category employed
at a college or university. If AVMA respondents were not in companion animal practice, they
were employed most commonly at a college or university (8.8 percent), followed by a mixed
animal practice (5.5 percent).
Figure 13: Distribution of Equine and AVMA Respondents by Type of Employment
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
% o
f Res
pond
ents
Type of Employment
Distribution of Respondents by Type of Employment
Equine (n=813) AVMA (n=2,275)
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2.1.5 Racial/Ethnic Group
Of the Equine respondents, 94.5 percent were classified as Caucasian (Figure 14) and among
respondents in the AVMA dataset, 89.2 percent Caucasians were represented. Non-Caucasians
represented 5.5 of Equine respondents, compared to 10.8 percent among AVMA respondents.
Figure 14: Distribution of Equine and AVMA Respondents by Racial/Ethnic Group
The ethnicity of Equine respondents is segmented by age in Figure 15. In the Caucasian group,
each generation was represented, with 30- to 39-year-olds having a slightly higher
representation than the other age groups. Among the Hispanic/Latino, Multi-racial/Ethnic
group, the majority of respondents are in their 30s. The African American, American Indian and
Alaskan Native groups had no representation under 50 years of age; and no representation
from the Native Hawaiian/Pacific Islander ethnicity was seen in any age group. Of Equine
89.2%
1.4%
0.9%
3.0%
0.3%
3.4%
1.7%
94.5%
0.2%
0.2%
0.4%
0.0%
2.1%
2.6%
Caucasian
African American
American Indian & Alaska Native
Asian
Native Hawaiian/Pacific Islander
Hispanic/Latino
Multi-racial/Ethnic
% of Respondents
Racia
l/Et
hnic
Grou
p
Distribution of Respondents by Racial/Ethnic Group
Equine (n=1,038) AVMA (n=2,375)
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respondents who identified as Asian, 50 percent were under 30 years old. A greater variety of
ages across racial/ethnic groups was represented in the AVMA sample than in the Equine
sample.
14.6%
50.0%
9.1% 18.5%
30.2%
25.0%
45.5% 33.3%
14.8%22.7%
14.8%17.7%
50.0%
9.1%11.1%
22.7%
100.0%
50.0%25.0% 13.6% 22.2%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Racial/Ethnic Group
Distribution of Equine Respondents by Age and Racial/Ethnic Group (n=970)
Less than 30 30-39 years 40-49 years 50-59 years 60+ years
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Figure 15: Distribution of Equine and AVMA Respondents by Age and Racial/Ethnic Group
2.1.6 Regional Distribution
The United States Postal Service defines nine regions in the United States; the first numbers of
USPS’ area ZIP codes correspond to these nine regions (Figure 16). These regions are not only
different geographically, but were also found to have significant differences in past analysis by
the AVMA with regard to debt, income, unemployment and underemployment.
14.7% 17.2% 16.9% 19.2% 11.4%
36.8% 31.0%50.0%
47.7%
50.0%
48.1%50.0%
17.4% 20.7%
21.5% 50.0% 13.5% 20.5%17.3% 17.2%9.2% 15.4% 11.4%13.8% 13.8%
50.0%
4.6% 3.8% 6.8%
% o
f Res
pond
ents
Racial/Ethnic Group
Distribution of AVMA Respondents by Age and Racial/Ethnic Group (n=2,371)
Less than 30 30-39 years 40-49 years 50-59 years 60 + years
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U.S. Postal Service Regions of the United States
Figure 16: U.S. Postal Service Regions of the United States
The distribution of Equine respondents based on the region where their work was primarily
performed is shown in Figure 17, which reflects representation across all nine regions. Region 9
constituted the highest proportion of respondents, with 14.8 percent, followed by Region 3 at
12 percent. The regionswith the lowest participation were Regions 5 and 6 with 6.4 percent and
6.6 percent, respectively. When compared to the AVMA dataset, similarities as well as
differences emerged. Among AVMA respondents, the top region in which respondents primarily
worked was the same as AAEP: Region 9 at 13.7 percent, and the least number of respondents
in AVMA also came from Region 5 (7.4 percent). However, 3 percent more of the respondents
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from the Equine sample worked in Region 8, 1.9 percent fewer worked in Region 2, and 2.8
percent fewer worked in Region 6 than did AVMA respondents.
Figure 17: Distribution of Equine and AVMA Respondents by U.S. Region of Employment
Region 0, 8.4%
Region 1, 8.9%
Region 2, 10.9%
Region 3, 12.0%
Region 4, 10.7%Region 5, 6.4%Region 6, 6.6%
Region 7, 10.3%
Region 8, 11.2%
Region 9, 14.8%
Distribution of Equine Respondents by U.S. Region of Employment (n=836)
Region 0, 7.7%
Region 1, 8.8%
Region 2, 12.8%
Region 3, 12.3%
Region 4, 9.9%Region 5, 7.4%
Region 6, 9.4%
Region 7, 9.9%
Region 8, 8.1%
Region 9, 13.7%
Distribution of AVMA Respondents by U.S. Region of Employment (n=2,103)
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2.1.7 Living Environment and Work Location
The majority of AVMA respondents indicated they live in a suburban setting, while 51.1 percent
of Equine respondents said they lived in a rural environment (Figure 18).
Figure 18: Distribution of Equine and AVMA Respondents by Living Environment/Community
51.1%
8.8%
40.1%
28.3%
18.7%
53.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Rural Urban Suburban
% o
f Res
pond
ents
Type of Environment/Community
Distribution of Respondents by Living Environment/Community
Equine (n=1,044) AVMA (n=2,391)
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When asked where respondents prefer to live, 46.6 percent of the Equine sample reported they
prefer to stay in a rural setting, while 17.6 percent said they prefer to move from a suburban to
a rural environment (Table 3); 37.6 percent of AVMA respondents indicated that they prefer to
stay in suburbia, 25.1 percent expressed that they prefer to stay in a rural environment, and
12.3 percent responded that they prefer to move from a suburban to a rural environment.
Table 3: Distribution of Equine and AVMA Respondents by Desire to Change Living Environment/Community
Desired Change Equine Sample (n=1,044)
AVMA Sample (n=2,391)
Rural to rural (no change) 46.6% 25.1% Rural to suburb 3.5% 2.5% Rural to urban 1.0% 0.8% Suburb to rural 17.6% 12.3% Suburb to urban 1.6% 3.1% Suburb to suburb (no change) 20.9% 37.6% Urban to urban (no change) 3.8% 11.2% Urban to suburb 1.3% 3.2% Urban to rural 3.7% 4.2% Total 100.0% 100.0%
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2.1.8 Marital Status
The majority of both Equine and AVMA respondents were married at the time of the survey.
The AVMA respondents had a slightly higher percentage of married practitioners (74.6 percent)
compared to the Equine (70.0 percent). The percentage of respondents who reported being
divorced was 6.1 percent among Equine compared to 5.6 percent for AVMA. The AVMA sample
had a smaller percentage of single, never married, respondents than did the Equine sample
(18.1 percent vs. 22.0 percent) (Figure 19).
Figure 19: Distribution of Equine and AVMA Respondents by Marital Status
70.4%
0.7% 0.9%6.1%
22.0%
74.6%
0.7% 1.1% 5.6%
18.1%
Married/partner Separated Widowed Divorced Single, nevermarried
% o
f Res
pond
ents
Marital Status
Distribution of Respondents by Marital Status
Equine (n=1,046) AVMA (n=2,393)
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SECTION 3: THE MARKET FOR VETERINARY EDUCATION
Dataset Observations (n)
AAEP Membership database 7,432
AAEP - secondary sample 975
AVMA - comparative sample 2,545
Equine - main sample (81 equine respondents from AVMA + 975 AAEP) 1,056
3.1 SUPPLY OF VETERINARY EDUCATION
The market for veterinary education is an important component of the veterinary industry as
applicants to the veterinary colleges begin the supply chain for providing veterinary services. In
the veterinary education market, potential veterinary students demand the educational
services that the colleges provide. Thus, the schools are the suppliers, the students are the
consumers (or demanders), and the product being exchanged is an education at different price
levels, or tuition. Students who master an appropriate curriculum in veterinary medicine are
equipped with essential tools to succeed in the veterinary industry which in turn promotes the
health of the profession.
There are 30 AVMA-accredited veterinary colleges in the United States, three AVMA-accredited
Caribbean colleges, 16 AVMA-accredited colleges in other countries, and many other non-
AVMA accredited veterinary colleges around the world.
The 2018 AVMA & AAVMC Report on The Market for Veterinary Education reports that the
number of applicants to colleges of veterinary medicine appears cyclical. After reaching a peak
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in 2013, with 6,769 applicants, applicants dropped to 6,744 in 2014, and dropped again in 2015
to 6,600. Since then, the number of applicants to veterinary colleges has seen an increase, with
6,667 in 2016, 7,071 in 2017, and 7,507 in 2018 (Figure 20). The last cycle peak occurred in
1998, with 6,783 applicants. The number of 2018 applicants was the highest since 1981.
Specific factors that may be responsible for this set of behaviors have not yet been determined,
and the cyclical pattern may need to be better defined.
Figure 20: Association of American Veterinary Medical Colleges (AAVMC) Veterinary School Applicant Figures, AAVMC Internal Data Reports, 1980-2018 8
8 Source: 2018 AVMA & AAVMC Report on The Market for Veterinary Education
7,286
3,922
6,783
4,440
6,769
6,600
7507
-
2,000
4,000
6,000
8,000
10,000
Num
ber o
f Rep
orte
d Ap
plica
nts
Year
AAVMC Veterinary School Applicant FiguresAAVMC Internal Data Reports
1980-2018
19 years 20 years
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3.2 NORTH AMERICAN VETERINARY LICENSING EXAM
Veterinarians who intend to practice veterinary medicine are required to pass the North
American Veterinary Licensing Exam (NAVLE) administered by the International Council for
Veterinary Assessment (ICVA). Figure 21 shows the national NAVLE pass rate.
Figure 21: North American Veterinary Licensing Exam National Pass Rate 9
After a student graduates from a U.S.-accredited veterinary college and passes the NAVLE they
are then eligible to obtain a state license to practice veterinary medicine. Among the Equine
respondents, 92.0 percent (AVMA: 93.0 percent) reported having a license to practice. 67.2
percent of Equine respondents with a license to practice veterinary medicine graduated within
the past 20 years and 32.8 percent graduated more than 20 years ago. In contrast, 72.1 percent
of AVMA respondents with a license to practice graduated within the past 20 years, and 27.9
percent graduated more than 20 years ago.
9 Source: NAVLE http://www.vetmed.vt.edu/academics/dvm/navle-pass-rates.asp
96% 96%95%
96%95% 95%
2011/12 2012/13 2013/14 2014/15 2015/16 2016/17
Pass
Rat
e (%
)
Year
North American Veterinary Licensing Exam National Pass Rate
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3.3 SUPPLY OF SEATS FROM AVMA-ACCREDITED SCHOOLS
The expected supply for seats at AVMA-accredited schools is approximately 3,300 seats per
year at the 30 U.S. colleges, 490 at the three Caribbean colleges, and more than 700 at the 16
U.S.-accredited foreign colleges. There is no information to suggest that the supply of seats at
these 49 veterinary colleges will increase; therefore a constant number of seats beyond 2019
are forecasted (Figure 22).
Figure 22: U.S. Veterinary Graduates, All Sources, 1980-202510
10 Source: 2018 AVMA & AAVMC Report on The Market for Veterinary Education
0
1000
2000
3000
4000
5000
Num
ber o
f Gra
duat
es
Year
U.S. Veterinary Graduates, All Sources, 1980-2025
U.S. Graduates Caribbean GraduatesForeign Graduates Total Graduates
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3.4 THE COST OF VETERINARY EDUCATION
The average annual tuition and fees for the 30 veterinary medical colleges in the United States
have more than doubled, from $10,549 in 1999 to $27,096 in 2015 (“2016 Report on Veterinary
Markets,” 2016). The tuition/fees for completing the DVM/VMD degree at the U.S. veterinary
medical colleges and the total cost (tuition and fees, plus housing, transportation, school
supplies, and food) are presented in Table 4 for 2017. Among the most costly colleges for the
four-year program are Tuskegee Univeristy ($337,007), University of Pennsylvania ($300,588),
and Western University of Health Sciences ($288,868). The least expensive schools are Purdue
University ($138,637), followed by University of Georgia ($146,586), and Oklahoma State
University ($152,370). Of the Equine respondents (refer back to Table 2), 7.8 percent graduated
from University of California-Davis, which falls near the top of tuition rank, with tuition and fees
at $128,174 and total costs of $239,770.
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Table 4: Tuition/Fees and Total Cost of a DVM Degree by Veterinary School 11
Veterinary School Total Cost Tuition & Fees
Tuskegee University $337,007 $155,523 University of Pennsylvania $300,588 $170,788 Western University of Health Sciences $288,868 $196,770 Tufts University $258,129 $173,177 University of California-Davis $239,770 $128,174 The Ohio State University $226,730 $135,866 University of Minnesota $213,088 $145,456 Michigan State University $212,977 $123,377 Cornell University $201,007 $129,007 University of Florida $200,741 $115,148 Louisiana State University $195,995 $98,027 University of Illinois $195,856 $119,544 University of Tennessee $188,400 $105,040 Texas A&M University $182,910 $90,494 Colorado State University $180,851 $112,667 University of Missouri-Columbia $176,669 $92,677 Kansas State University $173,368 $100,268 Virginia-Maryland College $172,446 $92,602 North Carolina State University $171,542 $71,066 Auburn University $169,933 $82,369 University of Wisconsin $163,324 $81,776 Oregon State University $162,735 $90,663 Washington State University $161,904 $89,506 Mississippi State University $153,774 $81,358 Iowa State University $152,978 $98,750 Oklahoma State University $152,370 $77,170 University of Georgia $146,586 $74,106 Purdue University $138,637 $79,267
11 Source: 2018 AVMA & AAVMC Report on the Market for Veterinary Education
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3.5 DISTRIBUTION OF NEW VETERINARIANS
While they are in veterinary school, all students begin a common curriculum and learn the same
fundamentals of veterinary medicine. In their third and fourth years, veterinary students gain
similar hands-on experience, though some schools allow limited tracking for students
interested in a particular species or practice type. Because veterinary licenses are not species-
specific, students must be competent in all species in order to successfully pass the NAVLE.
Sometimes it is not until they leave veterinary school and decide to participate in an internship
and then possibly a residency that new veterinarians gain specialized experience in the
species or practice area they are interested in focusing on exclusively. Alternatively, some new
DVMs decide to begin practicing without further education. Because there is no hard measure
to identify which students enter veterinary college with the intention of practicing equine
medicine, it is difficult to estimate the demand among students to enter the field. Data from
the American Association of Veterinary Medical College‘s poll of veterinary school applicants
suggest, however, that 57.4 percent of applicants develop an interest in veterinary medicine at
the age of 10 or younger, and that 37.5 percent desire to have an equine practice career path
(Table 5; Figure 23). It is unclear how many of these equine-oriented applicants are ultimately
successful in gaining a seat at a veterinary medical college.
Table 5: Distribution of Veterinary School Applicants’ Age When They Develop an Interest in Veterinary Medicine 12
Age Percent
10 or younger 57.4% 11-16 20.4% 17-25 18.1% Over 25 4.1%
12 Source: American Association of Veterinary Medical College’s Poll of Veterinary School Applicants, 2016
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Figure 23: Distribution of Veterinary School Applicants and Their Desired Career Path13
What is known is how many recent graduates of veterinary medical colleges have entered the
equine profession in the past 16 years. Figure 24 presents the number of veterinary graduates
reporting their first full-time employment in equine practice after graduation. Figure 25
compares first full-time employment in equine practice with other full-time private practice
types.
13 Source: American Association of Veterinary Medical College’s Poll of Veterinary School Applicants, 2016
65.9%
41.0%37.5%
31.6%28.4%
26.6%23.9%
22.1%12.2%
5.3%0.1%
Private PracticeProduction/Large Animal
EquineResearch
Shelter MedicinePublic Health
TrainingFederal Government
Corporate Veterinary MedicinePublic Policy
Other Career PathPercentage of Interested Applicants
Care
er P
ath
Distribution of Veterinary School Applicants and Their Desired Career Path
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Figure 24: Distribution of New Veterinarians in Equine Private Practice 14
Figure 25: Distribution of New Veterinarians in Private Practice 15
14 Source: 2018 AVMA & AAVMC Report on The Market for Veterinary Education 15 Source: 2018 AVMA & AAVMC Report on The Market for Veterinary Education
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017Equine practice 3.5% 4.0% 5.7% 3.6% 4.7% 4.7% 4.1% 3.3% 4.0% 2.0% 2.5% 1.6% 2.1% 1.4% 1.2% 1.3% 1.1%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
% o
f Gra
duat
ing
Seni
ors
Distribution of New Veterinarians in Equine Private Practice
Equine practice
0%5%
10%15%20%25%30%35%40%45%
% o
f Res
pond
ents
Year
Distribution of New Veterinarians in Private Practice
Food animal practice(exclusive)
Food animal practice(predominant)
Mixed practice
Companion animal(predominant)
Companion animal(exclusive)
Equine practice
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3.6 VETERINARY COLLEGE OUTCOMES OF VETERINARIANS IN THE EQUINE PROFESSION
Veterinary college equips students with the basic skills needed to be a well-rounded
veterinarian capable of treating multiple species. Most veterinary students gain additional
veterinary experience participating in externships, short experiential learning opportunities that
give students practical experiences in veterinary settings outside of the veterinary college.
Many DVM graduates continue their training after graduation by participating in a year-long
internship to gain more species-specific training. A smaller number then pursue participation in
a residency program to gain skills in a specialty and become board certified. The AVMA has
been studying the economic value of internship for several years to determine how this
advanced training impacts veterinarians’ careers. Externships, internships and residencies in the
equine veterinary field are explored in this section.
3.6.1 Externship Participation
Externships provide a way for veterinary students to gain firsthand insight into an area of
practice in which they have interest. The majority of externships are undertaken in a student’s
fourth year at veterinary school, but many students also do externships during a summer recess
during their first three years. While not all colleges require externships before graduation,
many do. Externships prepare veterinary students for the reality of employment in private or
public practice after graduation. Several questions were asked in the 2016 AVMA-AAEP Survey
of Equine Practitioners that were not included in the 2016 AVMA Census of Veterinarians and
are summarized in the following descriptive statistics.
More than 81 percent of AAEP respondents participated in an externship in veterinary school,
while almost 19 percent did not (Figure 26).
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Figure 26: Distribution of AAEP Respondents by Externship Participation
In addition, 50 percent of 970 AAEP respondents participated in one to three externships, 33.4
percent participated in four to six, 12.4 percent experienced six to ten externships, and 4.2
percent more than 10. 55.4 percent of AAEP respondents stated they applied for an internship
at a practice where they attended an externship, while 44.6 percent of them did not apply at an
externship practice (n=790).
3.6.2 Internship Participation
An internship is a one-year clinical training program that provides practical experience and
additional training in clinical sciences. Internships are designed to sharpen the broad clinical
skill set required in equine practice, and teach the intern how to successfully engage with
various sectors of the equine industry. Interns often work under direct supervision, participate
in practice rounds and seminars and deliver formal presentations. An internship prepares a
veterinarian for employment in a practice or for advanced specialty training. In their best form,
internship programs are quality educational programs that provide benefit to the practice and
18.8%
81.2%
Distribution of AAEP Respondents by Externship Participation (n=975)
Did not participate Did participate
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to the new graduate. The intern earns a smaller salary than a practice associate, but in return
receives substantial experiential benefit and mentoring.
There are many reasons why a veterinarian might take on an internship. A veterinarian might
be unable to find an associate position due to a tight job market, or the available associate
positions might require an internship experience as a condition of employment. Veterinary
graduates may have the perception that an internship experience will equate to a higher
starting salary at their first associate position, they might plan to pursue a residency in a
selected board specialty, or believe that it is prudent to gain more confidence and experience
as an equine-specific practitioner before entering private practice.
In the following descriptive statistics regarding internships, the Equine sample is used, as the
questions were consistent between the 2016 AVMA-AAEP Survey of Equine Practitioners and
the 2016 AVMA Census of Veterinarians.
Twenty-eight percent of Equine respondents applied for just one internship, 55.4 percent
applied to between two to four internship positions, and 16.6 percent applied to five or more.
Among Equine respondents, 5.7 percent were currently participating in an internship, 46.6
percent had not participated in an internship, and 47.7 percent had participated in an
internship (Figure 27). In contrast, the AVMA survey sample showed 74 percent of general
veterinary practitioners had not participated in an internship and 26 percent had participated in
an internship.
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Figure 27: Distribution of Equine and AVMA Respondents by Internship Participation
Note: The 2016 AVMA-AAEP Survey of Equine Practitioners asks if respondents are currently in
an internship, while the 2016 Census of Veterinarians asks only if the respondent has or has not
participated in an internship.
Figure 28 shows the percentage of males and females who participated in the past or were
currently participating in an internship. 64.3 percent of female Equine respondents participated
in an internship compared to 37.9 percent of males. The AVMA sample reported 23.5 percent
of males had participated in an internship, and 27.6 percent of females participated in one.
5.7%
46.6% 47.7%
74.0%
26.0%
Currently participating Have not participated Participated in the past
% o
f Res
pond
ents
Participation Status
Distribution of Respondents by Internship Participation
Equine (n=1,055) AVMA (n=2,532)
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Figure 28: Distribution of Equine and AVMA Respondents Internship Participation by Gender
Figure 29 displays the distribution of respondents by the year they completed their internship,
with more than half of respondents in both samples completing an internship between 2007-
2017.
Most internships were undertaken in the 12 months following completion of veterinary school.
89.5 percent of Equine respondents who participated in an internship did so immediately
following graduation (AVMA: 85.6 percent), 4.6 percent held an intership two to three years
after graduation (AVMA: 10.2 percent), and the remaining 5.9 percent of respondents who
completed an internship did so four or more years after graduation from veterinary college
(AVMA: 4.3 percent).
62.1%
35.7%
76.5% 72.4%
37.9%
64.3%
23.5% 27.6%
Equine - Male(n=435)
Equine - Female(n=611)
AVMA-Male(n=767)
AVMA-Female(n=1,617)
% o
f Res
pond
ents
Internship Participation
Distrbution of Respondent Internship Participation by Gender
Have not participated in an internship Participated in an internship
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Figure 29: Distribution of Equine and AVMA Respondents by Year of Completed Internship
A veterinarian can apply for equine internships through three main venues: the formal match
program, the AAEP Avenues program, and a non-formal match. The formal match program
consists of academic internships delivered at academic institutions. The AAEP Avenues program
provides an online listing of mostly private practice equine internships. AAEP also provides a
gathering for applicants to meet practice representatives at the summer AAEP Summer Focus
Conference & Labs and the annual AAEP Convention, and reviews of internships authored by
former interns. The non-formal match simply encompasses available internship opportunities
that are posted in a classified ad or on a social media account, spread by word of mouth, or
communicated by other means.
Of the Equine respondents, 39.0 percent applied for an internship through AAEP Avenues, 29.3
percent through a non-formal match, and 19 percent through the formal match system. 12.7
percent of respondents utilized both the formal and non-formal match systems. By contrast,
61.7 percent of AVMA respondents applied for an internship through the formal match system,
followed by 30.8 percent in a non-formal match, and 7.5 percent through both (Figure 30).
2012-2016
2007-2011
1997-2006
1987-1996
1977-1986
1967-1976
1966or
priorAVMA (n=641) 29.5%27.3%22.9%12.6%4.2%2.3%1.1%Equine (n=562) 40.6%21.4%14.6%11.2%7.3%4.1%0.9%
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%
% o
f Res
pond
ents
Distribution of Respondents by Year of Completed Internship
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Figure 30: Distribution of Equine and AVMA Respondents by Internship Program
Note: The 2016 AVMA Census of Veterinarians did not have the option of AAEP Avenues for
respondents to select.
In the Equine sample, 47.2 percent of female respondents applied through AAEP Avenues and
13.8 percent through the formal match system, while 37.7 percent of male respondents went
through a non-formal match and 31.5 percent the formal match system, with only 19.8 percent
utilizing AAEP Avenues. In contrast, 53.1 percent of AVMA males and 65.5 percent of AVMA
females applied though the formal match system (Figure 31).
39.0%
19.0%29.3%
12.7%
61.7%
30.8%
7.5%
AAEP Avenues Formal MatchSystem (academic
internships)
Non-Formal MatchSystem
Both through theFormal and Non-
Formal MatchSystem
% o
f Res
pond
ents
Internship Program
Distribution of Respondents by Internship Program
Equine (n=559) AVMA (n=655)
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Figure 31: Distribution of Equine and AVMA Respondents by Internship Program and Gender
Note: The 2016 AVMA Census of Veterinarians did not have the option of AAEP Avenues for
respondents to select.
When looking at the type of internship program by year of graduation, 58.4 percent of Equine
respondents who graduated in the past five years utilized AAEP Avenues; 28.1 percent relied on
a non-formal match (Table 6). The Equine respondents showed a declining trend in use of the
formal system for internship selection, with recent graduate use having declined from more
than 50 percent to 2.7 percent. In contrast, the AVMA sample has shown only a small decline in
formal system participation from slightly less than 70 percent for those who graduated 20-30
years ago to slightly more than 60 percent for recent graduates. The AVMA sample shows
respondents who applied through the formal or non-formal system, or both. The AAEP Avenues
19.8%
47.2%31.5%
13.8%
53.1%65.5%
37.7% 25.8% 38.4%27.1%
11.1% 13.3% 8.5% 7.4%
Equine - Male(n=162)
Equine - Female(n=392)
AVMA - Male(n=177)
AVMA - Female(n=446)
% o
f Res
pond
ents
Internship Program
Distribution of Respondents by Internship Program and Gender
Both through the Formal and Non-Formal Match system
Non-Formal Match system
Formal Match system (academic internships)
AAEP Avenues
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program has been in place since 1997. No such program for private practice internships exists in
the AVMA.
Table 6: Distribution of Equine and AVMA Respondents by Internship Program and Graduation Year
Equine 1966 or prior
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
AAEP Avenues 0.0% 3.6% 0.0% 1.5% 35.4% 54.2% 58.4% Formal Match system (academic internships)
50.0% 53.6% 50.0% 46.3% 17.7% 11.5% 2.7%
Non-Formal Match system 33.3% 32.1% 31.6% 38.8% 28.1% 25.2% 28.1% Both through the Formal and Non-Formal Match system
16.7% 10.7% 18.4% 13.4% 18.8% 9.2% 10.8%
AVMA 1966 or prior
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Formal Match system (academic internships)
0.0% 17.6% 52.0% 69.5% 64.9% 64.7% 61.5%
Non-Formal Match system 100.0% 70.6% 36.0% 26.8% 26.4% 30.6% 28.6% Both through the Formal and Non-Formal Match system
0.0% 11.8% 12.0% 3.7% 8.6% 4.6% 9.9%
To understand why so many equine-oriented new graduates decide to participate in an
internship after veterinary school, Equine respondents were queried as to their reasons for
undertaking an internship and selected all the reasons that applied to them (Table 7).
Among male equine respondents who graduated from 2012 to 2016, 65.4 percent selected “to
practice better quality veterinary medicine,” and 53.8 percent selected “plan/planned to apply
for a residency” and/or selected “to get more training before entering veterinary practice.” An
increase was seen in male respondents who graduated between the 1960s and 2016 (including
current interns) and selected the first reason – “practice better quality veterinary medicine” –
and “plan/planned to apply for a residency.” The answer “to get more training before entering
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veterinary practice” showed a decrease from the number of male respondents who graduated
between the 1960s and 2016 (including current interns).
Among female equine respondents who graduated from 2012 to 2016, 72 percent selected “to
get more training before entering veterinary practice,” 66.5 percent “to practice better quality
veterinary medicine,” and 48.8 percent “to be more competitive in applying for available jobs.”
All three reasons showed an increase in the percentage of female respondents across
graduation years from the 1960’s to 2016 (including current interns) who selected those
reasons.
Among male AVMA respondents who graduated from 2012 to 2016, 60.7 percent selected
“plan/planned to apply for a residency,” 50 percent selected “to practice better quality
veterinary medicine,” and 17.9 percent wanted “to get more training before entering
veterinary practice.” The first reason showed an increased response within graduation years
from the 1960s to 2016, the second reason showed a slight decrease in responses within these
graduation years, and the third reason showed an increase in responses within this same
timeframe. Among female AVMA respondents who graduated from 2012 to 2016, 64.8 percent
selected “to practice better quality veterinary medicine,” 40.0 percent selected “plan/planned
to apply for a residency,” and 38.4 percent wanted “to get more training before entering
veterinary practice.” Unlike the male AVMA respondents, all top three reasons of the females
showed an increasing trend among responses within the 1960s to 2016 graduation years.
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Table 7: Distribution of Equine and AVMA Respondents’ Reasons for Undertaking an Internship by Gender and Graduation Year
Equine - Male 1966 or prior (n=4)
1967-1976
(n=29)
1977-1986
(n=27)
1987-1996
(n=34)
1997-2006
(n=29)
2007-2011
(n=25)
2012-2016
(n=26)
Current Intern (n=12)
To practice better quality veterinary medicine
50.0% 34.5% 37.0% 50.0% 48.3% 60.0% 65.4% 58.3%
To get more training before entering veterinary practice
50.0% 55.2% 48.1% 41.2% 31.0% 56.0% 53.8% 41.7%
I plan/planned to apply for residency
0.0% 24.1% 22.2% 38.2% 51.7% 36.0% 53.8% 58.3%
I feel/felt that I wil l earn more money in veterinary medicine by doing an internship
0.0% 0.0% 3.7% 2.9% 10.3% 12.0% 26.9% 25.0%
Was not able to obtain a position in other aspects of veterinary medicine
0.0% 3.4% 0.0% 0.0% 0.0% 8.0% 0.0% 0.0%
To be more competitive in applying for available jobs
0.0% 0.0% 3.7% 5.9% 13.8% 24.0% 34.6% 41.7%
Other--Please specify 0.0% 3.4% 3.7% 0.0% 0.0% 4.0% 0.0% 8.3%
Equine - Female 1977-1986
(n=13)
1987-1996
(n=41)
1997-2006
(n=73)
2007-2011
(n=107)
2012-2016
(n=164)
Current Intern (n=48)
To practice better quality veterinary medicine
69.2% 58.5% 60.3% 67.3% 66.5% 68.8%
To get more training before entering veterinary practice
76.9% 48.8% 67.1% 74.8% 72.0% 62.5%
I plan/planned to apply for residency 38.5% 48.8% 47.9% 38.3% 30.5% 39.6% I feel/felt that I wil l earn more money in veterinary medicine by doing an internship
0.0% 0.0% 9.6% 11.2% 6.7% 2.1%
Was not able to obtain a position in other aspects of veterinary medicine
0.0% 0.0% 0.0% 5.6% 2.4% 2.1%
To be more competitive in applying for available jobs
0.0% 14.6% 23.3% 41.1% 48.8% 45.8%
Other--Please specify 0.0% 0.0% 0.0% 0.9% 1.2% 2.1%
Note: Graduation years 1967-1976 were omitted because the numer of observations did not
permit estimation.
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AVMA - Male 1966 or prior
(n=10)
1967-1976
(n=12)
1977-1986
(n=16)
1987-1996
(n=27)
1997-2006
(n=51)
2007-2011
(n=31)
2012-2016
(n=28) To practice better quality veterinary medicine
50.0% 41.7% 50.0% 40.7% 54.9% 35.5% 50.0%
To get more training before entering veterinary practice
20.0% 8.3% 25.0% 18.5% 27.5% 16.1% 17.9%
I plan/planned to apply for residency 30.0% 16.7% 31.3% 51.9% 49.0% 51.6% 60.7% I feel/felt that I wil l earn more money in veterinary medicine by doing an internship
0.0% 0.0% 75.0% 3.7% 9.8% 6.5% 14.3%
Was not able to obtain a position in other aspects of veterinary medicine
10.0% 0.0% 0.0% 0.0% 0.0% 3.2% 0.0%
To be more competitive in applying for available jobs
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Other--Please specify 30.0% 33.3% 0.0% 11.1% 3.9% 12.9% 3.6%
Note: The 2016 AVMA Census of Veterinarians did not have the option of selecting “To be more
competitive in applying for available jobs.”
AVMA - Female 1967-1976 (n=5)
1977-1986
(n=10)
1987-1996
(n=48)
1997-2006
(n=116)
2007-2011
(n=137)
2012-2016
(n=125) To practice better quality veterinary medicine
0.0% 50.0% 50.0% 48.3% 55.5% 64.8%
To get more training before entering veterinary practice
40.0% 10.0% 25.0% 30.2% 43.8% 38.4%
I plan/planned to apply for residency 20.0% 40.0% 58.3% 56.9% 48.9% 40.8% I feel/felt that I wil l earn more money in veterinary medicine by doing an internship
0.0% 0.0% 6.3% 8.6% 16.8% 10.4%
Was not able to obtain a position in other aspects of veterinary medicine
0.0% 0.0% 0.0% 0.0% 2.9% 0.8%
To be more competitive in applying for available jobs
0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Other--Please specify 60.0% 30.0% 12.5% 6.0% 5.1% 8.8%
Note: The 2016 AVMA Census of Veterinarians did not have the option of selecting “To be more
competitive in applying for available jobs.”
AAEP respondents were asked to indicate internship responsibilities and the percent of
responses for each is provided in Table 8. The majority (82.1 percent) of AAEP respondents had
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primary on-call emergency duty with mentoring available, contrasting with 16.9 percent who
had no mentoring available when on emergency duty. Most internships (70.1 percent) required
the intern to be responsible for primary client communication for cases. 68.2 percent of
practices offered case rounds for their interns. Most (60.9 percent) internships also included
overnight treatment duty on a regular basis. About half (52.7 percent) of internships included a
Journal Club. About one-third (31.6 percent) included hands-on procedural rounds designed
specifically for learning a skill or technique, and less than one-quarter (23.6 percent) offered
radiology rounds.
Table 8: Distribution of Elements Included in Equine Internships, Selecting All That Applied to AAEP Respondents
Internship Responsibilities Freq. Percent
Primary on call emergency duty with mentoring available 418 82.1% Primary Client communication responsibility for cases 357 70.1% Clinical case rounds 347 68.2% Overnight treatment duty on a regular basis 310 60.9% Independent case management without oversight 274 53.8% Journal club 268 52.7% Periodic performance evaluations 173 34.0% Procedural rounds with teaching horses specifically for learning a skill or technique
161 31.6%
Radiology rounds 120 23.6% Primary on call emergency duty without mentoring available 86 16.9%
Internships provide a salary or stipend, but this remuneration is rarely equivalent to that of a
full-time practicing veterinarian who is in the first year of practice. Table 9 displays the mean
internship salary for males and females among Equine respondents and AVMA respondents.
Female Equine respondents on average reported an annual internship stipend of $24,661 vs.
$19,918 for males; female AVMA respondents reported an average internship salary of
$25,726, while males reported $22,766. Current Equine interns have a slightly higher average
salary than the Equine and AVMA samples.
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Table 9: Distribution of Equine and AVMA Respondents’ Internship Stipends/Salaries by Gender
Equine Gender Obs. Mean Std. Dev. Min. Max.
Male 162 $19,918 $9,188 $0 $60,000 Female 389 $24,661 $5,663 $0 $40,000
AVMA Gender Obs. Mean Std. Dev. Min. Max.
Male 153 $22,767 $8,292 $3,600 $67,000 Female 411 $25,726 $7,005 $2,400 $75,000
Current Equine Intern Gender
Obs. Mean Std. Dev. Min. Max.
Male 12 $25,850 $3,529 $19,200 $30,000 Female 48 $26,917 $4,334 $12,500 $40,000
Salaries may differ over time. Table 10 shows the mean internship stipends/salaries of
respondents by graduation year. Both Equine and AVMA respondents reported larger average
salaries and stipends in the past 20 years. It should be noted that no adjustment for inflation
has been made in this report.
Table 10: Distribution of Equine and AVMA Respondents’ Internship Stipends/Salaries by Graduation Year
Equine Graduation Year Obs. Mean Std. Dev. Min. Max.
2012-2016 185 $26,915 $3,677 $12,500 $40,000 2007-2011 130 $27,165 $5,567 $13,000 $60,000 1997-2006 95 $22,679 $5,288 $0 $45,000 1987-1996 66 $18,180 $5,209 $12,000 $48,000 1977-1986 36 $12,706 $5,410 $0 $25,000 1967-1976 29 $10,626 $5,689 $50 $25,000 1966 or prior 5 $14,280 $14,380 $2,400 $30,000
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AVMA Graduation Year Obs. Mean Std. Dev. Min. Max.
2012-2016 158 $29,174 $4,607 $18,000 $45,000 2007-2011 168 $27,222 $5,212 $10,000 $50,000 1997-2006 158 $23,657 $7,168 $2,400 $75,000 1987-1996 61 $17,844 $6,186 $5,000 $41,000 1977-1986 19 $15,551 $4,431 $9,000 $28,000 1967-1976 11 $12,227 $3,545 $8,000 $19,000 1966 or prior 6 $7,900 $4,096 $3,600 $15,000
During an internship, interns must fund their housing if it is not provided to them during their
internship program. Thus, AAEP respondents who participated in an internship were asked
about their housing situation during their internship. Compensation packages for 66 percent of
the respondents did not include free housing (Figure 32).
Figure 32: Distribution of AAEP Respondents by Internship Compensation Package Which Includes/Included Free Housing
66.0%
34.0%
Distribution of AAEP Respondents by Internship Compensation Package Which Includes/Included Free
Housing
Does not include free housing Includes free housing
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AAEP respondents who reported free housing in their compensation package versus those who
did not generally reported lower internship salaries (Table 11).
Table 11: Distribution of AAEP Respondents’ Internship Housing Status with Respect to Intern Salaries and Graduation Year
Graduation Year Obs. Housing No Housing
Less than 5 years ago $0-$10,000 0 - - $11,000-$20,000 3 66.7% 33.3% $21,000-$30,000 146 46.6% 53.4% $31,000-$40,000 19 36.8% 63.2% $41,000 or more 0 - -
5-10 years ago $0-$10,000 0 - - $11,000-$20,000 11 54.5% 45.5% $21,000-$30,000 84 38.1% 61.9% $31,000-$40,000 17 35.3% 64.7% $41,000 or more 2 50.0% 50.0%
10-20 years ago $0-$10,000 1 100.0% 0.0% $11,000-$20,000 30 33.3% 66.7% $21,000-$30,000 51 33.3% 66.7% $31,000-$40,000 3 33.3% 66.7% $41,000 or more 0 - -
20 + years ago $0-$10,000 26 34.6% 65.4% $11,000-$20,000 88 10.2% 89.8% $21,000-$30,000 14 7.1% 92.9% $31,000-$40,000 0 - - $40,000 or more 1 0.0% 100.0%
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Table 12 shows the reported average monthly value of rental housing by graduation year
among those respondents who had free housing included in their compensation package. The
average monthly housing value for AAEP intern respondents from 2012 through 2016 was
$741.89 per month, compared to less than $500 for respondents who graduated more than 30
years ago.
Table 12: Means of Equine Monthly Value of Housing per Month
Graduation Year Obs. Mean Std. Dev. Min. Max.
2012-2016 74 $742 $341 $300 $2,500 2007-2011 44 $738 $312 $200 $1,800 1997-2006 29 $681 $331 $0 $2,000 1987-1996 9 $544 $231 $250 $1,000 1977-1986 3 $500 $0 $500 $500 1967-1976 4 $256 $216 $0 $500
Note: Graduation year 1966 or prior was omitted because the number of observations did not
permit estimation.
Interns are often provided with a benefits package. Specific benefit questions were asked of the
AAEP respondents. In addition to indicating benefits by gender, Table 13 lists the types of
benefits and the percentage of respondents who had certain benefits during their internship. If
respondents had completed more than one internship, they were asked to respond only about
their first internship. Respondents selected all benefits that they received during their
internship. The majority of respondents had health insurance (63.1 percent), AVMA’s
professional liability insurance (PLIT) (62.5 percent), and continuing education expenses (60.9
percent). More than half of the interns were paid or reimbursed for license fees (57.2 percent)
and association dues (56 percent), and received paid continuing education leave (50.9 percent).
39.3 percent of interns received paid vacation days and 29.9 percent were given paid personal
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or sick days. 9.6 percent were offered a retirement plan. 4.7 percent of interns received none of
the benefits listed.
PLIT, health insurance, and continuing education expenses were the top benefits provided by
an employer to both females and males. Males were less likely to receive the listed benefits
than females in almost all categories. 11.6 percent of males received no benefits in their
internships compared to 1.9 percent of females. These differences may be due to male intern
Equine respondents having a mean of 23 years of experience versus females’ having a mean of
10 years of experience in this sample.
Table 13: Percentage of Benefits Provided by Equine First, or Only, Internship
Benefit Equine (n=509)
Female (n=361)
Male (n=146)
Health insurance 63.1% 64.8% 58.2% PLIT insurance (Professional liability/malpractice) 62.5% 67.6% 50.0% Continuing education expenses 60.9% 65.1% 50.7% License(s) fees 57.2% 63.7% 41.1% Association dues (AVMA, AAEP, etc.) 56.0% 63.2% 39.0% Continuing education leave (paid days off to attend) 50.9% 55.4% 39.7% Practice owned cell phone 42.0% 47.9% 28.1% Paid vacation 39.3% 41.8% 33.6% Discounted veterinary care for personal animals 37.9% 43.2% 26.0% Paid personal or sick days 29.9% 32.1% 24.0% Paid holidays 24.6% 22.7% 29.5% Disability insurance 21.4% 19.9% 25.3% Personal use of vehicle 16.3% 16.9% 15.1% Retirement plan 9.6% 8.3% 12.3% None of the above 4.7% 1.9% 11.6% Other 3.5% 3.0% 4.8%
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Benefits received by interns have changed over time (Table 14). In general, the percent of
interns receiving all types of benefits except for paid holidays has increased over time.
Table 14: Percentage of Benefits Provided by Equine First, or Only, Internship by Graduation Year
Benefit 1966 or prior (n=5)
1967-1976
(n=30)
1977-1986
(n=37)
1987-1996
(n=62)
1997-2006
(n=86)
2007-2011
(n=114)
2012- 2016
(n=168) Health insurance 80.0% 43.3% 40.5% 74.2% 67.4% 61.4% 65.5% PLIT insurance (Professional l iability/malpractice)
20.0% 16.7% 32.4% 54.8% 66.3% 77.2% 71.4%
Continuing education expenses 0.0% 26.7% 32.4% 46.8% 67.4% 64.0% 75.6% License(s) fees 0.0% 16.7% 8.1% 43.5% 57.0% 66.7% 75.0% Association dues (AVMA, AAEP, etc.)
0.0% 13.3% 13.5% 37.1% 51.2% 68.4% 75.0%
Continuing education leave (paid days off to attend)
20.0% 20.0% 21.6% 46.8% 52.3% 58.8% 59.5%
Practice owned cell phone 20.0% 6.7% 0.0% 17.7% 46.5% 62.3% 50.6% Paid vacation 60.0% 36.7% 24.3% 38.7% 39.5% 34.2% 45.8% Discounted veterinary care for personal animals
20.0% 20.0% 8.1% 17.7% 26.7% 40.4% 59.5%
Paid personal or sick days 60.0% 20.0% 24.3% 32.3% 29.1% 26.3% 33.9% Paid holidays 20.0% 33.3% 24.3% 32.3% 26.7% 24.6% 19.0% Disability insurance 40.0% 30.0% 24.3% 25.8% 18.6% 19.3% 20.8% Personal use of vehicle 0.0% 10.0% 18.9% 12.9% 11.6% 15.8% 22.0% Retirement plan 60.0% 13.3% 5.4% 12.9% 9.3% 14.0% 4.2% Other 0.0% 6.7% 8.1% 3.2% 3.5% 1.8% 3.0% None of the above 20.0% 20.0% 18.9% 6.5% 3.5% 0.0% 1.2%
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AAEP respondents were asked how many vacation days they were allotted during their
internship. Over 50 percent of respondents who graduated since 1997 reported 10 or more
vacation days. Respondents who graduated prior to 1997 reported a varied number of vacation
days, all under 50 percent, with the exception of three respondents (60 percent), who
graduated in 1966 or before; those respondents reported one to five vacation days (Figure 33).
Figure 33: Distribution of AAEP Respondents’ Vacation Days Allotted for Internships by Graduation Year
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
% o
f Res
pond
ents
Graduation Year
Distribution of AAEP Respondents' Vacation Days Allotted for Internships by Graduation Year
0 days 1-5 days 6-10 days 10 or more days
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Figure 34 presents first post-internship salaries of respondents by year of graduation. On
average, those who graduated after 1997 reported higher first post-internship salaries than
those who graduated prior. Of veterinarians who graduated from 2012-2016, AVMA
respondents reported an average starting salary of $68,049, while Equine respondents reported
an average starting salary of $52,410.
Figure 34: Distribution of Equine and AVMA Respondents’ First Post-Internship Salary by Year of Graduation
$52,410
$68,049
$- $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 $80,000
Sala
ry (
$)
Graduation Year
Distribution of Respondents' First Post-Internship Salary by Year of Graduation
Equine AVMA
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AVMA respondents reported higher starting salaries than Equine respondents on average, with
the exception of male Equine respondents who graduated in the time period 2012-2016, and
who reported an average starting salary of $61,687 compared to AVMA males who reported
$61,810 (Table 15). In contrast, female Equine respondents who graduated from 2012-2016
reported an average starting salary of $51,109 compared to AVMA females, who reported
$70,452.
Table 15: Mean Distribution of Equine and AVMA Respondents’ Post-Internship Salary by Gender and Graduation Year
Equine 1966 or prior
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Male (n=147) $21,000 $22,192 $27,960 $30,431 $51,400 $56,043 $61,867 Female (n=327) - $20,000 $27,250 $31,529 $46,224 $51,992 $51,109
AVMA 1966 or prior
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Male (n=153) $9,229 $24,625 $30,154 $45,580 $64,660 $70,267 $61,810 Female (n=411) - $49,000 $27,900 $44,951 $67,209 $70,645 $70,452
Internship Program Focus
The focus of an internship program is often well defined. Prospective interns can seek training
in an academic/university setting, corporate-owned practice, private ambulatory practice,
private hospital-based referral practice, or a practice with multiple elements, such as a full-
service private specialty/referral hospital with an ambulatory division. Internships can also
focus on a specific facet of practice such as surgery or imaging, or may be a rotating internship
that offers exposure to a variety of practice settings.
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As indicated in Figure 35, 49.9 percent of Equine respondents’ internships occurred in a private
referral practice setting, followed by 28.6 percent in an academic/university location. The
AVMA respondents indicated a similar pattern, with 45.3 percent of respondents reporting that
they focused on private referral practice, with 34.3 percent reporting an academic/university
focus. AVMA respondents had a 5.7 percent higher participation in an academic setting than
seen in Equine respondents.
Figure 35: Distribution of Equine and AVMA Respondents’ Program Focus of Internship
0.0%10.0%20.0%30.0%40.0%50.0%60.0%
% o
f Res
pond
ents
Program Focus
Distribution of Respondents' Program Focus of Internship
Equine (n=563) AVMA (n=651)
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When comparing internship focus of respondents by gender, 53.4 percent of female Equine
respondents reported that they participated in an internship at a private referral practice,
compared to 41.2 percent of males. 21.9 percent of female Equine respondents’ internships
were located in an academic/university setting, compared to 44.2 percent of male respondents
(Figure 36). Among AVMA respondents, 49.5 percent of females reported focusing on private
referral practice compared to 33.7 percent of males. Of AVMA female respondents, 30.6
percent trained in an academic/university internship setting compared to 46.1 percent of
males.
44.2%
1.2%12.7%
41.2%
0.6%
21.9%
0.3%
21.4%
53.4%
3.1%
% o
f Res
pond
ents
Program Focus
Distribution of Equine Respondents' Program Focus of Internship by Gender
Male Female
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Figure 36: Distribution of Equine and AVMA Respondents’ Program Focus of Internship by Gender
46.1%
2.8%8.4%
33.7%
3.9% 1.1% 3.9%
30.6%
2.7%9.7%
49.5%
2.9% 0.2% 4.3%
% o
f Res
pond
ents
Program Focus
Distribution of AVMA Respondents' Program Focus of Internship by Gender
Male Female
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Segmenting the type of internship by practice type, gender and graduation year shows an
increase in specialization and increased opportunities for achieving that focus through private
referral practices. As the referral practices have increased they have provided increased
opportunities for specialty board certification. In addition, while the percent of those choosing
a private general practice internship across the profession has shown little change, there has
been substantial change in this choice for equine practitioners (Table 16).
Table 16: Distribution of Equine and AVMA Respondents’ Program Focus of Internship by Gender and Graduation Year
Equine Academic/ University
Corporate-owned practice
Private general practice
Private referral practice
Other
Male Female Male Female Male Female Male Female Male Female
2012-2016 (n=185)
15.4% 8.2% 0.0% 0.6% 3.8% 26.4% 80.8% 61.6% 0.0% 3.1%
2007-2011 (n=129)
4.3% 20.8% - - 30.4% 21.7% 65.2% 52.8% 0.0% 4.7%
1997-2006 (n=96)
30.8% 27.1% - - 11.5% 18.6% 57.7% 51.4% 0.0% 2.9%
1987-1996 (n=68)
50.0% 55.3% - - 10.0% 2.6% 36.7% 42.1% 3.3% 0.0%
1977-1986 (n=38)
76.0% 61.5% 8.0% 0.0% 8.0% 30.8% 8.0% 7.7% - -
1967-1976 (n=30)
78.6% 100.0% - - 14.3% 0.0% 7.1% 0.0% - -
1966 or prior (n=4)
75.0% 75.0% - - - - 25.0% 25.0% - -
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AVMA Academic/ University
Corporate-owned practice
Private general practice
Private referral practice
Male Female Male Female Male Female Male Female 2012-2016 (n=153)
21.4% 17.6% 7.1% 4.8% 14.3% 8.0% 53.6% 63.2%
2007-2011 (n=167)
41.9% 32.4% 3.2% 4.4% 3.2% 8.8% 45.2% 51.5%
1997-2006 (n=166)
43.1% 27.8% 2.0% 0.0% 7.8% 13.0% 41.2% 49.6%
1987-1996 (n=74)
61.5% 50.0% 3.8% 0.0% 7.7% 10.4% 19.2% 22.9%
1977-1986 (n=25)
66.7% 70.0%
6.7% 10.0% 20.0% 0.0%
1967-1976 (n=17)
66.7% 80.0%
8.3% 0.0% 0.0% 20.0%
1966 or prior (n=10)
20.0%
AVMA Not-For-Profit Uniform Services Other
Male Female Male Female Male Female 2012-2016 (n=153)
0.0% 3.2% 0.0% 0.8% 3.6% 2.4%
2007-2011 (n=167)
3.2% 0.7% 3.2% 2.2%
1997-2006 (n=166)
5.9% 4.3% 0.0% 5.2%
1987-1996 (n=74)
0.0% 6.3% 3.8% 0.0% 3.8% 10.4%
1977-1986 (n=25)
6.7% 0.0% 0.0% 20.0%
1967-1976 (n=17)
25.0% 0.0%
1966 or prior (n=10)
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Internship Species Focus
Interns often intend to focus on specific species during an internship. As expected, the majority
(90.4 percent) of Equine respondents focused on equine work, while 65.4 percent of
respondents from the AVMA sample focused on companion animals (Figure 37).
Figure 37: Distribution of Equine and AVMA Respondents by Species Focus of Internship
0.4%
90.4%
4.1% 5.2%
65.4%
18.3%4.8% 3.6%
Companionanimal
Equine Food animal Mixed animal Exotic orzoological
animal
% o
f Res
pond
ents
Species Focus
Distribution of Respondents by Species Focus of Internship
Equine (n=563) AVMA (n=641)
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Internship Primary Focus
An investigation of the primary work focus of internships revealed that 56.9 percent of Equine
respondents and 73.2 percent of AVMA respondents worked in practices where they rotated
through different departments or foci (Table 17); 15.3 percent of Equine respondents focused
on ambulatory practice and 15.3 percent on surgery; 6.7 percent of AVMA respondents
participated in an internship focused on emergency/critical care, followed by 5.5 percent
concentrating on internal medicine.
Table 17: Distribution of Equine and AVMA Respondents by Primary Focus of Internship
Primary Focus Equine (n=562) AVMA (n=642)
General rotating 56.9% 73.2% Ambulatory 15.3% 0.0% Surgery 15.3% 4.7% Sports Medicine and Rehabilitation 5.0% 0.0% Theriogenology 3.0% 0.0% Emergency/Critical Care 2.0% 6.7% Internal Medicine 1.6% 5.5% Dentistry 0.5% 0.0% Anesthesia 0.2% 0.5% Veterinary Practitioners 0.2% 0.0% Laboratory Animal Medicine 0.0% 1.1% Radiology 0.0% 0.0% Zoological Medicine 0.0% 0.0% Oncology 0.0% 0.2% Pathology 0.0% 0.3% Toxicology 0.0% 0.0% Behavior 0.0% 0.0% Dermatology 0.0% 0.2% Microbiology 0.0% 0.0% Other 0.0% 7.8% Total 100.0% 100.0%
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Satisfaction and Experience with Internships
Examining the distribution of respondents by gender finds that 91.5 percent of male Equine
respondents were extremely or very satisfied with their internship experience versus 75.3
percent of female Equine respondents. In the AVMA sample 77.7 percent of males were
extremely or very satisfied with their internship versus 69.9 percent of AVMA females (Figure
38).
Figure 38: Distribution of Equine and AVMA Respondents’ Internship Satisfaction by Gender
0.0%10.0%20.0%30.0%40.0%50.0%60.0%
Extremelysatisfied
Very satisfied Moderatelysatisfied
Not toosatisfied
Not satisfiedat all
% o
f Res
pond
ents
Satisfaction Level
Distribution of Respondents' Internship Satisfaction by Gender
Equine - Male (n=165) Equine - Female (n=393)
AVMA - Male (n=179) AVMA - Female (n=445)
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Segmenting the satisfaction rating of those who participated in an internship by year of
graduation found that the overall satisfaction level has fallen over time for both the Equine and
AVMA samples (Table 18).
Table 18: Distribution of Equine and AVMA Respondents’ Internship Satisfaction by Graduation Year
Equine 1966 or less
(n=6)
1976-1967
(n=30)
1986-1977
(n=38)
1996-1987
(n=68)
2006-1997
(n=96)
2011-2007
(n=131)
2016-2012
(n=185) Extremely satisfied
66.7% 60.0% 57.9% 61.8% 49.0% 37.4% 31.9%
Very satisfied 33.3% 20.0% 28.9% 29.4% 39.6% 43.5% 37.3% Moderately satisfied
0.0% 16.7% 10.5% 7.4% 6.3% 16.0% 25.9%
Not too satisfied 0.0% 3.3% 2.6% 1.5% 4.2% 2.3% 4.3% Not satisfied at all 0.0% 0.0% 0.0% 0.0% 1.0% 0.8% 0.5%
AVMA 1966 or prior
(n=12)
1976-1967
(n=17)
1986-1977
(n=25)
1996-1987
(n=82)
2006-1997
(n=174)
2011-2007
(n=173)
2016-2012
(n=161) Extremely satisfied
58.3% 52.9% 52.0% 41.5% 42.0% 31.8% 34.8%
Very satisfied 41.7% 35.3% 32.0% 35.4% 32.8% 34.1% 33.5% Moderately satisfied
0.0% 11.8% 8.0% 11.0% 17.8% 19.7% 23.6%
Not too satisfied 0.0% 0.0% 8.0% 11.0% 4.6% 8.7% 5.0% Not satisfied at all 0.0% 0.0% 0.0% 1.2% 2.9% 5.8% 3.1%
When determining whether the specific internship experiences have met the expectations of
the participating veterinarian, rankings of certain experience expectations associated with an
internship were considered, as displayed in Figure 39 . Most Equine and AVMA respondents
believed that their internship met their learning/career objectives “extremely well” or “very
well” (Equine: 81.0 percent; AVMA: 79.8 percent). In evaluating their experience in the context
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of how consistent it was with the advertised internship description, more than half of the
Equine and AVMA samples thought the experience matched “extremely well” or “very well”
with that description. More than 90 percent of Equine respondents believed their internship
made them a better veterinarian. In considering how the their internship performed in gaining
valuable mentors, almost 80 percent of Equine respondents and about 60 percent of AVMA
respondents reported that it did “extremely well” or “very well.” Nearly three-quarters (73.3
percent) of Equine respondents however, reported receiving little business training. The
percentage was even higher (84.0 percent) for the AVMA respondents. There was more positive
feedback from Equine respondents on clinical skills improvement (88.8 percent reported “met
expectations extremely well” or “met expectations very well”) than of skills involving
comunication/client relationships (58.6 percent). AVMA respondents showed similar
experience ratings for these aspects of their internship (84 percent and 59.1 percent,
respectively).
41.8% 39.1%
15.7%
2.8% 0.5%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Learning/Career objectives
Equine AVMA
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36.8% 38.2%
18.6%
4.3% 2.1%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Being consistent with the advertised internship description
Equine AVMA
57.7%
32.9%
7.7% 1.3% 0.5%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Becoming a better veterinarian
Equine AVMA
51.7%
28.3%
13.4%4.8% 1.8%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Gaining valuable mentors
Equine AVMA
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43.9%33.0%
18.8%
3.0% 1.3%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Easing transition from student to practicing veterinarian
Equine AVMA
59.8%
28.9%
9.3%1.8% 0.2%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Improving clinical skills
Equine AVMA
9.1%17.6%
27.1%33.5%
12.7%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Improving understanding of the management of a business
Equine AVMA
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Figure 39: Distribution of Equine and AVMA Respondents’ by Satisfaction with Specific Internship Expectations
Note: Client-building skills are associated with building rapport and a relationship with a client
yielding a high level of trust in the veterinarian, a desire on the part of the client to return to the
same veterinarian for services, and to recommend the veterinarian to others.
Overall, if Equine respondents had the option of participating in an internship again, 75.3
percent would participate in the same internship, 15.1 percent would participate in a different
internship, 1.8 percent said they would not participate in an internship, and 7.8 percent said
they are not sure what they would do (Figure 40).
24.6%
34.0%27.6%
11.4%
2.3%
Extremelywell
Very well Moderatelywell
Not too well Not well atall
Improving client building skills
Equine AVMA
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Figure 40: Distribution of Equine Respondents by Likelihood of Future Internship Participation
Factors That Are Significant in Explaining the Population of Veterinarians Who Participated In an
Internship After Graduation
Using a binary logit model, factors associated with past internship participation are identified. A
binary logit measures the relationship between the variable of interest (dependent variable)
and the factors (independent variables) hypothesized to affect the variable of interest. In the
binary logistic regression, however, the dependent variable has only two values (1=yes, 0=no)
and the relationship measured is the probability of the dependent variable occurring when the
factor occurs. The dependent variable is veterinarians who participated in an internship taking
on the value of 1, with those who did not participate in an internship taking on the value of 0.
Independent variables that were used to attempt to explain internship participation include:
graduation year, gender, education level, residency participation, board certified, first position
75.3%
15.1%
1.8%7.8%
I would participatein the sameinternship
I would participatein a different
internship
I would notparticipate in an
internship
I'm not sure what Iwould do
% o
f Res
pond
ents
View of Internship Participation
Distribution of Equine Respondents by Likelihood of Future Internship Participation (n=499)
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after internship (private or public practice positions), education preparation, student veterinary
debt, and veterinary school.
In this table the coefficients are used to calculate the probability of an individual respondent
falling into a specific category (participated in an internship or did not participate in an
internship). The main criterion is to observe whether the coefficient is positive or negative. This
will indicate the direction of the relationship (i.e., negative is more likely to have not
particpated in an internship and positive more likely to have participated in an internship).
Variables that significantly contribute to predictive ability of the model would have a p-value of
.10 or less in the column labeled “Sig.” Variables that are significant at the 10, 5, and 1 percent
level are reported in explaining the factors that affected participation in an internship. The
“Odds Ratio” column is the probability of having participated in an internship assigned to each
of the independent variables and is defined as “the change in odds of being in one of the
categories of outcome (participated in an internship or did not participate in an internship)
when the value of one of the independent variables (predictors) increases by one point.”16 To
interpret the odds ratio, the odds ratio value is subtracted by one to obtain the odds of the
event occurring.
As a baseline for comparison with the other variables in the respective groups, the following
factors were omitted from the model: bachelor’s degree, The Ohio State University, first
position equine practice (Equine model) and first position companion animal practice (AVMA
model).
16 Barbara G. Tabachnick and Linda S. Fidell. Using Multivariate Statistics, 6th Edition (New York City, New York: Pearson, 2013), pg.8.
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Results in Table 19 show that for Equine respondents, the year of graduation variable is
negative and significant, implying the longer a respondent has been out of veterinary school the
less likely they were to have participated in an internship. The odds ratio is interpreted as for a
one-unit increase in year (a change) since graduation, the odds of having participated in an
internship versus not participating in an internship was .07 times lower given that all the other
variables are held constant. In percent terms, each unit increase in graduation decreased the
odds of participation in an internship by 7 percent.
Other significant variables in the Equine sample that affected the odds of a respondent who
particpated or did not participate in an internship include residency participation (odds were
7.06 greater that a respondent who participated in a residency pursued an internship than
respondents who did not particpate in a residency), first position in food animal practice (odds
were .96 lower that a respondent who participated in an internship had a first position in food
animal practice than a first position in equine practice), first position in companion animal
practice (odds were .78 lower than respondents’ first position being in equine practice), first
position in mixed animal practice (odds were .88 lower than respondents’ first position being in
equine practice), first position in a university/college (odds were 5.92 greater than respondents’
first position being in equine practice), and first position in industry/commercial organization
(odds were .94 lower than respondents’ first position being in equine practice), given all other
variables are held constant. In addition, respondents who attended veterinary college at
University of Florida, Mississippi State University and University of Wisconsin had a significant
negative relationship with The Ohio State University in identifying the variation in internship
participation by veterinary school, meaning that the respondents who graduated from these
three veterinary schools, the odds of having participated in an internship versus not
particpating in an internship were lower than the respondents who attended The Ohio State
University.
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Table 19: Factors That Are Significant in Explaining the Population of Veterinarians Who Participated in an Internship After Graduation
Equine Coefficient Std. Error Sig. Odds Ratio
Graduation Year -0.069 0.013 0.00*** 0.93 Gender (Female=1) 0.226 0.257 0.38 1.25 DVM Debt 0.000 0.000 0.38 1.00 Education Preparation (5=Extremely well/1=Not well at all)
-0.059 0.143 0.68 0.94
Bachelor’s (baseline) Omitted Ph.D. -0.623 0.713 0.38 0.54 Master’s -0.247 0.318 0.44 0.78 Specialty Degree -1.055 1.031 0.31 0.35 DVM only -0.393 0.361 0.28 0.68 Residency (Yes=1) 1.954 0.499 0.00*** 7.06 Board Certified (Yes=1) -0.147 0.522 0.78 0.86 First Position - Equine (baseline) Omitted First Position - Food Animal -3.256 0.797 0.00*** 0.04 First Position - Companion Animal -1.522 0.410 0.00*** 0.22 First Position - Mixed Animal -2.136 0.274 0.00*** 0.12 First Position - University/College 1.778 0.654 0.01*** 5.92 First Position - Industry/Commercial -2.779 1.439 0.05** 0.06 The Ohio State University (baseline) Omitted Auburn University -0.512 0.659 0.44 0.60 Tuskegee University 0.002 1.124 1.00 1.00 University of California - Davis -0.085 0.605 0.89 0.92 Colorado State University -0.362 0.570 0.53 0.70 University of Florida -1.129 0.641 0.08* 0.32 University of Georgia 0.019 0.814 0.98 1.02 University of Illinois -1.018 0.800 0.20 0.36 Iowa State University -0.112 0.761 0.88 0.89 Kansas State University -0.185 0.643 0.77 0.83 Louisiana State University 0.050 0.915 0.96 1.05 Tufts University 0.154 0.702 0.83 1.17 Michigan State University -0.513 0.845 0.54 0.60 Mississippi State University -1.725 0.916 0.06* 0.18 Purdue University 0.411 0.763 0.59 1.51 Cornell University 0.037 0.657 0.96 1.04
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Oklahoma State University -0.461 0.712 0.52 0.63 University of Pennsylvania -0.528 0.638 0.41 0.59 Texas A&M University 0.235 0.669 0.73 1.26 Washington State University 0.298 0.758 0.70 1.35 University of Missouri-Columbia -0.592 0.648 0.36 0.55 Oregon State University -0.274 0.856 0.75 0.76 University of Tennessee -0.239 1.017 0.81 0.79 North Carolina State University -0.722 0.794 0.36 0.49 University of Wisconsin -1.479 0.741 0.05** 0.23 Western University of Health Sciences -0.645 0.967 0.51 0.52 University of Minnesota -0.855 0.675 0.21 0.43 Other college 0.082 0.561 0.88 1.09 Virginia-Maryland College -0.727 0.781 0.35 0.48 Constant 2.367 0.769 0.00*** 10.66
Observations 674
Pseudo R-Square 0.3271
***, **, and * indicate significance at the 1 percent, 5 percent, and 10 percent levels, respectively.
Note: Federal government, uniformed services, state and local government, not-for-profit, and
other type of first position were omitted because the number of observations did not permit
estimation.
AVMA Coefficient Std. Error Sig. Odds Ratio
Age -0.037 0.009 0.00*** 0.96 Gender (Female=1) 0.034 0.162 0.84 1.03 DVM Debt 0.000 0.000 0.19 1.00 Education Preparation (5=Extremely well/1=Not well at all)
0.038 0.089 0.67 1.04
Bachelor’s (baseline) Omitted Ph.D. -0.329 0.280 0.24 0.72 Master’s -0.138 0.193 0.47 0.87 Specialty Degree -0.395 1.469 0.79 0.67 DVM only -0.511 0.299 0.09* 0.60 Residency (Yes=1) 2.190 0.326 0.00*** 8.93 Board Certified (Yes=1) 0.327 0.327 0.32 1.39
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First Position - Companion Animal (baseline)
Omitted
First Position - Mixed Animal -0.858 0.243 0.00*** 0.42 First Position - Food Animal -1.566 0.544 0.00*** 0.21 First Position - Equine 1.698 0.248 0.00*** 5.47 First Position - Federal Government -1.231 1.106 0.27 0.29 First Position - Uniformed Services -1.035 0.710 0.15 0.36 First Position - University/College 0.566 0.323 0.08* 1.76 First Position - State/Local Government -1.130 1.187 0.34 0.32 First Position - Industry/Commercial -1.017 0.639 0.11 0.36 First Position - Not-for-profit 0.154 0.457 0.74 1.17 First Position - Advanced Education -0.879 1.278 0.49 0.42 First Position - Other 0.861 0.403 0.03** 2.37 The Ohio State University (baseline) Omitted Auburn University -0.436 0.487 0.37 0.65 Tuskegee University 0.177 0.604 0.77 1.19 University of California - Davis 0.398 0.394 0.31 1.49 Colorado State University 0.526 0.388 0.18 1.69 University of Florida 0.541 0.454 0.23 1.72 University of Georgia -1.005 0.529 0.06* 0.37 University of Illinois -0.101 0.440 0.82 0.90 Iowa State University -0.922 0.514 0.07* 0.40 Kansas State University 0.443 0.396 0.26 1.56 Louisiana State University -0.795 0.549 0.15 0.45 Tufts University 0.865 0.423 0.04** 2.37 Michigan State University -0.329 0.458 0.47 0.72 University of Minnesota 0.013 0.424 0.98 1.01 Mississippi State University -0.552 0.570 0.33 0.58 Purdue University -0.561 0.533 0.29 0.57 Cornell University 0.997 0.417 0.02** 2.71 Oklahoma State University -0.082 0.557 0.88 0.92 University of Pennsylvania 0.375 0.393 0.34 1.46 Texas A&M University -0.349 0.439 0.43 0.71 Washington State University -0.436 0.491 0.38 0.65 University of Missouri-Columbia -1.052 0.557 0.06* 0.35 Oregon State University -0.741 0.648 0.25 0.48 University of Tennessee 0.104 0.507 0.84 1.11
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Virginia-Maryland College -0.687 0.465 0.14 0.50 North Carolina State University -0.341 0.500 0.50 0.71 University of Wisconsin -0.344 0.466 0.46 0.71 Western University of Health Sciences 0.357 0.569 0.53 1.43 Other college -0.098 0.334 0.77 0.91 Constant -1.006 0.493 0.04** 0.37
Observations 1,761
Pseudo R-Square 0.218
***, **, and * indicate significance at the 1 percent, 5 percent, and 10 percent levels, respectively
3.6.3 Residency Participation
Veterinarians who want to pursue residency training generally complete an internship program
in order to obtain a competitive edge in selection for a residency. A veterinarian with several
years of clinical experience who has never undertaken an internship can, however, still
successfully apply for some residency programs. A residency offers advanced training in a
specialty area of veterinary medicine to veterinarians who intend to acquire a specialty
certification from an AVMA-recognized veterinary specialty organization. Veterinary specialty
organizations establish guidelines to ensure that these residencies are approved as appropriate
training for board eligibility and specialty certification. An approved residency program is
conducted under the supervision of a board-certified specialist. A residency is usually narrowly
confined to a specific discipline. A residency might, in some instances, be related to an
advanced degree program.
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Overall, in the entire Equine sample 20.9 percent of respondents reported residency
participation at some point during their veterinary career, compared to 13.0 percent of AVMA
respondents (Figure 41).
Figure 41: Distribution of Equine and AVMA Respondents’ Participation in a Residency
20.9% 13.0%
79.1% 87.0%
Equine (n=1,056) AVMA (n=2,530)
% o
f Res
pond
ents
Residency Participation
Distribution of Respondents' Participation in a Residency
I'm neither participating in, nor have I completed a residency
I have completed a residency
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Prior to actually participating in a residency, 27.4 percent of AAEP respondents had applied or
attempted to participate in a residency. More than two-thirds (69.6 percent) of the AAEP
respondents who reported that they had applied or attempted to participate in a residency had
completed a residency (Figure 42), while 23.5 percent ended up neither participating nor
completing a residency; 6.9 percent currently were participating in a residency.
Figure 42: Distribution of AAEP Respondents (Who Applied or Attempted to Participate in a Residency) by Residency Participation
Note: Chart includes respondents who did not participate in an internship but participated in a
residency.
6.9%
69.6%
23.5%
Distribution of AAEP Respondents (Who Applied or Attempted to Participate in a Residency) by Residency Participation
I am currently participatingin a residency (n=20)
I have completed aresidency (n=201)
I'm neither participating in,nor have I completed aresidency (n=68)
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Three-fifths (60 percent) of those Equine respondents who reported completing a residency did
so since 2000; for the same time period a slightly higher proportion of AVMA respondents (63.7
percent) reported doing so (Figure 43).
Figure 43: Distribution of Equine and AVMA Respondents by Year of Completed (or Future Completion) Residency
Note: Chart includes respondents who did not participate in an internship but participated in a
residency.
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
1974 orprior
1975 -1979
1980 -1984
1985 -1989
1990 -1994
1995 -1999
2000 -2004
2005 -2009
2010 -2014
2015 -2019
% o
f Res
pond
ents
Year of Residency Completion
Distribution of Respondents by Year of Completed (or Future Completion) Residency
Equine (n=220) AVMA (n=328)
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In contrast to internship participation, which had a large difference in Equine participation rates
(64.3 percent for females, and 37.9 percent for males), the residency gender distribution was
much tighter with 21.8 percent of males and 19.5 percent of female Equine respondents
participating in a residency (Figure 44).
Figure 44: Distribution of Equine and AVMA Respondents Who Participated in a Residency by Gender
19.5%
21.8%
16.4%
11.6%
Equine Male (n=85)
Equine Female (n=133)
AVMA Male (n=126)
AVMA Female (n=188)
Distribution of Respondents Who Participated in a Residency by Gender
Residency Participation
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Among Equine and AVMA respondents who previously replied that one of the reasons they
were participating in an internship was because they planned to apply for a residency, more
than half of these male and female Equine respondents and male AVMA respondents reported
completing (or currently participating in) a residency, while less than 50 percent of female
AVMA respondents with this reason for internship participation reported completing (or
currently participating in) a residency (Figure 45).
Figure 45: Distribution of Equine and AVMA Respondents Who Stated They Were Participating in an Internship because They Planned to Apply for a Residency, and Their Residency Completion Status by Gender
58.5% 58.9%64.7%
47.5%41.5% 41.1%
35.3%
52.5%
Equine - Male Equine - Female AVMA - Male AVMA - Female
% o
f Res
pond
ents
Residency Completion
Distribution of Respondents Who Stated They Were Participating in an Internship because They Planned to Apply for a Residency, and
Their Residency Completion Status by Gender
I have completed (or currently participating) in a residency
I'm neither participating in, nor have I completed a residency
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As with interns, residents also choose a program focus environment (Figure 46). The majority of
respondents across both Equine and AVMA samples participated in an academic/university
setting (Equine: 95.0 percent; AVMA: 84.1 percent). Academic settings are generally affiliated
with major veterinary teaching hospitals. The second most prevalent program location for
respondents pursuing residency training was in a private referral hospital. Of the Equine sample
respondents, 4.1 percent trained in a private hospital, compared to 9.8 percent of AVMA
respondents.
Figure 46: Distribution of Equine and AVMA Respondents by Program Focus of Residency
Privatereferralpractice
Privategeneralpractice
Academic/University
Not-for-profit
Corporate-ownedpractice
UniformedServices Other
Equine (n=221) 4.1% 0.5% 95.0% 0.5% 0% 0% 0%AVMA (n=328) 9.8% 0.6% 84.1% 1.5% 0.3% 1.5% 2.1%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0%
100.0%
% o
f Res
pond
ents
Residency Program
Distribution of Respondents by Program Focus of Residency
Equine (n=221) AVMA (n=328)
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Within the residency program, 76.5 percent of Equine respondents focused on equines,
followed by 14.5 percent who worked on mixed animal species, 6.3 percent other species, 1.8
percent food animals, and less than 1 percent companion animals. 43 percent of AVMA
respondents focused on companion animals, 22.3 percent other species, 18.5 percent mixed
animals, 8.3 percent exotic or zoological animals, and 8 percent equines (Figure 47).
Figure 47: Distribution of Equine and AVMA Respondents by Species Focus of Residency
About 44 percent of Equine respondents had a residency focus of surgery, followed by 28.5
percent in internal medicine (Table 20). In the AVMA sample, residency focus was more widely
distributed: 19.6 percent studied internal medicine, 19.3 percent focused on “Other”
specialties, and 16.8 percent trained in surgery.
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
Companionanimal
Equine Mixedanimal
Foodanimal
Exotic orzoological
animal
Other
% o
f Res
pond
ents
Species Focus
Distribution of Respondents by Species Focus of Residency
Equine (n=221) AVMA (n=314)
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Table 20: Distribution of Equine and AVMA Respondents by Primary Focus of Residency
Primary Focus Equine (n=221)
AVMA (n=327)
Surgery 44.3% 16.8% Internal Medicine 28.5% 19.6% Theriogenology 11.8% 0.0% General rotating 3.2% 2.7% Ambulatory 2.7% 0.0% Radiology 2.3% 0.0% Sports Medicine and Rehabilitation 1.8% 0.0% Dentistry 1.4% 0.0% Pathology 0.9% 10.4% Emergency/critical care 0.9% 4.9% Other 0.5% 19.3% Laboratory Animal Medicine 0.5% 13.8% Ophthalmology 0.5% 2.1% Pharmacology 0.5% 0.0% Veterinary Practitioners 0.5% 0.0% Oncology 0.0% 3.7% Neurology 0.0% 2.8% Anesthesia 0.0% 2.7% Dermatology 0.0% 1.2% Total 100.0% 100.0%
After veterinarians complete their residency, they have the opportunity to become board
certified. An individual who is board certified in a veterinary specialty generally participated in
an internship after graduation from veterinary school, followed by several years of advanced
residency training. Board certification is awarded once the individual demonstrates an
advanced level of knowledge and skill by successfully passing a certification examination
developed and administered by an AVMA-recognized veterinary specialty organization.
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A higher percent of Equine respondents (18.3 percent) than AVMA respondents (14.8 percent)
reported being board certified. Of those Equine respondents who are board certified, 39.9
percent are board certified in surgery, 25.9 percent in internal medicine, and the remainder
across several other categories (Table 21). In the AVMA sample, 18.9 percent are certified in
internal medicine, 12.5 percent in surgery and 12 percent in laboratory animal medicine.
Table 21: Distribution of Board-Certified Equine and AVMA Respondents by AVMA-Recognized Veterinary Specialty Organizations
AVMA-Recognized Veterinary Specialty Organizations
Equine (n=193)
AVMA (n=371)
Surgery 39.9% 12.5% Internal Medicine 25.9% 18.9% Theriogenology 11.9% 3.5% Veterinary Practitioners 9.8% 7.2% Sports Medicine and Rehabilitation
9.8% 1.1%
Emergency & Critical Care 5.7% 4.3% Radiology 2.6% 3.5% Preventive Medicine 2.1% 9.3% Other 1.6% 5.3% Pathology 1.0% 8.8% Microbiology 1.0% 2.9% Pharmacology 1.0% 1.1% Dentistry 1.0% 0.8% Laboratory Animal Medicine 0.5% 12.0% Anesthesia 0.5% 2.7% Zoological Medicine 0.5% 2.1% Ophthalmology 0.5% 1.3% Poultry Veterinarians 0.0% 2.9% Nutrition 0.0% 1.3% Toxicology 0.0% 1.1% Animal Welfare 0.0% 1.1% Dermatology 0.0% 0.8% Behavior 0.0% 0.3%
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3.6.4 College Preparedness
Survey data indicated that 29.5 percent of Equine respondents and 30.4 percent of AVMA
respondents believed that their education prepared them “moderately well,” “not too well,” or
“not well at all” for life after veterinary college. The graduation year was found to be significant
with regard to educational preparation, and is presented in Figure 48. Among the Equine
respondents, 51.5 percent of those who graduated in 2012-2016 were satisfied “moderately
well,” “not too well” or “not well at all” with their college education, compared to 39.3 percent
of AVMA respondents. In the Equine sample, the respondents choosing “extremely well”
declined within each group of respondents as identified by year of graduation beginning with
1966 or prior. Those who indicated they were “very well prepared” showed an increasing trend
across graduation groups up to 2011. But only 39.8 percent of Equine respondents who
graduated in 2012-2016 reported being very well prepared, down from a high of 54.7 percent
of the 2007-2011 cohort. Respondents in the AVMA sample who answered “very well
prepared” was 47.2 percent for the 2007-2011 cohort and 50.4 percent in 2012-2016.
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2012-2016
(n=241)
2007-2011
(n=179)
1997-2006
(n=168)
1987-1996
(n=170)
1977-1986
(n=166)
1967-1976
(n=92)
1966 orprior
(n=24)Not well at all 0.8%0.0%0.6%0.0%0.0%0.0%0.0%Not too well 5.0%1.7%0.6%1.2%1.8%1.1%0.0%Moderately well 45.6%27.9%28.0%19.4%15.1%9.8%8.3%Very well 39.8%54.7%51.8%47.6%45.8%35.9%29.2%Extremely well 8.7%15.6%19.0%31.8%37.3%53.3%62.5%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Graduation Year
Distribution of Equine Respondents' Attitudes About College Education Preparation by Graduation Year
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Figure 48: Distribution of Equine and AVMA Respondents’ Attitudes about College Education Preparation by Graduation Year
3.6.5 Most Important Skills for New Veterinarians
In addition to learning specific skills in the veterinary medical curriculum, during an internship
and/or residency veterinarians may be exposed to newly developed techniques or variations of
treatment methods. Other skills are learned through continuing education or developed though
experience on the job. Employers typically expect new associates to possess certain entry-level
skills.
A specific question in the 2016 AVMA-AAEP Survey of Equine Practitioners asked respondents to
answer the question: “For each procedure below, please indicate whether or not it is important
for new associates to have mastery of it to work in the practice you own or are employed at.”
This question was specific to the AAEP survey, so only the AAEP sample was used for analysis.
2012-2016
(n=601)
2007-2011
(n=506)
1997-2006
(n=650)
1987-1996
(n=363)
1977-1986
(n=189)
1967-1976
(n=111)
1966 orprior
(n=79)Not well at all 0.5%0.0%0.2%0.0%0.0%0.0%0.0%Not too well 3.2%3.8%2.2%1.4%1.6%0.9%1.3%Moderately well 35.6%33.6%28.0%22.9%13.8%10.8%11.4%Very well 50.4%47.2%46.3%44.9%47.1%40.5%45.6%Extremely well 10.3%15.4%23.4%30.9%37.6%47.7%41.8%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Graduation Year
Distribution of AVMA Respondents' Attitudes About College Education Preparation by Graduation Year
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About 90 percent of the AAEP respondents stated that it was important for new associates to
have mastery of diagnosing and treating foot abscesses, and of examining and repairing simple
lacerations. Diagnosing uncomplicated lameness using diagnostic nerve blocks, obtaining
diagnostic radiographs of limbs, performing a complete physical or ophthalmic exam, placing IV
catheters and subpalpebral lavage systems, setting up preventative health protocols, and
working up, treating and making recommendations for colic cases in the field were reported to
be essential basic skills by more than 80 percent of AAEP respondents. Less than 20 percent of
respondents considered the ability to perform gastroscopy or a standing castration as entry-
level skills. About one-third of AAEP respondents considered applying a foot or limb cast,
obtaining diagnostic radiographs of neck, performing abdominocentesis, thoracocentesis, a
transtracheal wash, rectal biopsy or other similar diagnostic procedures, and performing
diagnostic ultrasound of the abdomen or thorax as important for a new graduate (Table 22).
Table 22: Distribution of AAEP Respondents and the Importance of Specific Procedures for New Associates to Have Mastery of
Procedure Important Not important
Not relevant
Total
Diagnose and treat foot abscess 90.6% 2.1% 7.3% 100.0% Examine and repair simple lacerations 90.4% 1.3% 8.3% 100.0% Work up, treat and make recommendations for colic case in the field, including performing rectal examination, passage of nasogastric tube, and checking for or obtaining reflux
88.7% 2.9% 8.4% 100.0%
Perform complete physical or ophthalmic exam and document complete medical record
87.6% 4.2% 8.1% 100.0%
Diagnose uncomplicated lameness using diagnostic nerve blocks
84.9% 6.7% 8.4% 100.0%
Obtain diagnostic radiographs of limbs 84.8% 5.0% 10.2% 100.0% Set up preventative health protocols 84.7% 6.8% 8.5% 100.0% Place IV catheters, subpalpebral lavage systems, etc.
83.2% 8.4% 8.4% 100.0%
Remove shoes using common farrier's tools 79.8% 11.4% 8.9% 100.0% Perform routine dental maintenance (e.g., "floating", removing wolf teeth)
79.6% 7.4% 13.0% 100.0%
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Perform castration in recumbent anesthetized patient
74.8% 14.5% 10.8% 100.0%
Perform routine reproductive procedures such as Caslicks and uterine culture
73.7% 14.0% 12.3% 100.0%
Induce and recover patient in the field with intravenous anesthesia
69.0% 19.7% 11.3% 100.0%
Ultrasound mares and diagnose singleton pregnancy at 16-18 days post ovulation
63.3% 19.8% 16.9% 100.0%
Obtain samples from or inject substances into synovial structures such as joints or tendons
62.9% 26.4% 10.7% 100.0%
Perform diagnostic ultrasound of distal limbs 47.9% 40.1% 12.0% 100.0% Perform a regional limb perfusion 46.6% 39.3% 14.1% 100.0% Obtain diagnostic radiographs of head 44.6% 43.4% 12.0% 100.0% Perform endoscopy 43.4% 36.6% 20.0% 100.0% Perform diagnostic ultrasound of thorax (e.g., Rhodococcus equi screen, screen for pleuritis)
38.3% 46.2% 15.5% 100.0%
Perform abdominocentesis, thoracocentesis, transtracheal wash, rectal biopsy, and other similar diagnostic procedures
37.7% 47.0% 15.3% 100.0%
Apply a foot or limb cast 33.3% 47.1% 19.5% 100.0% Obtain diagnostic radiographs of neck 33.2% 52.3% 14.5% 100.0% Perform diagnostic ultrasound of abdomen (e.g. ileus, hemoabdomen, peritonitis)
30.6% 50.8% 18.7% 100.0%
Perform gastroscopy 19.2% 45.2% 35.5% 100.0% Perform castration in standing sedated patient 16.9% 44.2% 38.8% 100.0%
The expectation for entry-level associates to have mastery of a certain procedure may change
over time. To examine this, Table 23 presents procedures identified as important by
respondents who have less than 20 years of experience in the veterinary field, and by
respondents who have more than 20 years of experience in the veterinary field.
Certain procedures were felt to have different levels of importance by those respondents who
have under 20 years of experience compared to those with more than 20 years of experience.
For example, 41.4 percent of AAEP respondents with more than 20 years of experience stated
that applying a foot or limb cast is an important skill for new associates to have, compared to
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26.8 percent of veterinarians with fewer than 20 years of experience. In contrast, 55.8 percent
of veterinarians with fewer than 20 years of experience stated it is important for new associates
to be comfortable performing a regional limb perfusion, compared to 34.4 percent of
veterinarians with more than 20 years of experience. Additionally, 92.4 percent of
veterinarians with fewer than 20 years of experience stated it is important for new associates
to be skilled at performing a complete physical or ophthalmic exam, compared to 81.2 percent
of respondents with more than 20 years of experience. 86.3 percent of the former group
responded similarly regarding performing routine dental maintenance, compared to 70.6
percent of the latter group.
Some skills were reported by respondents as not relevant. Because of the variety of sectors in
which equine practitioners practice, some skills are not needed in some settings.
Table 23: Distribution of AAEP Respondents and the Importance of Specific Procedures for New Associates to Have Mastery by Years of Experience
Procedure - Less than 20 years of experience
Obs. Important Not important
Not relevant
Total
Apply a foot or limb cast 291 26.8% 58.4% 14.8% 100.0% Diagnose and treat foot abscess 291 94.8% 1.0% 4.1% 100.0% Diagnose uncomplicated lameness using diagnostic nerve blocks
291 87.6% 7.2% 5.2% 100.0%
Examine and repair simple lacerations 290 94.8% 0.3% 4.8% 100.0% Induce and recover patient in the field with intravenous anesthesia
291 70.1% 21.3% 8.6% 100.0%
Obtain diagnostic radiographs of head 290 43.4% 50.3% 6.2% 100.0% Obtain diagnostic radiographs of limbs 289 88.6% 5.2% 6.2% 100.0% Obtain diagnostic radiographs of neck 290 29.3% 62.4% 8.3% 100.0% Obtain samples from or inject substances into synovial structures such as joints or tendons
291 64.9% 27.8% 7.2% 100.0%
Perform a regional limb perfusion 292 55.8% 36.3% 7.9% 100.0% Perform abdominocentesis, thoracocentesis, transtracheal wash,
288 33.0% 54.2% 12.8% 100.0%
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rectal biopsy, and other similar diagnostic procedures Perform castration in recumbent anesthetized patient
289 75.1% 17.0% 8.0% 100.0%
Perform castration in standing sedated patient
291 13.4% 47.4% 39.2% 100.0%
Perform complete physical or ophthalmic exam and document complete medical record
291 92.4% 3.1% 4.5% 100.0%
Perform diagnostic ultrasound of abdomen (e.g. ileus, hemoabdomen, peritonitis)
292 33.2% 51.7% 15.1% 100.0%
Perform diagnostic ultrasound of distal limbs
287 48.1% 44.9% 7.0% 100.0%
Perform diagnostic ultrasound of thorax (e.g. Rhodococcus equi screen, screen for pleuritis)
290 41.7% 46.2% 12.1% 100.0%
Perform endoscopy 290 39.3% 40.7% 20.0% 100.0% Perform gastroscopy 289 18.7% 48.8% 32.5% 100.0% Perform routine dental maintenance (e.g., "floating", removing wolf teeth)
291 86.3% 6.9% 6.9% 100.0%
Perform routine reproductive procedures such as Caslicks and uterine culture
291 72.9% 16.8% 10.3% 100.0%
Place IV catheters, subpalpebral lavage systems, etc.
292 86.0% 9.2% 4.8% 100.0%
Remove shoes using common farrier's tools
289 83.4% 11.8% 4.8% 100.0%
Set up preventative health protocols 290 90.3% 5.2% 4.5% 100.0% Ultrasound mares and diagnose singleton pregnancy at 16-18 days post ovulation
291 64.9% 21.6% 13.4% 100.0%
Work up, treat and make recommendations for colic case in the field, including performing rectal examination, passage of nasogastric tube, and checking for or obtaining reflux
292 93.8% 1.4% 4.8% 100.0%
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Procedure - More than 20 years of experience
Obs. Important Not important
Not relevant
Total
Apply a foot or limb cast 227 41.4% 32.6% 26.0% 100.0% Diagnose and treat foot abscess 227 85.0% 3.5% 11.5% 100.0% Diagnose uncomplicated lameness using diagnostic nerve blocks
228 81.1% 6.1% 12.7% 100.0%
Examine and repair simple lacerations
226 84.5% 2.7% 12.8% 100.0%
Induce and recover patient in the field with intravenous anesthesia
228 67.1% 18.0% 14.9% 100.0%
Obtain diagnostic radiographs of head
223 46.6% 33.6% 19.7% 100.0%
Obtain diagnostic radiographs of limbs
228 79.8% 4.8% 15.4% 100.0%
Obtain diagnostic radiographs of neck
225 38.2% 39.1% 22.7% 100.0%
Obtain samples from or inject substances into synovial structures such as joints or tendons
228 59.6% 25.0% 15.4% 100.0%
Perform a regional limb perfusion 224 34.4% 43.3% 22.3% 100.0% Perform abdominocentesis, thoracocentesis, transtracheal wash, rectal biopsy, and other similar diagnostic procedures
225 44.4% 36.9% 18.7% 100.0%
Perform castration in recumbent anesthetized patient
227 74.9% 10.6% 14.5% 100.0%
Perform castration in standing sedated patient
225 21.8% 40.0% 38.2% 100.0%
Perform complete physical or ophthalmic exam and document complete medical record
223 81.2% 5.8% 13.0% 100.0%
Perform diagnostic ultrasound of abdomen (e.g. ileus, hemoabdomen, peritonitis)
224 27.2% 49.1% 23.7% 100.0%
Perform diagnostic ultrasound of distal limbs
226 47.8% 33.6% 18.6% 100.0%
Perform diagnostic ultrasound of thorax (e.g. Rhodococcus equi screen, screen for pleuritis)
223 34.1% 45.7% 20.2% 100.0%
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Perform endoscopy 226 48.7% 31.0% 20.4% 100.0% Perform gastroscopy 222 19.8% 40.5% 39.6% 100.0% Perform routine dental maintenance (e.g., "floating", removing wolf teeth)
221 70.6% 8.1% 21.3% 100.0%
Perform routine reproductive procedures such as Caslicks and uterine culture
225 75.6% 9.8% 14.7% 100.0%
Place IV catheters, subpalpebral lavage systems, etc.
228 79.8% 7.0% 13.2% 100.0%
Remove shoes using common farrier's tools
226 75.7% 10.2% 14.2% 100.0%
Set up preventative health protocols
225 77.8% 8.4% 13.8% 100.0%
Ultrasound mares and diagnose singleton pregnancy at 16-18 days post ovulation
225 61.8% 16.9% 21.3% 100.0%
Work up, treat and make recommendations for colic case in the field, including performing rectal examination, passage of nasogastric tube, and checking for or obtaining reflux
228 82.0% 4.8% 13.2% 100.0%
Competencies are skill or knowledge sets that make a practitioner successful at their work.
AAEP respondents were asked to rank 10 workplace competencies, on a scale of one to 10, on
their importance for new associates (Table 24). In general, people skills ranked higher than
organizational, technical or writing skills. People skills were cited as the most important
competency by 63.9 percent, followed by client communication (21.2 percent), and customer
service skills (4.8 percent). The three competencies ranked the least important were public
speaking (57.7 percent), technology proficiency (21.4 percent) and writing proficiency (11.9
percent).
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Table 24: Distribution of AAEP Respondents’ Important Competencies of New Associates
AAEP (n=496) Mean Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Total
People skills 1.7 63.9% 19.6% 8.3% 3.8% 2.2% 100.0% Ability to collaborate 4.5 3.4% 15.3% 16.3% 18.5% 16.1% 100.0% Client communication 2.5 21.2% 37.5% 25.4% 9.1% 4.4% 100.0% Conflict resolution 6.3 0.6% 1.8% 4.0% 14.9% 15.1% 100.0% Customer service skills 4.0 4.8% 12.9% 26.4% 21.8% 15.7% 100.0% Efficient use of resources
5.7 2.2% 3.8% 7.7% 10.3% 19.6% 100.0%
Organizational skills 5.8 1.0% 4.6% 6.9% 12.3% 16.3% 100.0% Proficiency in writing 8.2 0.2% 0.0% 0.6% 1.2% 2.0% 100.0% Public speaking 9.3 0.0% 0.2% 0.2% 0.4% 0.6% 100.0% Technology proficiency 7.0 2.6% 4.2% 4.2% 7.7% 7.9% 100.0%
AAEP (n=496) Mean Rank 6 Rank 7 Rank 8 Rank 9 Rank 10 Total
People skills 1.7 1.4% 0.6% 0.2% 0.0% 0.0% 100.0% Ability to collaborate 4.5 10.9% 10.3% 5.0% 3.2% 0.8% 100.0% Client communication 2.5 1.8% 0.4% 0.0% 0.0% 0.2% 100.0% Conflict resolution 6.3 15.9% 15.5% 15.5% 10.7% 5.8% 100.0% Customer service skills 4.0 9.3% 6.7% 1.6% 0.6% 0.2% 100.0% Efficient use of resources
5.7 22.4% 19.4% 10.5% 2.6% 1.6% 100.0%
Organizational skills 5.8 19.0% 23.6% 11.5% 4.4% 0.4% 100.0% Proficiency in writing 8.2 5.0% 11.3% 31.3% 36.5% 11.9% 100.0% Public speaking 9.3 1.6% 3.4% 8.7% 27.2% 57.7% 100.0% Technology proficiency 7.0 12.7% 8.9% 15.7% 14.7% 21.4% 100.0%
3.6.6 Equine Veterinarians Leaving the Equine Profession
Despite respondents reporting that their veterinary education prepared them well for their
career, young equine veterinarians are leaving the profession. AAEP membership data show
that many young veterinarians fail to renew their AAEP membership after five years from their
graduation date from veterinary school, and that the trend is slowly increasing (Figure 49): 37
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percent of members who were in the Class of 2000 did not renew their AAEP membership after
five years, 50 percent of members who were in the Class of 2011 did not renew their
membership after five years, and 47 percent of members who were in the Class of 2012 did not
renew their membership after five years. Starting with the Class of 2000, almost half (45
percent) of former AAEP members dropped their membership within five years of their
graduation date.
Figure 49: AAEP Membership Attrition by Graduation Year, 2000-201217
The Equine respondents were asked if they had changed from working in one veterinary sector
to another. A little more than one-quarter of Equine respondents (26.5 percent) reported
having made a change at some point during their career. Of the Equine respondents who
reported a change, 39 percent (91 out of 233 Equine respondents) who started in the equine
profession reported that they made their first change out of the equine veterinary sector.
17 Source: AAEP Membership Database
2000 2008 2009 2010 2011 2012% Attrition after 5 Years 37% 49% 44% 33% 50% 47%
0%
10%
20%
30%
40%
50%
60%
% o
f AAE
P M
embe
rs n
ot R
enew
ing
M
embe
rshi
p af
ter F
ive
Year
s
Graduation Year
AAEP Membership Attrition by Graduation Year, 2000-2012
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Of the Equine respondents who were currently not in equine medicine, and reported how many
years they worked as an equine veterinarian, 67.4 percent were in the equine profession from
zero to five years after graduation, 14.6 percent six to 10 years, 5.6 percent 11-15 years, and
13.3 percent 16 years or more (Figure 50).
Figure 50: Distribution of Equine Respondents Leaving the Equine Profession by Timeframe of Departure
When the respondents who reported leaving the equine veterinary sector and who are not
currently practicing in equine medicine are analyzed by graduation year, 100 percent of
respondents who graduated within the last five years obviously did so within five years of
graduation, followed by 91.3 percent from 2007-2011, and 27.8 percent from 1987-1996
(Figure 51). An additional 18 respondents who graduated prior to 1987 reported leaving equine
practice within five years of graduation.
67.4%
14.6%5.6%
11.2%1.1%%
of R
espo
nden
ts
Years after Graduation
Distribution of Equine Respondents Leaving the Equine Profession by Timeframe of Departure (n=89)
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Figure 51: Distribution of Equine Respondents Who Reported Leaving the Equine Profession within Five Years after Graduation by Graduation Year
100.0%91.3%
56.3%
27.8%
45.5%57.1%
2012-2016(n=15)
2007-2011(n=23)
1997-2006(n=16)
1987-1996(n=18)
1977-1986(n=11)
1967-1976(n=7)
% o
f Res
pond
ents
Graduation Year
Distribution of Equine Respondents Who Reported Leaving the Equine Profession within Five Years after Graduation by
Graduation Year
Left equine 5 years or prior
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Factors That Are Significant in Explaining the Population of Veterinarians Who Have Left the
Equine Profession within Five Years of Entering the Profession After Graduation
A binary logit model identified factors associated with a veterinarian who had left the equine
veterinary profession within five years of entering after graduation. A binary logit measures the
relationship between the variable of interest (dependent variable) and the factors
(independent variables) hypothesized to affect the variable of interest. In the binary logistic
regression, however, the dependent variable has only two values (1=yes, 0=no) and the
relationship measured is the probability of the dependent variable occurring when the factor
occurs. The dependent variable taking on the value of 1 is veterinarians who left equine
medicine within five years of entering the equine veterinary profession after veterinary school
graduation; the variable is 0 if they did not leave equine medicine within five years but left after
five years of entering the equine veterinary profession after graduation.
Independent variables used to identify factors associated with a veterinarian who had left the
equine veterinary profession within five years of entering after graduation included year of
graduation, gender, board certification, residency and internship participation, education level,
public practice, and education preparation.
In Table 25, the coefficients are used to calculate the probability of an individual respondent
falling into a specific category (left equine veterinary practice within five years or left equine
veterinary practice after five years of veterinary graduation). The main condition is determined
through identifying whether the coefficient is positive or negative. This will indicate the
direction of the relationship (i.e., negative is less likely to have left the equine veterinary
profession within five years and positive is more likely to have left the equine veterinary
profession within five years).
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Variables that significantly contribute to predictive ability of the model would have a p-value of
.10 or less in the column labeled “Sig.” Variables that are significant at the 10, 5 and 1 percent
level are reported in explaining the factors affecting leaving the equine veterinary profession
within five years. The “Odds Ratio” column is the probability of having left assigned to each of
the independent variables, and is defined as “the change in odds of being in one of the
categories of outcome (left equine veterinary profession within five years or did not leave
equine veterinary profession within five years but left after five years post graduation) when
the value of one of the independent variables (predictors) increases by one point.”18 To
interpret the odds ratio, the odds ratio value is subtracted by one to obtain the likelihood of the
event occurring.
Results show that for Equine respondents who participated in an internship compared to those
who did not participate in an internship, the odds of having left equine medicine within five
years versus having left equine medicine after five years was 5.87 times greater, given the other
variables are held constant in the model; for a respondent who is currently in public practice
compared to private practice, the odds of having left equine medicine within five years versus
having left equine medicine after five years is 35.57 times greater, given the other variables are
held constant in the model. For each additional year since graduation, the odds of having left
equine medicine within five years versus having left equine medicine after five years is .11
times lower, given the other variables are held constant in the model.
18 Barbara G. Tabachnick and Linda S. Fidell. Using Multivariate Statistics, 6th Edition (New York City, New York: Pearson, 2013), pg.8.
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Table 25: Factors That Are Significant in Explaining the Population of Veterinarians Who Have Left the Equine Profession within Five Years of Entering the Profession After Graduation
Equine Coefficient Std. Error Sig. Odd Ratio
Gender (Female=1) 0.306 1.038 0.77 1.36 Graduation Year -0.113 0.048 0.02** 0.89 Board Certified (Yes=1) -0.304 1.728 0.86 0.74 Residency (Yes=1) -2.256 1.791 0.21 0.10 Bachelor’s (baseline) Omitted Ph.D. -0.384 2.252 0.87 0.68 Master’s 0.464 1.797 0.80 1.59 Education Preparation (5=Extremely well/1=Not well at all) 0.560 0.815 0.49 1.75 Internship (Yes=1) 1.770 0.912 0.05* 5.87 Public Practice (Yes=1) 3.572 1.733 0.04** 35.57 Constant -0.431 3.150 0.89 0.65
Observations 60
Pseudo R-Square 0.3869
***, **, and * indicate significance at the 1 percent, 5 percent and 10 percent levels, respectively
Note: DVM only was removed because the variable did not permit estimation.
3.6.7 New Veterinarian Starting Salaries
From 2001 through 2017, the mean starting salary for new graduate veterinarians increased
from just under $40,000 to more than $60,000, according to the AVMA Senior Survey. These
numbers are inclusive of those finding full-time employment along with those pursuing
internships, residencies and advanced education (Figure 52). Since 2009, private practice has
offered the highest starting salaries. It was not until the 2007-2009 financial crisis that salaries
in public practice began trailing behind. Prior to that, salaries of new veterinarians in public
practice and private practice were generally equivalent. The data seem to show that the effect
of the recession on state and federal budgets has had a larger impact on public practice
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incomes than the impact of the recession on private practice incomes. Both are below their
long-term trend but following a similar direction in terms of growth.
Figure 52: Mean Starting Salaries of New Veterinarians 19
19 Source: AVMA Senior Survey, 2001-2017
$-
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
Star
ting
Sala
ry ($
)
Graduation Year
Mean Starting Salaries of New Veterinarians
ALL
Public Practice
Private Practice
Advanced Education
Internships
Residencies
Internships/Residencies/Advanced Education
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Although starting salaries among new veterinarians in private practice have been on a steady
incline, new veterinarians pursuing employment in the equine industry have consistently
experienced the lowest starting salaries (Figure 53). Internship salaries are not included in this
analysis of starting salaries.
Figure 53: Mean Starting Salaries of New Veterinarians — Private Practice 20
20 Source: AVMA Senior Survey, 2001-2017
$-
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
Star
ting
Sala
ry ($
)
Graduation Year
Mean Starting Salaries of New Veterinarians — Private Practice
Food animal practice(exclusive)
Food animal practice(predominant)
Mixed practice
Companion animal practice(predominant)
Companion animal practice(exclusive)
Equine practice
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Factors Affecting Starting Salaries of New Veterinarians
Using respondents from the 2001-2016 AVMA Senior Survey(s) to explain the factors affecting
the variation in starting salaries after graduation from veterinary school, a multiple linear
regression was used to determine factors significant in explaining the variation. Two models are
presented: a new veterinarian model specific to respondents who entered full-time equine
veterinary practice, and a second model that includes all new veterinarian respondents who are
working full-time. Variables that are significant at the 10, 5, and 1 percent level are reported in
explaining the factors affecting new veterinarian starting salaries. The main factors under
observation were year of graduation, age, gender, veterinary educational debt, additional
degrees held, participation in an internship and residency, work region, and a respondent’s first
veterinary position.
The coefficient in Table 26 indicates the dollar value impact of the corresponding variable on
starting salaries of new veterinarians. For instance, starting with a constant of $52,353.90 of
new equine veterinarian respondents, the value of coefficients (multiplied by the value of the
factor) is added. That is, a new veterinarian who graduated in 2016 would have had estimated
mean starting salary of $62,227.50 ($52,353.90 plus 16 times 617.10), holding all else constant.
The final column labeled “Sig.” represents the significant variables. These variables, also known
as p-values, are such that for a “sig” less than 0.10, the coefficient is statistically different from
“0.” For instance, for new equine veterinarian respondents who went to school in Region 0, the
p-value is 0.00; this means it is statistically significantly different from the baseline, Region 921.
The following factors were statistically significant in explaining the variation in new equine
veterinarian respondent starting salaries, at the 10 percent level of significance or less: year of
21 Baseline variables are used for comparison to avoid statistical errors.
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graduation, gender, anticipated work hours per week, student veterinary debt, master’s
degree, Region 0 and Region 8.
The following factors were statistically significant in explaining the variation in all new
veterinarian respondents at the 10 percent level of significance or less: year of graduation,
gender, anticpated work hours per week, student veterinary debt, Regions 1 – 8, and all first
veterinary positions, excluding “other veterinary employment.”
The coefficient for gender, $5,734.89, indicates that on average, new equine veterinarian
female respondents receive about $6,000 less in starting salary than new equine veterinarian
male respondents.
The coefficient for Region 0, -$9,774.93, indicates that on average, new equine veterinarian
respondents who work in Region 0 earn about $9,700 less than respondents who work in
Region 9, the baseline variable ($2,606.24 less for the new veterinarian respondent sample).
The factors that were included in this model produced an adjusted R-square of 0.1836 in the
new equine veterinarian model, and .4342 in the whole new veterinarian model. This indicates
that the inclusion of all these factors was able to explain 18 percent and 43 percent of the
variation between the individually reported starting salaries and the estimated mean starting
salary for all new graduates between 2001 and 2016. Thus, there are important variables that
determine starting salaries that have not been included, and are due to other unobservable
factors.
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Table 26: Factors Affecting Starting Salaries of New Veterinarians
New Equine Veterinarian Coefficient Std. Error Sig.
Graduation Year 617.10 132.39 0.00*** Age 13.40 161.25 0.93 Gender (Female=0) 5734.89 1233.54 0.00*** Anticipated work hours per week -334.38 37.96 0.00*** DVM Debt 0.03 0.01 0.00*** Admitted before degree was completed 2005.94 1592.84 0.21 Bachelor’s (baseline) Omitted Master’s 5360.99 2188.49 0.02** Ph.D. 3595.66 7974.52 0.65 Other professional degree -787.10 6232.57 0.90 Other degree -2854.30 4963.53 0.57 Region 0 -9774.93 2703.77 0.00*** Region 1 1130.33 2411.78 0.64 Region 2 -2209.42 2103.87 0.29 Region 3 -3309.49 2021.47 0.10* Region 4 667.46 1991.48 0.74 Region 5 -2071.49 2717.04 0.45 Region 6 1192.20 4247.58 0.78 Region 7 -2077.34 2009.44 0.30 Region 8 -6322.28 2417.60 0.01*** Region 9 (baseline) Omitted Constant 52353.90 5414.21 0.00***
Observations 693
Adjusted R-Square 0.1836
***, **, and * indicate significance at the 1 percent, 5 percent and 10 percent levels, respectively
New Veterinarian Coefficient Std. Error Sig.
Graduation Year 1759.95 23.41 0.00*** Age 32.36 30.00 0.28 Gender (Female=0) 3708.77 235.34 0.00*** Anticipated work hours per week -190.56 11.89 0.00*** DVM Debt 0.01 0.00 0.00***
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Admitted before degree was completed -254.79 308.66 0.41 Bachelor’s (baseline) Omitted Master’s 511.34 426.82 0.23 Ph.D. -823.32 1413.77 0.56 Other professional degree 1945.18 1871.19 0.30 Other degree -1247.49 1361.03 0.36 Region 0 -2606.24 554.15 0.00*** Region 1 -1193.64 509.04 0.02** Region 2 -2860.88 437.00 0.00*** Region 3 -4020.25 418.31 0.00*** Region 4 -4165.31 440.32 0.00*** Region 5 -5414.38 475.57 0.00*** Region 6 -5031.69 458.23 0.00*** Region 7 -1952.50 428.48 0.00*** Region 8 -837.33 465.22 0.07* Region 9 (baseline) Omitted First Position - Food Animal (exclusive) 1276.97 577.30 0.03** First Position - Food Animal (predominant) -3045.33 544.47 0.00*** First Position - Mixed Animal -4625.78 301.26 0.00*** First Position - Companion Animal (exclusive) (baseline)
Omitted
First Position – Companion Animal (predominant) -1437.04 310.21 0.00*** First Position - Equine -18386.44 527.29 0.00*** First Position - Federal Government -5829.46 1331.48 0.00*** First Position - Uniformed Services -2721.73 643.77 0.00*** First Position - University/College -27973.47 1447.48 0.00*** First Position - State/Local Government -10610.42 2910.19 0.00*** First Position - Industry/Commercial 9195.61 1701.08 0.00*** First Position - Not-for-profit -9018.46 1378.51 0.00*** First Position - Other veterinary employment -1187.49 2218.39 0.59 Constant 55733.47 1093.41 0.00*** Observations 14,914 Adjusted R-Square 0.4342
***, **, and * indicate significance at the 1 percent, 5 percent and 10 percent levels, respectively
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3.7 EDUCATIONAL DEBT OF NEW VETERINARIANS
Since 2005, the gap between student debt and professional income has widened sharply. The
rapid and persistent expansion of this debt-to-income ratio for new veterinarians represents a
major challenge for the entire veterinary profession and is inclusive of the equine profession.
Figure 54 shows the increase in educational debt load of new graduates in the equine
veterinary profession. Using the Consumer Price Index (CPI) by the Bureau of Labor Statistics,
the debt was adjusted for inflation to current dollars. Over a 15-year period, real mean debt of
new veterinarians in fields other than equine has more than doubled – from $70,726 in 2001 to
$142,732 in 2016, a difference of $75,372. New equine veterinarians’ real mean debt has risen
from $90,670 to $131,325.
Figure 54: Real Mean Debt for New Graduates in the Equine Profession vs. All Other Veterinary Fields
This section looks at summary statistics and an analysis of veterinary educational debt to
determine whether significant differences in mean veterinary educational debt exist among
different demographics when comparing Equine respondents to AVMA respondents. The mean
$90,670 $131,325
$70,726
$142,732
$-
$50,000
$100,000
$150,000
$200,000
2001 2003 2005 2007 2009 2011 2013 2015Amou
nt o
f DVM
Deb
t ($)
Graduation Year
Real Mean Debt for New Graduates in the Equine Profession vs. All Other Veterinary Fields (n=751)
Equine Other Types
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data for comparable groups (e.g., mean veterinary educational debt for men vs. mean
veterinary educational debt for women) were evaluated using t-statistics to test whether or not
differences observed are statistically significant. The demographic factors considered are
number of years since DVM graduation, level of education, internship and residency
participation, board certification, gender, type of employment, location, practice ownership,
type of community, equine sector, and size of community. For each sample, the mean and the
standard deviation of veterinary educational debt, as well as the first, the second, and the third
quartiles are presented. In addition, data were analyzed using a multiple regression model to
determine factors affecting veterinary educational debt.
3.7.1 Summary Statistics
More than 58 percent of Equine respondents (AVMA: 58.4 percent) had no educational debt
prior to veterinary school, 30.3 percent had under $25,000 (AVMA: 30.1 percent) and 11.2
percent had more than $25,000 in educational debt (AVMA: 11.5 percent).
The distribution of respondents’ pre-veterinary educational debt by gender and graduation year
is presented in Figures 55 and Figure 56. Equine and AVMA respondents had almost identical
distributions in all figures. More than 94 percent of the male Equine respondents (AVMA Males:
91.4 percent) had pre-veterinary debt under $25,000, compared to 85.3 percent of the females
(AVMA Females: 87.4 percent). A higher percentage of respondents who graduated after 1997
in both the Equine and AVMA samples reported pre-veterinary school educational debt over
$25,000 compared to the respondents who graduated prior to 1997.
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Figure 55: Distribution of Equine and AVMA Respondents’ Pre-Veterinary Educational Debt by Gender
61.3%
33.1%
3.5% 2.1%
$0 $1-$25,000 $25,001-$50,000 $50,001 +
% o
f Res
pond
ents
Pre-Veterinary Debt ($)
Distribution of Respondents' Pre-Veterinary Educational Debt by Gender
Equine - Male (n=287) Equine - Female (n=470)
AVMA - Male (n=521) AVMA - Female (n=1,363)
2012-2016
2007-2011
1997-2006
1987-1996
1977-1986
1967-1976
1966or
prior$50,001 + 6.1%4.6%3.8%0.9%0.0%0.0%0.0%$25,001-$50,000 11.6%9.2%10.7%5.3%1.0%0.0%0.0%$1-$25,000 28.8%28.9%26.7%38.9%34.3%30.4%0.0%$0 53.5%57.2%58.8%54.9%64.7%69.6%100.0%
0.0%20.0%40.0%60.0%80.0%
100.0%120.0%
% o
f Res
pond
ents
Graduation Year
Distribution of Equine Respondents Pre-Veterinary Educational Debt by Graduation Year
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Figure 56: Distribution of Equine and AVMA Respondents’ Pre-Veterinary Educational Debt by Graduation Year
More than two-thirds (70.8 percent) of Equine respondents incurred debt from their veterinary
medical education (AVMA: 79.2 percent). Table 27 shows the mean student debt from post-
secondary education. Equine respondents had, on average, student debt of $92,918 compared
to AVMA respondents who reported an average of $114,202.
Table 27: Distribution of Equine and AVMA Respondents’ Mean Student Debt
Obs. Mean Std. Dev 1st Quartile Median 2nd Quartile
Equine 739 92,918 82,524 25,000 71,000 140,000 AVMA 1,902 114,202 97,005 40,000 100,000 160,000
2012-2016
2007-2011
1997-2006
1987-1996
1977-1986
1967-1976
1966or
prior$50,001 + 6.6%3.0%3.4%1.1%1.6%0.0%0.0%$25,001-$50,000 12.3%9.8%6.7%4.1%0.8%2.2%0.0%$1-$25,000 27.1%30.8%29.2%41.9%26.8%19.6%0.0%$0 53.9%56.3%60.7%52.8%70.7%78.3%100.0%
0.0%20.0%40.0%60.0%80.0%
100.0%120.0%
% o
f Res
pond
ents
Graduation Year
Distribution of AVMA Respondents Pre-Veterinary Educational Debt by Graduation Year
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53.5 percent of Equine respondents and 62.5 percent of AVMA respondents reported that they
currently owe payments on their veterinary educational debt. Recent graduates may have a
grace period in which they do not have to make payments. This grace period is usually six
months, but borrowers may start paying off loans as soon as they graduate. The longer a
respondent has been out of veterinary school the longer they have been paying off their
educational debt. As the individual pays off debt, the loan balance decreases until it is
eventually retired. On average, Equine respondents have been actively repaying their student
loan debt for five years. AVMA respondents on average have been repaying for six years. The
respondents who have already paid off their debt took, on average, 7.6 years to do so (AVMA:
7.2 percent).
Figure 57 presents the percentage of annual compensation used to service respondents’ debt.
In the Equine sample, 74.6 percent reported 0 percent-20 percent of their paycheck goes to
servicing their debt compared to 98.6 percent of the AVMA sample. Among the Equine
respondents, 25.4 percent reported that they apply more than 21 percent of their annual
compensation to service their debt compared to 1.4 percent of AVMA respondents. More than
10 percent of Equine respondents reported that in excess of 30 percent of their compensation
is used to service their education debt.
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Figure 57: Distribution of Equine and AVMA Respondents’ Gross Annual Compensation that Debt Repayment Requires
On average, female Equine respondents reported that they use 18.2 percent of their annual
compensation to service their student debt, while males reported they use an average of 14.1
percent (AVMA females: 15.8 percent; AVMA males: 14.9 percent). Table 28 illustrates the
effect of graduation year. Equine respondents who graduated within the past 10 years
reported a mean of nearly 20 percent of their annual compensation going toward educational
loan repayment (AVMA: approximately 18 percent). Respondents who graduated prior to 2006
reported they spent on average 10 percent or less on debt repayment.
4.3%
20.0%26.8% 23.5%
12.2% 13.2%
0% 1 - 5% 6 - 10% 11 - 20% 21 - 30% 30% or more
% o
f Res
pond
ents
% of Compensation
Distribution of Equine and AVMA Respondents’ Gross Annual Compensation that Debt Repayment Requires
Equine (n=370) AVMA (n=709)
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Table 28: Percentage of Equine and AVMA Respondents’ Annual Compensation Used to Service Student Loan Debt by Graduation Year22
Equine - Graduation Year Obs. Mean Std. Dev. Min Max
2012-2016 167 19.97 20.55 0 100 2007-2011 113 20.15 18.22 0.5 100 1997-2006 73 9.56 12.09 0 89 1987-1996 11 4.16 3.15 0 10
AVMA - Graduation Year Obs. Mean Std. Dev. Min Max
2012-2016 425 18.53 16.76 0 90 2007-2011 318 17.60 15.21 0 90 1997-2006 320 9.68 10.77 0 89 1987-1996 16 8.15 7.40 0.2 23
3.7.2 Difference in Student Debt for Selected Characteristics
Differences in mean debt at graduation from veterinary school by number of years since DVM
graduation, level of education, internship and residency participation, board certificate, gender,
type of employment, location, practice ownership, type of community, equine sector, and size
of community are reported. Means, medians, standard deviation and debt by quartile for each
variable were calculated first. Then a significance test was used to determine if the relationship
between debt and each factor is statistically significant. A significance test with a p-value <.01
means there is 99 percent confidence that there exists a relationship between the response and
the factor, while a p-value between >.01 and <.05 means there is 95 percent confidence that
there exists a relationship between the response and the factor, and a p-value between >.05
and <.10 means there is a 90 percent confidence that there exists a relationship between the
response and the factor. A p-value greater than .10 is not significant.
22 AVMA graduation year category 1977-1986 was omitted because the number of observations did not permit estimation.
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3.7.2.1 Educational Debt by Number of Years since DVM Graduation
Educational debt reported by Equine and AVMA respondents doubled over the past two
decades. The average debt among Equine respondents who graduated more than 50 years ago
was $6,938. In contrast, average debt was $125,374 for Equine respondents who graduated 6-
10 years ago, and $168,710 for those who graduated within the last five years (Table 29).
Analysis shows that the difference in mean student debt between Equine respondents of
different graduation years is statistically significant (p-value < 0.001). The difference in mean
student debt in AVMA respondents is statistically significant as well (p-value < 0.001).
Table 29: Mean Student Debt with Respect to the Number of Years since Graduation
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
0-5 years 197 $168,710 $85,856 $110,000 $158,000 $215,000 6-10 years 152 $125,374 $66,523 $79,000 $120,000 $162,500 11-20 years 128 $79,426 $44,740 $50,000 $75,000 $100,000 21-30 years 111 $42,879 $35,526 $22,000 $35,000 $56,000 31-40 years 94 $21,794 $17,531 $10,000 $20,000 $27,000 41-50 years 40 $13,743 $18,085 $4,000 $8,500 $11,000 51 or more years
8 $6,938 $6,026 $3,500 $5,000 $9,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
0-5 years 509 $183,902 $119,257 $112,000 $167,000 $250,000 6-10 years 429 $143,735 $76,192 $100,000 $136,000 $180,000 11-20 years 503 $89,774 $52,159 $53,000 $80,000 $115,000 21-30 years 259 $37,731 $27,604 $17,000 $30,000 $49,000 31-40 years 116 $24,079 $31,308 $10,000 $19,000 $24,000 41-50 years 45 $15,367 $36,901 $3,500 $10,000 $13,500 51 or more years
16 $11,759 $26,650 $1,850 $5,000 $8,000
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3.7.2.2 Educational Debt by Level of Education
The difference in mean student debt by level of education in Equine respondents was
statistically significant with respect to the degree obtained in addition to the DVM degree (p-
value < 0.001). Equine respondents with a DVM degree alone accrued an average of $54,197 of
educational debt, while those respondents with an undergraduate degree in addition to a DVM
degree accrued $106,114; and those with a graduate degree had on average of $82,556 of debt
(Table 30). The difference in mean student debt between AVMA respondents was also
statistically significant (p-value < 0.001). On average, AVMA respondents had a higher mean
educational debt than Equine respondents, including those with a DVM degree only and those
with an additional degree.
Table 30: Mean Student Debt with Respect to Additional Degree
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 75 $54,197 $56,360 $11,000 $30,000 $80,000 DVM + Undergraduate Degree
510 $106,114 $84,884 $35,000 $85,500 $155,000
DVM + Graduate Degree 154 $82,556 $75,050 $20,000 $63,000 $120,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 143 $91,202 $82,793 $30,000 $69,000 $130,000 DVM + Undergraduate Degree
1,336 $121,965 $89,915 $50,000 $105,000 $170,000
DVM + Graduate Degree
378 $96,631 $120,567 $25,000 $65,000 $136,000
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3.7.2.3 Educational Debt by Internship Participation
Equine respondents who completed an internship program reported an average student debt
higher than those who did not complete an internship. This difference is statistically significant
(p-value < 0.001). The difference in the AVMA respondents is also statistically significant (p-
value = 0.078). Equine respondents reported a higher difference of mean educational debt
between those who participated in internships and those who did not ($39,664) than did AVMA
respondents (mean debt difference of $8,915) (Table 31). Notably, Equine respondents who
participated in internships reported a mean educational debt of $109,865, a lower figure than
the mean reported by AVMA respondents without internship ($112,008).
Table 31: Mean Student Debt with Respect to Internship Participation
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 326 $70,201 $74,081 $16,000 $41,000 $110,000 DVM + Internship 437 $109,865 $84,484 $40,000 $96,000 $160,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 1,401 $112,008 $100,615 $40,000 $95,000 $153,000 DVM + Internship 497 $120,923 $85,804 $50,000 $100,000 $174,000
3.7.2.4 Educational Debt by Residency Participation
The difference in mean student debt for those Equine respondents pursuing residency
programs compared to those with only a DVM/VMD degree is statistically significant (P-value <
0.001). The difference in mean student debt within the AVMA respondents is also statistically
significant (P-value <0.001). For both samples, the mean student debt of respondents
participating in a residency is lower than for respondents not completing a residency (Table 32).
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Table 32: Mean Student Debt with Respect to Residency Participation
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 600 $100,215 $84,751 $30,000 $80,000 $149,500 DVM - Residency 139 $77,465 $66,733 $22,000 $60,000 $110,000
3.7.2.5 Educational Debt by Board Certificate
Among both the Equine and AVMA respondents who completed a residency, the difference in
mean student debt between those who achieved board certification versus those who did not
was statistically significant (P-value <0.001). Within both the Equine and AVMA samples the
mean student debt was lower for those who became board certified (Table 33).
Table 33: Mean Student Debt with Respect to Board Certificate
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 638 $98,467 $85,092 $27,000 $80,000 $145,000 DVM + Board certificate 125 $64,598 $60,722 $17,500 $45,000 $100,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 1,636 $119,897 $99,347 $45,750 $100,000 $165,000 DVM + Board certificate 262 $79,328 $71,927 $28,000 $55,500 $110,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
DVM 1,661 $118,797 $99,456 $45,000 $100,000 $165,000 DVM - Residency 238 $83,262 $70,573 $30,000 $60,250 $120,000
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3.7.2.6 Educational Debt by Gender
The difference in mean student debt between male and female Equine respondents was
statistically significant (P-value <0.001). The average student debt reported by female Equine
respondents was $117,036 versus $53,722 reported by males (Table 34). The difference in
mean educational debt between male and female AVMA respondents was also statistically
significant (P-value <0.001). While the debt means reported by Equine respondents fall below
those reported by the AVMA sample, the difference between male and female Equine
respondents’ debt is $63,314, while the difference between male and female AVMA
respondents’ debt is $37,091. It should be noted that the mean years of veterinary experience
of the male equine respondent cohort was 29 years (AVMA: 23 years) and the mean years of
veterinary experience of the female cohort was 12 years (AVMA: 11 years). Data on educational
debt by years since graduation can be found in Table 29.
Table 34: Mean Student Debt with Respect to Gender
Equine Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
Female 472 $117,036 $84,067 $55,000 $101,500 $170,000 Male 289 $53,722 $62,895 $10,000 $30,000 $70,000
AVMA Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
Female 1,356 $124,807 $100,126 $50,000 $109,000 $170,000 Male 513 $87,716 $84,013 $22,000 $60,500 $125,000
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3.7.2.7 Educational Debt by Type of Employment
The difference in mean educational debt across veterinarians of different employment types
among both Equine and AVMA respondents was statistically significant (P-value <0.001). The
highest mean debt levels were reported by those respondents in advanced education (Equine:
$175,724; AVMA: $162,589) (Table 35).
Table 35: Mean Student Debt with Respect to Type of Employment23
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Equine Practice 387 $96,272 $78,949 $30,000 $77,000 $140,000 Mixed Animal Practice 76 $94,894 $76,187 $32,000 $96,500 $139,250 College/University 52 $55,154 $50,292 $16,000 $40,000 $92,500 Companion Animal Practice
35 $105,186 $94,697 $25,000 $85,000 $130,000
Advanced Education 29 $175,724 $97,420 $100,000 $155,000 $250,000 Food Animal Practice 13 $62,923 $55,756 $20,000 $38,000 $97,000 Other Veterinary Employment
6 $136,833 $60,572 $67,000 $152,000 $190,000
23 Industry/Commercial Organization and Not-for-profit in the Equine sample were omitted because the number of observations did not permit estimation.
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AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Companion Animal Practice
1,149 $124,546 $103,850 $50,000 $105,000 $170,000
College/University 122 $84,870 $68,376 $35,000 $68,500 $120,000 Mixed Animal Practice
95 $106,207 $73,248 $50,000 $105,000 $150,000
Equine Practice 65 $121,662 $88,677 $56,000 $96,000 $170,000 Industry/Commercial Organization
57 $85,221 $72,318 $39,000 $60,000 $120,000
Not-for-profit 56 $106,741 $97,310 $35,000 $80,000 $150,000 Federal Government 45 $97,870 $84,630 $30,000 $95,000 $140,000 Advanced Education 45 $162,589 $92,151 $95,000 $160,000 $206,000 Food Animal Practice 43 $111,477 $72,356 $48,000 $110,000 $160,000 State/Local Government
28 $88,636 $72,681 $35,000 $75,000 $115,500
Uniformed Services 10 $77,800 $36,660 $62,000 $77,500 $110,000 Non-Veterinary Employment
7 $92,286 $56,603 $32,000 $125,000 $141,000
Other Veterinary Employment
57 $109,258 $99,873 $20,000 $85,000 $170,000
3.7.2.8 Educational Debt by Work Region
The difference in mean educational debt reported by Equine respondents with respect to
region was not statistically significant (P-value = 0.173). The difference in mean student debt by
region reported by AVMA respondents was statistically significant (P-value = 0.001). Equine
respondents from Region 0 reported the highest average educational debt ($121,622). In
contrast, Equine respondents from Region 6 reported the smallest mean debt ($81,183) (Table
36). Region 0 was also the region with the highest average educational debt ($138,415)
reported by AVMA respondents, with respondents from Region 7 reporting the smallest
amount ($96,298).
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Table 36: Mean Student Debt with Respect to Work Region24
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Region 0 49 $121,622 $91,798 $40,000 $109,000 $189,000 Region 1 59 $112,500 $101,062 $35,000 $70,000 $179,000 Region 2 63 $92,195 $77,151 $25,000 $85,000 $130,000 Region 3 78 $117,628 $99,591 $32,000 $90,000 $182,000 Region 4 65 $87,948 $79,089 $22,000 $60,000 $150,000 Region 5 47 $93,617 $76,421 $30,000 $80,000 $139,000 Region 6 47 $81,183 $76,138 $25,000 $60,000 $120,000 Region 7 63 $99,382 $68,524 $50,000 $100,000 $140,000 Region 8 72 $98,514 $80,835 $35,000 $73,250 $141,000 Region 9 88 $96,924 $74,876 $30,000 $85,000 $140,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Region 0 130 $138,415 $91,107 $65,000 $130,000 $200,000 Region 1 151 $126,731 $91,053 $47,000 $118,500 $180,000 Region 2 214 $109,083 $88,839 $40,000 $95,000 $157,000 Region 3 194 $128,904 $91,802 $57,000 $114,500 $165,000 Region 4 168 $115,492 $98,385 $50,000 $99,000 $160,000 Region 5 140 $116,479 $80,324 $50,000 $100,000 $160,000 Region 6 162 $96,372 $69,133 $35,000 $84,000 $145,000 Region 7 165 $96,298 $82,210 $30,000 $80,000 $140,000 Region 8 142 $126,563 $100,511 $49,000 $100,000 $200,000 Region 9 232 $128,417 $142,394 $47,500 $107,000 $170,000
3.7.2.9 Educational Debt by Practice Ownership
The difference in mean educational debt reported by Equine and AVMA respondents with
relation to practice ownership and years from graduation was statistically significant (p-value
24 Map of U.S. Regions, Figure 16.
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<0.001) (Table 37). Practice owners tended to have slightly higher debt levels than non-practice
owners when grouped by graduation year.
Table 37: Mean Student Debt with Respect to Practice Ownership by Years from Graduation 25
Equine - Practice Owner
Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 4 $178,750 $81,549 $119,500 $167,500 $238,000 6-10 years 37 $129,481 $63,525 $96,000 $120,000 $165,000 11-20 years 52 $81,356 $48,792 $53,000 $77,500 $95,500 21-30 years 61 $40,980 $38,830 $20,500 $35,000 $51,000 31-40 years 43 $24,035 $14,829 $13,000 $20,000 $30,000 41-50 years 16 $15,606 $17,449 $5,000 $9,500 $16,500
Equine - Non-Practice Owner
Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 86 $164,911 $85,647 $110,000 $149,500 $205,000 6-10 years 78 $125,987 $67,663 $78,000 $127,000 $170,000 11-20 years 35 $76,299 $36,702 $50,000 $70,000 $105,000 21-30 years 13 $44,431 $24,746 $28,000 $40,000 $47,000 31-40 years 7 $22,229 $26,822 $5,000 $15,000 $25,000
AVMA -Practice Owner
Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 10 $181,600 $82,986 $105,000 $162,000 $255,000 6-10 years 45 $144,900 $119,681 $95,000 $128,000 $155,000 11-20 years 109 $83,311 $49,590 $50,000 $76,000 $105,000 21-30 years 84 $39,086 $25,707 $20,500 $31,000 $47,625 31-40 years 50 $27,765 $42,166 $13,000 $20,000 $25,000 41-50 years 14 $10,471 $12,676 $3,000 $7,000 $10,000
25 Equine non-practice owners with 41-50 years and 51 or more years post-graduation and AVMA practice owners who graduated 51 or more years ago were omitted because the number of observations did not permit estimation.
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AVMA - Non-Practice Owner
Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 412 $183,132 $122,952 $112,500 $167,500 $245,000 6-10 years 285 $146,975 $70,567 $100,000 $140,000 $181,000 11-20 years 239 $96,627 $55,117 $60,000 $85,000 $125,000 21-30 years 88 $37,710 $30,515 $16,500 $30,000 $48,000 31-40 years 20 $20,920 $13,653 $10,000 $19,500 $28,500 41-50 years 4 $10,625 $2,810 $8,500 $11,000 $12,750
3.7.2.10 Educational Debt by Type of Community
The difference in mean educational debt reported by respondents with respect to the type of
community (or environment) in which a respondent lives was statistically significant in the
Equine sample (P-value =0.069) and statistically significant (P-value =0.001) in the AVMA
sample (Table 38).
Table 38: Mean Student Debt with Respect to Type of Community
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Rural 387 $86,550 $79,621 $22,000 $65,000 $126,500 Urban 70 $101,649 $84,731 $27,300 $90,000 $156,000 Suburban 301 $100,105 $85,357 $26,000 $80,000 $150,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Rural 529 $101,226 $88,160 $30,000 $85,000 $149,000 Urban 325 $125,579 $95,663 $45,000 $105,000 $185,000 Suburban 1,010 $118,065 $102,031 $45,000 $100,000 $161,000
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3.7.2.11 Educational Debt by Type of Equine Sector
The difference in mean educational debt reported by AAEP respondents working in disparate
equine sectors was not statistically significant (P-value =0.782). AAEP respondents in the
Western Performance sector disclosed the highest student debt, $115,692, followed by
respondents in the equine companion sector ($110,333) (Table 39).
Table 39: Mean Student Debt with Respect to Primary Equine Sector26
AAEP Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
General equine practice 249 $89,166 $75,527 $25,000 $70,000 $135,000 English performance 59 $85,525 $82,958 $35,000 $60,000 $109,000 Reproductive 21 $68,257 $77,792 $25,000 $32,600 $95,000 Racing - Thoroughbred 20 $87,975 $66,065 $28,500 $65,000 $142,000 Equine companion 18 $110,333 $93,194 $17,000 $114,000 $160,000 Western performance 13 $115,692 $62,569 $91,000 $110,000 $143,000 Ranch or working 7 $80,429 $76,162 $18,000 $50,000 $140,000 Racing - Quarter Horse 5 $99,000 $57,271 $80,000 $120,000 $125,000 Racing - Standardbred 5 $79,000 $85,029 $25,000 $30,000 $150,000
3.7.2.12 Educational Debt by Size of Community
The difference in mean educational debt reported by Equine respondents relative to the size of
the respondent’s community was not statistically significant
(P-value = 0.524), nor was it among AVMA respondents (P-value = 0.709). Respondents in the
Equine sample whose primary practice was based in a community of 500,000 or more residents
had the lowest average student debt ($81,947). Respondents in the AVMA sample with the
lowest reported average student debt were those whose practice is in a community of fewer
than 2,500 residents ($110,498) (Table 40).
26 Gaited breeds was omitted because the number of observations did not permit estimation.
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Table 40: Mean Student Debt with Respect to Size of Community
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Less than 2,500 residents
35 $93,186 $72,515 $35,000 $80,000 $140,000
2,500 to 49,999 residents
195 $98,028 $87,972 $25,000 $76,000 $140,000
50,000 to 499,999 residents
158 $89,789 $70,647 $35,000 $72,000 $137,000
500,000 or more residents
62 $81,947 $72,981 $25,000 $60,000 $117,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Less than 2,500 residents
69 $110,498 $79,725 $48,000 $100,000 $160,000
2,500 to 49,999 residents
533 $124,438 $115,102 $48,000 $110,000 $170,000
50,000 to 499,999 residents
510 $121,493 $88,112 $50,000 $100,000 $167,000
500,000 or more residents
265 $124,987 $96,213 $46,000 $108,000 $179,000
3.7.3 Factors Affecting Veterinary Educational Student Debt upon Graduation
Using respondents from the 2001-2016 AVMA Senior Survey(s) to explain the factors affecting
the variation in veterinary educational student debt at graduation, a multiple linear regression
was used to determine the surveyed factors significant in explaining the variation. Variables
significant at the 10, 5 and 1 percent level are reported in explaining the factors affecting
student debt. The main factors under observation were age, graduation year, gender, and the
region in which the school is located.
The coefficient in Table 41 indicates the dollar value impact of the corresponding variable on
student debt. Starting with a constant of $ 146,527.90, for instance, the value of coefficients
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(multiplied by the value of the factor) is added. That is, a new equine veterinarian respondent
who went to school in Region 2 would have had estimated student debt of $101,204.73
($146,527.90 minus $45,323.17).
The final column labeled “Sig.” represents the significant variables. These variables, also known
as p-values, are such that for a “Sig.” less than 0.10, the coefficient is statistically different from
“0.” For new equine veterinarian respondents who went to school in Region 4, for example, the
p-value is 0.03; this means it is statistically significantly different from the baseline, Region 327.
The following factors were statistically significant in explaining the variation in veterinary
educational student debt of new equine veterinarian respondents at the time of graduation, at
the 10 percent level of significance or less: graduation year, and attended school in Region 2,
Region 4, Region 5, Region 7 and Region 9.
The following factors were statistically significant in explaining the variation in veterinary
educational student debt of all new veterinarian respondents at the 10 percent level of
significance or less: age, graduation year and attended school in Region 0, Region 2, Region 4,
Region 5, Region 6, Region 7, Region 8 and Region 9.
The coefficient for graduation year indicates that the average volume of veterinary educational
student debt declines with year of graduation by $4,828; in other words, respondents pay back,
on average, $4,828 of debt each year. The coefficent for attending a school in Region 7, -
$19,359, indicates that, on average, new equine veterinarian respondents who attended a
veterinary school in Region 7 have $19,359 less debt than respondents who attended school in
Region 3, the baseline variable. New veterinarian respondents in Region 7 on average had
$52,928 less debt than AVMA respondents in Region 3.
27 Baseline variables are used for comparison to avoid statistical errors.
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The factors that were included in this model produced an adjusted R-square of 0.4545 in the
new equine veterinarian sample and .3553 in the new veterinarian sample. This indicates that
the inclusion of all these factors was able to explain 46 percent and 36 percent of the variation
between the individually reported student debt and the estimated mean student debt. Thus,
there are important variables that determine starting salaries that have not been included, and
are due to other unobservable factors.
Table 41: Factors Affecting Educational Student Debt upon Graduation
New Equine Veterinarian Coefficient Std. Err. Sig.
Age 896.65 620.33 0.15 Graduation Year -4827.66 643.03 0.00*** Gender (Female=1) 3582.86 5638.79 0.53 Region of School 0 -7328.35 9833.71 0.46 Region of School 1 15670.46 11381.33 0.17 Region of School 2 -45323.17 10904.35 0.00*** Region of School 3 (baseline) Omitted Region of School 4 -19009.57 8476.01 0.03** Region of School 5 -20212.50 8845.80 0.02** Region of School 6 -12451.12 8297.49 0.13 Region of School 7 -19359.00 9183.31 0.04** Region of School 8 -14734.16 9312.46 0.11 Region of School 9 -15293.01 7952.82 0.06* Constant 146527.90 18311.14 0.00***
Observations 726
Adjusted R-Square
0.4545
***, **, and * indicate significance at the 1 percent, 5 percent and 10 percent levels, respectively
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New Veterinarian Coefficient Std. Err. Sig.
Age 1966.88 497.74 0.00*** Graduation Year -6630.5 511.99 0.00*** Gender (Female=1) 337.48 4310.24 0.94 Region of School 0 -25521.5 7999.53 0.00*** Region of School 1 -6086.77 9546.03 0.52 Region of School 2 -58648.8 8239.49 0.00*** Region of School 3 (baseline) Omitted Region of School 4 -27607.3 6333.52 0.00*** Region of School 5 -33258.6 6545.04 0.00*** Region of School 6 -31720.1 6599.29 0.00*** Region of School 7 -52928.1 7317.62 0.00*** Region of School 8 -17656.7 10361.27 0.09* Region of School 9 -20986.7 6760.04 0.00*** Constant 143236.9 15137.07 0.00***
Observations 1,840
Adjusted R-Square 0.3553
***, **, and * indicate significance at the 1 percent, 5 percent and 10 percent levels, respectively
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3.8 EXPECTATIONS BEFORE ENTERING PROFESSION
Respondents were asked how they felt about their work experiences based on their
expectations before they started working, and then asked about their satisfaction since
entering the veterinary profession. The questions pertained to the aspects of the veterinary
field in which they are employed, career development opportunities, relationship with
management, compensation and benefits, and the work environment.
A person with experience is defined as having had exposure to or involvement with a certain
event or subject. Satisfaction level reveals how a respondent feels about certain aspects of the
event or subject, and measures the individual’s perception of their experiences. Each queried
competency was ranked as to how well the average experience met expectations and the level
of satisfaction with the actual experience after the respondent had entered the veterinary
profession (Table 42).
Across both the Equine and AVMA samples respondents reported that their actual experiences
with opportunities to network were on average the same as they had expected prior to
entering the job market. The Equine respondents also reported that their expectations of
career development opportunities and management recognition of employee job performance
were met, and that their health care or medical benefits, feeling physically and psychologically
safe in the work environment, and the overall culture of the workplace on average exceeded
their expectations. AVMA respondents reported that their expectations of communication
between associates and owners, and of opportunities for variable pay were met, and that
career development opportunities, management recognition of employee job performance,
health care or medical benefits, feeling physically safe in the work environment, and the overall
culture of the work place exceeded their average expectations.
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Factors that were reported to be experienced at a lower level than expected by Equine
respondents included opportunities for variable pay and communication between associates
and owners. When comparing how experiences met expectations with the satisfaction with
experiences since working, the mean scores did not change much.
Table 42: Competency Scores by College Preparedness
Equine College Preparedness
Professional Satisfaction
N Mean Std. Dev.
N Mean Std. Dev. Career development opportunities for learning and professional growth
260 3.3 1.1
253 3.3 1.0
Opportunities to network with others to help in advancing one's career
260 3.2 1.1
253 3.2 1.0
Communication between associates and owners
259 2.9 1.2
259 2.8 1.2
Management recognition of employee job performance
260 2.6 1.1
259 2.6 1.0
Opportunities for variable pay 259 2.8 1.0
255 2.7 1.0 Health care or medical benefits 257 2.8 1.1
257 2.9 1.1
Feeling physically safe in the work environment
258 3.2 0.7
256 3.6 0.8
Feeling psychologically safe in the work environment
211 3.0 0.9
209 3.3 1.0
Overall culture of work place 258 3.1 1.1
255 3.2 1.1
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AVMA College Preparedness
Professional Satisfaction
N Mean Std. Dev.
N Mean Std. Dev. Career development opportunities for learning and professional growth
1,797 3.2 1.1
1,780 3.3 1.0
Opportunities to network with others to help in advancing one's career
1,796 3.2 1.0
1,778 3.2 1.0
Communication between associates and owners
1,774 2.9 1.1
1,773 2.9 1.0
Management recognition of employee job performance
1,773 2.6 1.1
1,772 2.7 1.0
Opportunities for variable pay 1,758 2.8 1.1
1,751 2.8 1.1 Health care or medical benefits 1,753 2.9 1.1
1,752 3.0 1.1
Feeling physically safe in the work environment
1,754 3.3 0.8
1,748 3.8 0.9
Overall culture of workplace 1,749 3.0 1.0
1,741 3.2 1.1
Note: 1=much worse than expected, 2=somewhat worse than expected, 3=the same as you
expected, 4=somewhat better than expected, 5=much better than expected
*The 2016 AVMA Census of Veterinarians did not ask respondents if they felt psychologically
safe in the work environment.
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3.9 KEY PERFORMANCE INDICATOR: DEBT-TO-INCOME RATIO (DIR) OF NEW VETERINARIANS
The debt-to-income ratio is an important measure of the economic performance of the market
for veterinary education. The DIR connects the market for education and the market for new
veterinarians. By definition, the DIR measures what percentage of debt is covered by annual
income. Although some economists suggest that a DIR of 1:1 may be the limit that should be
considered to guarantee personal financial sustainability, this best applies to non-professional
undergraduate degrees. Because the increases in income associated with experience are much
greater for those with professional degrees, especially graduate professional degrees, the level
of debt-to-income that can be serviced in professional fields without posing serious financial
stress is likely closer to 1.4:1.
The weighted (by gender) average28 DIR of new veterinarians who work full time in equine
medicine was 2.48 (median was 2.10) in the years 2000-2016. The weighted average DIR of all
new veterinarians working full time in the years 2000-2016 was 1.71 (median was 1.62)
(Table 43).
Table 43: Distribution of Weighted New Veterinarian Debt-to-Income Ratio29
Obs. Mean Std. Dev 1st Quartile Median 3rd Quartile
AVMA Equine 708 2.48 2.04 1.25 2.10 3.33 AVMA 15,049 1.71 1.25 .97 1.62 2.27
The average DIR of new veterinarians by graduation year is shown in Figure 58. In both samples,
the longer a respondent has been out of veterinary school the smaller the DIR he or she had.
28 A weighted average “refers to the mathematical practice of adjusting the components of an average to reflect the importance of certain characteristics.” Source: Merriam-Webster Dictionary https://www.merriam-webster.com/dictionary/weighted%20average 29 Source: AVMA Senior Survey, 2000-2016
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Figure 58: Mean Debt-to-Income Ratio of New AVMA Equine Veterinarians and All New AVMA Veterinarians by Graduation Year30
30 Source: AVMA Senior Survey, 2000-2016
0.00
1.00
2.00
3.00
4.00
Debt
to In
com
e Ra
tio
Graduation Year
Mean Debt-to-Income Ratio of New AVMA Equine Veterinarians by Graduation Year
Male (unweighted DIR) Female (unweighted DIR)
Gender Weighted (DIR)
0.000.501.001.502.002.50
Debt
To
Inco
me
Ratio
Graduation Year
Mean Debt-to-Income Ratio of All New AVMA Veterinarians by Graduation Year
Male (unweighted DIR) Female (unweighted DIR)
Gender Weighted (DIR)
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3.9.1 Factors Affecting Debt-to-Income Ratio
Using respondents from the 2001-2016 AVMA Senior Survey(s) to explain the factors affecting
the variation in the DIR, a multiple regression was used to investigate the surveyed factors
affecting the variation in the DIR for new veterinarians, both who are working full time in
equine medicine, and those who are working full time in veterinary medicine (both in a private
and public setting), including a starting annual income between $20,000 and $200,000. A
multiple regression assesses the relationship between the dependent variable and multiple
independent variables (explanatory variables).
The multiple regression was used to understand DIR as a function of graduation year, age,
gender, anticipated hours worked per week, additional degrees held, type of employment
(AVMA model), and veterinary school attended.
The coefficient in Table 44 indicates the impact of the corresponding variable on the DIR of new
veterinarians. New equine veterinarians who obtained a master’s degree along with their DVM
degree, for example, have a -.66 lower mean DIR than respondents with a bachelor’s degree
and a DVM degree.
The column labelled “Sig.” represents the significant variables. These variables, also known as
p-values, are such that for a “sig” less than 0.10, the coefficient is statistically different from
“0.” For instance, for new equine veterinarians who attended the University of Minnesota for
veterinary school, the p-value is 0.016; this means that statistically, it is significantly different
from the baseline, The Ohio State University.
As a baseline for comparison with the other variables in the respective groups, the following
factors were omitted from the model: The Ohio State University, bachelor’s degree, and
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working in an exclusive companion practice (AVMA model). Results from the regressions are
presented in Table 44.
The following factors were statistically significant in explaining the variation in the DIR of new
equine veterinarians, at a 10 percent level of significance or less: year of graduation, age,
gender, anticipated number work hours per week, obtained a master’s degree, and attended
Louisiana State University, Tufts University, University of Minnesota, Texas A&M, University of
Tennessee, North Carolina State University, or Western University of Health Sciences.
Some significant findings in the national DIR for new veterinarians include an average increase
in the DIR for graduation year, age, and anticipated work hours per week, as well as
respondents working in a predominantly companion animal practice, equine practice, state or
local government, college/university, or not-for-profit compared to respondents in an exclusive
companion animal practice. For respondents in food animal practices, uniformed services, and
industry/commercial organizations the DIR decreases on average compared to respondents in
an exclusive companion animal practice. In addition, the DIR, on average, decreases for
respondents who obtained a doctorate degree, male, and were admitted before degree was
completed.
The factors that were included in this model produced an adjusted R-square of 0.1454 in the
new equine veterinarian model and .1876 in the new veterinarian model. This indicates that the
inclusion of all these factors was able to explain 15 percent and 19 percent of the variation
between the individually reported DIR and the estimated mean DIR. Thus, there are important
variables that affect the DIR that have not been included, and are due to other unobservable
factors.
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Table 44: Factors Affecting Debt-to-Income Ratio
New Equine Veterinarian Coefficient Std. Error Sig.
Graduation Year 0.114 0.018 0.00*** Age 0.092 0.022 0.00*** Gender (Female=0) -0.386 0.175 0.03** Anticipated work hours per week 0.015 0.005 0.01*** Admitted before degree was completed -0.204 0.228 0.37 Bachelor’s (baseline) Omitted Master’s -0.660 0.307 0.03** Ph.D. 0.369 1.111 0.74 Other professional degree -0.608 0.882 0.49 Other degree 0.252 0.694 0.72 The Ohio State University (baseline) Omitted Auburn University -0.220 0.459 0.63 Tuskegee University 0.405 0.684 0.55 University of California-Davis -0.400 0.404 0.32 Colorado State University -0.286 0.371 0.44 University of Florida -0.627 0.491 0.20 University of Georgia -0.517 0.472 0.27 University of Illinois -0.524 0.484 0.28 Iowa State University 0.397 0.557 0.48 Kansas State University 0.289 0.446 0.52 Louisiana State University -0.852 0.512 0.10* Tufts University 0.957 0.484 0.05** Michigan State University 0.411 0.459 0.37 University of Minnesota 1.238 0.512 0.02** Mississippi State University -0.089 0.494 0.86 Purdue University -0.869 0.573 0.13 Cornell University 0.447 0.486 0.36 Oklahoma State University 0.305 0.411 0.46 University of Pennsylvania 0.141 0.523 0.79 Texas A&M University -0.771 0.374 0.04** Washington State University -0.508 0.512 0.32 University of Missouri-Columbia 0.338 0.839 0.69 Oregon State University -0.083 0.890 0.93 University of Tennessee -1.349 0.592 0.02** Virginia-Maryland College 0.067 0.384 0.86
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North Carolina State University -1.031 0.470 0.03** University of Wisconsin 0.634 0.500 0.21 Western University of Health Sciences 1.571 0.774 0.04** Constant -1.525 0.751 0.04**
Observations 688
Adjusted R-Square 0.1454
New Veterinarian Coefficient Std. Error Sig.
Graduation Year 0.057 0.002 0.00*** Age 0.025 0.003 0.00*** Gender (Female=0) -0.168 0.022 0.00*** Anticipated work hours per week 0.013 0.001 0.00*** Admitted before degree was completed -0.206 0.029 0.00*** Bachelor’s (baseline) Omitted Master’s -0.019 0.039 0.63 Ph.D. -0.231 0.130 0.08* Other professional degree -0.268 0.173 0.12 Other degree 0.154 0.125 0.22 Food Animal (exclusive) -0.237 0.053 0.00*** Food Animal (predominate) -0.142 0.049 0.00*** Mixed Animal 0.016 0.028 0.56 Companion Animal (exclusive) (baseline) Omitted Companion Animal (predominant) 0.054 0.028 0.06* Equine 0.695 0.048 0.00*** State/Local Government 0.504 0.266 0.06* Federal Government -0.091 0.122 0.46 Uniformed Services -0.686 0.059 0.00*** College/University 1.427 0.132 0.00*** Industry/Commercial -0.267 0.155 0.09* Non-for-profit 0.415 0.126 0.00*** The Ohio State University (baseline) Omitted Auburn University -0.434 0.057 0.00*** Tuskegee University 0.076 0.074 0.31 University of California-Davis -0.434 0.070 0.00*** Colorado State University -0.134 0.058 0.02**
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University of Florida -0.182 0.063 0.00*** University of Georgia -0.628 0.058 0.00*** University of Illinois -0.294 0.054 0.00*** Iowa State University -0.195 0.056 0.00*** Kansas State University -0.025 0.056 0.65 Louisiana State University -0.490 0.059 0.00*** Tufts University 0.292 0.071 0.00*** Michigan State University 0.058 0.058 0.32 University of Minnesota 0.401 0.060 0.00*** Mississippi State University -0.095 0.063 0.13 Purdue University -0.589 0.070 0.00*** Cornell University -0.310 0.062 0.00*** Oklahoma State University -0.355 0.059 0.00*** University of Pennsylvania 0.198 0.075 0.01*** Texas A&M University -0.746 0.050 0.00*** Washington State University -0.384 0.059 0.00*** University of Missouri-Columbia -0.273 0.060 0.00*** Oregon State University -0.203 0.083 0.02** University of Tennessee -0.323 0.064 0.00*** Virginia-Maryland College -0.296 0.056 0.00*** North Carolina State University -0.624 0.065 0.00*** University of Wisconsin -0.151 0.064 0.02** Western University of Health Sciences 1.381 0.089 0.00*** Constant 0.163 0.099 0.10
Observations 14,853
Adjusted R-Square 0.1876
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SECTION 4: THE MARKET FOR VETERINARIANS
Dataset Observations (n)
AAEP Membership database 7,432
AAEP - secondary sample 975
AVMA - comparative sample 2,545
Equine - main sample (81 Equine respondents from AVMA + 975 AAEP)
1,056
The veterinary profession is one of the many horizontal labor markets that comprise the
national labor market. The market for veterinarians may be thought of as the market for
veterinary labor. The largest market for veterinarians is private practice (e.g., companion
animal, food animal, equine and mixed animal), comprising roughly three-quarters of all active
veterinarians. The remaining quarter of active veterinarians are in the markets of education,
research, industry, government, non-profit, and consulting.
This section provides summary statistics about Equine and AVMA respondents’ income and
benefits, as well as information on factors that may affect income. In addition, the key
performance indicator (KPI) for the market for veterinarians, net present value of the DVM
degree, is discussed. An analysis of employment, unemployment and underemployment of the
Equine and AVMA samples is provided, along with an illustration of the geographic distribution
of Equine respondents.
4.1 EQUINE VETERINARY PROFESSION INCOMES
This following subsection on income summary statistics are based on respondents who are
employed full time (unless otherwise stated), not participating in an internship, residency, or
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advanced education, and reported their annual income between $20,000 and $300,000 in 2015
($600,000 for AVMA respondents).
4.1.1 Summary Statistics
To identify the weighted31 mean income of respondents before taxes, factors significant in
explaining the variation in income, location and gender, were used. Weighting the Equine
respondents using the membership data on location and gender yielded a weighted income of
$106,290.04 compared to for the weighted AVMA mean income of $118,452.04.
Mean income for Equine respondents was $99,000 annually, $118,000 for practice owners and
$78,000 for associates compared to $112,000 for the mean income of AVMA respondents,
$159,000 for practice owners and $90,000 for associates (Figure 59).
Separating mean income by gender, in all comparisons the mean income of male respondents
exceeded female respondents. Female equine practice owner respondents had a mean $55,000
less than male owners ($85,000 female vs. $140,000 male). For the AVMA survey, male owner
respondents had a mean $66,000 more in income ($186,000) than their female counterparts
($120,000). A $24,000 difference between male and female Equine respondent associates, and
a $15,000 difference between male and female AVMA respondent associates were measured.
31 A weighted average “refers to the mathematical practice of adjusting the components of an average to reflect the importance of certain characteristics.” Source: Merriam-Webster Dictionary
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Figure 59: Distribution of Respondents’ Mean Income by DVMs
To control for hours worked, full-time vs. part-time employment was compared by gender
(Figure 60). Equine female respondents who worked full time earned a mean of $76,000, and
male full-time respondents, $129,000, for a difference of $53,000. The difference between
Equine male and female part-time respondents was $40,000, with the mean income of $99,000
for part-time males compared to $59,000 for females. Male part-time employees in the AVMA
sample had a mean annual income of $80,000, which was $19,000 less than male part-time
Equine respondents. Male part-time Equine respondents had a higher mean income than full-
time Equine female respondents. Equine female respondents working part-time schedules had
a mean income ($59,000) similar to the mean income of AVMA female respondents ($60,000).
102K
87K
186K
120K
90K
159K
112K
97K
73K
140K
85K
78K
118K
99K
$0 $50,000 $100,000 $150,000 $200,000
Male Associate
Female Associate
Male Owner
Female Owner
Associate
Owner
Overall
Mean Income ($)
Type
of D
VMDistrbution of Respondents' Mean Income by DVMs
Equine AVMA
Equine DVM Associates: n=248, 187 F/58 M; DVM Owners: 273, 109 F/162 MAVMA DVM Associates: n=923, 685 F/181 M; DVM Owners: 360, 164 M/182 M
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Figure 60: Distribution of Respondents’ Mean Income by Gender and Full-Time vs. Part-Time Employment
80K
60K
146K
96K
140K
90K
112K
99K
59K
129K
76K
128K
78K
99K
$0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000 $140,000 $160,000
Male Part-Time
Female Part-Time
Male Full-Time
Female Full-Time
Male
Female
Overall
Mean Income
Empl
oym
ent
Stat
usDistribution of Respondents' Mean Income by Gender and Full-Time vs. Part-
Time Employment
Equine AVMA
Equine FT: n=521 (218 M/303 F); PT: n=23 (14 F/9 M)AVMA FT: n=1,764 (539 M/1,225 F); PT: n=185 (153 F/32 M)
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Mean income of the AAEP respondents also varies by size of practice, with those employed in
larger practices (by number of employees) earning more than those employed in smaller
practices (Figure 61). The number of employees used to determine practice size included all
veterinarians (both owners and associates) plus support staff.
Figure 61: Distribution of AAEP Mean Veterinary Income by Practice Size (Veterinarians and Support Staff)
$130,454.50
$115,915.10
$103,380.10
$96,668.57
$92,074.17
$92,201.16
$0 $50,000 $100,000 $150,000
50 or more staff members
20-49 staff members
10-19 staff members
5-9 staff members
2-4 staff members
One staff member
Mean Income ($)
Num
ber o
f Em
ploy
ees
Distribution of AAEP Mean Veterinary Income by Practice Size (Veterinarians and Support Staff) (n=447)
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4.1.2 Differences in Professional Income for Selected Characteristics
While the summary statistics describe differences in mean income by gender, ownership status,
employment status, and size of practice, the relationship between income and specific variables
are presented in this subsection. Means, medians, standard deviation and income by quartile
for each variable is presented first. Then a significance test is used to produce t-statistics for
each variable to determine if each factor is statistically significant in explaining the variation in
income between veterinarians.
A significance test with a p-value <.01 means there is 99 percent confidence that there exists a
relationship between the response and the factor, while a p-value between >.01 and <.05
means there is 95 percent confidence that there exists a relationship between the response
and the factor, and a p-value between >.05 and <.10 means there is 90 percent confidence that
there exists a relationship between the response and the factor. A p-value greater than .10 is
not significant. The data were cleaned of outlying observations. The values used in the
statistical analysis fall into the following categories: incomes above $20,000 and below
$300,000 for the Equine sample, incomes above $20,000 and below $600,000 for the AVMA
sample, those who worked more than 30 hours a week, those currently not in an internship or
residency, and/or those who are not enrolled in advanced education. Observations outside of
these ranges likely represent either input errors or are so far removed from the mean that they
are not representative of the population at large. While values outside of these ranges may be
of interest to some studies, they are not representative of the realities of a typical full-time
veterinarian and may represent undue upward or downward bias on the estimates. A
veterinarian working full time but making less than $20,000, for example, is most likely doing so
as a personal choice. He or she may easily enter the mainstream veterinary labor market and
earn a significantly higher salary.
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4.1.2.1 Number of Years since DVM Graduation
The analysis of the relationship between years since graduation and income uses seven
categories:
1) less than five years post-graduate,
2) 6 to 10 years,
3) 11 to 20 years,
4) 21 to 30 years,
5) 31 to 40 years,
6) 41 to 50 years,
7) more than 51 years.
All Equine and AVMA respondents’ mean income is highly significant (p-value <.001) with
regard to years since their DVM graduation. A Pearson’s Correlation coefficient was produced
for this characteristic to access the relationship of income with the increasing years out of
veterinary school. The correlation for Equine was .442 and .432 for AVMA respondents. These
two coefficients for both samples indicate a moderate positive relation between income and
graduation year. Equine respondents’ professional earnings increased with the number of years
of experience in veterinary medicine, with the exception of respondents who graduated more
than 51 years ago, who reported an average decrease in income, from $138,900 to $94,750. In
the AVMA sample, income continued to increase over time for these respondents (Table 45).
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Table 45: Mean Annual Income with Respect to the Number of Years since DVM Graduation
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 125 $56,875 $19,824 $43,000 $55,000 $70,000 6-10 years 151 $81,914 $34,689 $60,000 $75,000 $96,000 11-20 years 140 $107,547 $49,642 $75,000 $100,000 $125,000 21-30 years 121 $119,185 $62,487 $75,000 $105,000 $155,000 31-40 years 94 $132,055 $65,623 $80,000 $125,000 $162,000 41-50 years 33 $138,900 $72,121 $87,000 $125,000 $167,845 51 or more years 4 $94,750 $52,785 $58,500 $102,500 $131,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
0-5 years 465 $74,439 $22,570 $62,000 $72,000 $85,000 6-10 years 404 $95,749 $38,496 $72,000 $90,000 $111,000 11-20 years 467 $120,597 $69,952 $82,000 $102,000 $138,000 21-30 years 276 $142,472 $89,672 $84,750 $112,000 $181,500 31-40 years 117 $179,100 $114,648 $106,000 $140,000 $200,000 41-50 years 37 $172,471 $94,316 $100,000 $156,000 $227,000 51 or more years 6 $184,000 $214,798 $60,000 $100,000 $220,000
4.1.2.2 Level of Education
Respondents were classified into three categories with respect to degree or degrees obtained,
as explained in the following category definitions:
1) DVM, if the respondent did not obtain any degree or professional certificate in addition
to a DVM
2) DVM + Undergraduate Degree, if the respondent completed a Bachelor’s degree
program prior to or after obtaining a DVM degree
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3) DVM + Graduate Degree, if the respondent completed a Doctoral degree (e.g., Doctor of
Philosopy, Doctor of Education), or a Master’s degree (Master of Science, Master of
Arts, Master of Business Administration, Master of Public Health, or any degree
equivalent to a Master’s degree), or other advanced degree.
Equine respondents having a DVM degree only, (that is, no additional degree) have higher
mean income than those who have an undergraduate or graduate degree. The difference
between mean earnings was statistically significant for Equine respondents, p-value <.001
(AVMA p-value <.001) (Table 46).
Table 46: Mean Annual Income with Respect to Additional Degree Graduation
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 79 $123,575 $62,712 $79,000 $117,000 $156,000 DVM + Undergraduate Degree
460 $92,954 $54,702 $59,753 $78,000 $112,000
DVM + Graduate Degree 135 $107,090 $51,821 $70,000 $105,000 $137,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 157 $125,381 $75,994 $79,222 $105,000 $150,000 DVM + Undergraduate Degree
1,229 $105,626 $69,287 $70,000 $86,000 $115,000
DVM + Graduate Degree 369 $123,528 $73,001 $80,000 $105,000 $145,000
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4.1.2.3 Internship Participation
The rate of internship participation was approximately 53 out of 100 Equine respondents
compared to 26 out of 100 veterinarians from among the AVMA respondents. The difference in
mean income of Equine respondents who participated in an internship and those who did not
was statistically significant (p-value = .011) and negative, indicating that those who have
participated in an internship have a lower mean salary than those respondents who did not
participate in an internship. The AVMA sample showed no statistical significance between
veterinarians who completed an internship and those who did not (p-value = .264) (Table 47).
Because veterinarians who have been practicing equine medicine longer may have not
participated in an internship, and are also the majority who are practice owners and earning
higher salaries, Figure 62 shows the distribution of mean income of respondents, by graduation
year, who participated in an internship and those who didn’t.
Table 47: Mean Annual Income with Respect to Internship Participation
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 317 $105,173 $61,600 $65,000 $85,000 $130,000 DVM + Internship 366 $94,234 $50,480 $60,000 $82,000 $119,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 1,327 $110,339 $70,164 $72,000 $90,000 $120,000 DVM + Internship 467 $114,649 $76,042 $71,000 $98,000 $135,000
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Figure 62: Distribution of Respondents' Mean Income and Internship Participation by Graduation Year
$-
$50,000
$100,000
$150,000
$200,000
Mea
n In
com
e
Graduation Year
Distribution of Respondents' Mean Income and Internship Participation by Graduation Year
Equine-Internship (n=281) Equine-No Internship (n=241)
AVMA-Internship (n=1,285) AVMA-No Internship (n=446)
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4.1.2.4 Residency Participation
A substantial majority of respondents (83.1 percent) who had participated in a residency
indicated that they had also participated in an internship. Because internship or several years
of clinical experience are required to be admitted to participate in a residency program, this
finding is unsurprising. The income of respondents who participated in a residency after
undertaking an internship differs significantly from respondents who did not participate in a
residency but participated in an internship, for both Equine and AVMA sample (p-value <.001).
There was a difference of nearly $30,000 more in income between Equine respondents with a
residency and those who did not complete a residency. AVMA respondents showed an average
difference of $53,000 between respondents who participated in a residency and respondents
who did not (Table 48).
Table 48: Mean Annual Income with Respect to Residency Participation
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 262 $84,090 $49,959 $54,000 $71,000 $100,000 DVM +Residency w/ Internship
123 $113,802 $47,502 $80,000 $110,000 $145,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
DVM 286 $93,105 $53,764 $63,250 $85,000 $110,000 DVM + Residency w/ Internship
180 $146,185 $85,985 $90,000 $125,000 $180,000
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4.1.2.5 Gender
The difference in income between genders (the gender wage gap) is well known and exists in
nearly all professions; including the veterinary profession (pharmacy is the only profession
without a pronounced gender wage gap). Some of the gender wage gap can be explained by
differences in hours worked, type of employment, location of employment, educational
background and employment preparation. But, even after all available factors are considered, a
gap remains in salaries between men and women.
Without controlling for other factors the mean income for new female veterinary graduates in
both the Equine and AVMA sample is approximately $50,000 less than the mean for their male
counterparts (Table 49). For both Equine and AVMA respondents the difference in mean
income between genders is large and statistically significant (Equine: p-value <.001; AVMA: p-
value <.001). It must be noted that the male Equine respondents had a mean of 23 years of
experience versus the female Equine respondents, who had a mean of 10 years of experience in
this sample.
Table 49: Mean Annual Income with Respect to Gender
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Female 399 $79,128 $38,358 $55,000 $72,000 $98,000 Male 269 $129,695 $63,864 $80,000 $119,000 $165,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Female 1,167 $95,619 $47,771 $70,000 $85,000 $108,750 Male 527 $145,678 $94,648 $80,000 $115,000 $185,000
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4.1.2.6 Type of Employment
Employment type was divided into the major public and private practice types and the variation
in income among these samples is statistically significant for both the Equine (p-value = 0.015)
and AVMA (p-value <.001) samples. The mean income of Equine respondents in equine
practice is $98,853 and $97,118 for equine practitioners in the AVMA sample (Table 50).
Table 50: Mean Annual Income with Respect to Type of Employment32
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Equine Practice 448 $98,853 $59,057 $60,000 $82,000 $120,000 Mixed Animal Practice 80 $91,713 $53,859 $60,000 $75,000 $111,000 Companion Animal Practice 39 $98,051 $50,796 $70,000 $85,000 $114,000 Food Animal Practice 16 $81,451 $51,427 $37,000 $71,000 $106,712 College/University 80 $118,371 $39,323 $100,000 $114,500 $143,500 Other Veterinary Empl. 6 $46,167 $30,486 $24,000 $39,000 $55,000
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Equine Practice 77 $97,118 $98,473 $50,000 $65,000 $100,000 Mixed Animal Practice 100 $88,677 $53,184 $62,000 $75,000 $94,500 Companion Animal Practice
1,154 $112,094 $73,923 $73,000 $90,000 $120,000
Food Animal Practice 44 $107,112 $88,713 $66,000 $81,000 $118,500 Uniformed Services 13 $93,138 $34,301 $75,000 $85,794 $102,000 College/University 154 $126,411 $63,297 $90,000 $110,000 $140,000 Federal Government 52 $108,055 $47,290 $73,757 $107,500 $134,426 Industry/Commercial Organization
67 $157,070 $55,532 $115,000 $150,000 $200,000
Not-for-profit 52 $90,593 $47,405 $64,500 $83,500 $104,500 Other Veterinary Employment
51 $107,335 $69,926 $69,000 $88,000 $120,000
State/Local government 28 $96,026 $24,274 $83,000 $96,000 $107,500 Non-Veterinary Empl. 3 $63,500 $21,148 $46,000 $57,500 $87,000
32 Federal government, Industry/Commercial Organization, and Not-for-profit were omitted in the Equine sample because the number of observations did not permit estimation.
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4.1.2.7 Geographic Location
For both the Equine and AVMA sample the variation in mean incomes was great between the
regions 0 to 9 (Table 51). The region with the highest mean professional income in the Equine
sample was Region 4 ($115,410). Kentucky is located in Region 4, and Lexington, Ky., is known
as the “Horse Capital of the World” because it is heavily populated with horses and large
Thoroughbred breeding operations. Region 5 had the lowest mean income at $83,640.
Comparatively, when examining the AVMA respondent incomes, the lowest mean income
occurred in Region 5 ($95,611) and the highest mean income was Region 1 ($124,761). For
both Equine and AVMA respondents the mean incomes were statistically significant with
respect to work region (Equine p-value = .022; AVMA p-value = .009).
Table 51: Mean Annual Income with Respect to Region
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Region 0 57 $98,283 $57,562 $60,000 $82,000 $120,000 Region 1 63 $91,376 $44,015 $60,000 $79,000 $114,000 Region 2 67 $102,514 $66,538 $60,000 $80,000 $125,000 Region 3 76 $106,958 $69,408 $59,000 $87,500 $140,633 Region 4 65 $115,410 $58,031 $71,000 $112,000 $145,000 Region 5 45 $83,640 $42,210 $59,000 $75,000 $105,000 Region 6 45 $91,813 $42,312 $65,000 $85,000 $112,000 Region 7 69 $114,071 $52,641 $80,000 $100,000 $150,000 Region 8 68 $88,969 $56,241 $51,500 $75,000 $104,000 Region 9 92 $100,204 $53,926 $65,000 $83,000 $124,500
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AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Region 0 130 $118,386 $80,736 $76,000 $95,500 $135,000 Region 1 147 $124,761 $79,425 $76,000 $100,000 $150,000 Region 2 203 $113,601 $70,783 $75,000 $93,851 $122,000 Region 3 209 $112,364 $70,866 $72,000 $94,000 $125,000 Region 4 171 $97,538 $48,270 $70,000 $85,000 $115,000 Region 5 118 $95,611 $57,906 $65,000 $80,000 $100,000 Region 6 154 $104,644 $63,451 $70,000 $84,500 $115,000 Region 7 163 $115,245 $73,968 $75,000 $95,000 $125,000 Region 8 128 $117,473 $94,041 $70,000 $90,075 $122,500 Region 9 215 $114,563 $58,114 $80,000 $100,000 $130,000
Figure 63 displays the variation among annual income of respondents by U.S. region, as laid out
in Table 51.
Mean Annual Income of Equine Respondents by U.S. Region, 2016
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Mean Annual Income of AVMA Respondents by U.S. Region, 2016
Figure 63: Map of U.S. Regions with Respect to Mean Annual Income of Equine and AVMA Respondents
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4.1.2.8 Practice Ownership
Practice ownership had a statistically significant impact on professional income (p-value <.001)
among both the Equine and AVMA respondents. Mean annual income for practice owners and
for non-practice owners differed by $41,248 for Equine respondents and $67,623 for AVMA
respondents (Table 52).
Table 52: Mean Annual Income with Respect to Practice Ownership
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Non-Practice Owner 258 $77,124 $35,337 $55,000 $70,000 $90,000 Practice Owner 264 $118,372 $68,622 $65,000 $100,000 $152,789
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Non-Practice Owner 1,004 $91,495 $41,489 $70,000 $82,000 $103,500 Practice Owner 360 $159,118 $117,125 $75,000 $125,000 $200,000
4.1.2.9 Practice Ownership and Board Certified vs. Non-Board Certified
Board certification had a significant impact on professional income for Equine respondent
practice owners (p-value <.001) as well as associates (p-value = .003). This was also reflected in
the AVMA sample where board certification of both practice owners (p-value = .002) and
associates (p-value <.001) was found to have a significant impact on income compared to that
of non-board-certified owners and associates.
The difference in mean annual income for practice owners who are and who are not board
certified was $42,088 for the Equine respondents and $67,041 for the AVMA respondents
(Table 53). Mean income for Equine respondents who are board-certified associates was
$18,157 more than non-board-certified associates (AVMA income difference: $57,077).
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Table 53: Mean Annual Income with Respect to Board-Certified Practice Owners and Board-Certified Associates
Equine Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Practice Owners
Board Certified 31 $154,960 $66,970 $112,000 $150,000 $197,000 Non-Board Certified
242 $112,872 $67,393 $65,000 $95,000 $150,000
Associates
Board Certified 36 $93,845 $37,944 $70,000 $90,000 $114,404 Non-Board Certified
212 $75,688 $33,193 $55,000 $70,000 $85,500
AVMA Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Practice Owners
Board Certified 30 $220,710 $139,308 $98,000 $212,500 $320,000 Non-Board Certified
329 $153,669 $113,635 $75,000 $120,000 $200,000
Associates
Board Certified 82 $142,239 $69,446 $90,000 $130,000 $195,000 Non-Board Certified
840 $85,162 $28,271 $68,600 $80,000 $99,250
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4.1.2.10 Primary Equine Sector
The mean income with respect to the primary equine sector that veterinarians serve was
statistically significant (p-value = .011). The highest mean income level was found in the racing
segment. The total percent of AAEP respondents in the racing segment (Standardbred,
Thoroughbred, and Quarter Horse) was 8 percent with a range of mean incomes of
approximately $131,000-$143,000. Respondents who are ranch or working horse veterinarians
on average had the lowest mean income at $82,629. Among respondents, over 60 percent
reported serving multiple sectors and this group had a mean income that was lower than the
average for all equine practitioners (Table 54).
Table 54: Mean Annual Income with Respect to Primary Equine Sector33
AAEP Obs. Mean Std. Dev. 1st Quartile Median 3rd Quartile
Racing - Standardbred 5 $143,200 $72,448 $85,000 $125,000 $180,000 Racing - Thoroughbred 24 $133,308 $71,940 $85,000 $113,500 $150,000 Racing - Quarter Horse 5 $131,400 $79,952 $82,000 $95,000 $175,000 English performance 66 $111,588 $66,645 $65,000 $95,500 $145,265 Western performance 14 $105,536 $57,414 $62,500 $103,000 $137,000 Reproductive 26 $105,359 $60,273 $70,000 $87,000 $110,000 General equine practice
271 $94,174 $54,207 $60,000 $79,433 $117,000
Equine companion 23 $83,599 $57,726 $52,000 $72,000 $100,000 Ranch or working 7 $82,629 $52,714 $45,000 $70,000 $106,403 Overall 441 $100,173 $59,156 $65,000 $84,000 $120,000
33 Gaited breeds was omitted because the number of observations did not permit estimation.
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4.1.3 Factors Affecting Income
Numerous factors explain the variation in income. Narrative in the previous section provides
the difference between specific (but not all) factors and income.
To explain the contribution of each factor to the variation in income, a multiple linear
regression was used. Variables that are significant at the 10 percent, 5 percent and 1 percent
levels were reported in explaining the factors affecting income. The main factors considered
were year of graduation, age, gender, hours worked, full-time employment (work 30 or more
hours), veterinary educational debt, board certified, intern and residency participation, home
ownership, living environment/community, work region, highest degree obtained, practice
ownership, community size in which respondents work, and compensation method. In addition,
equine-specific variables such as business model, equine sector, total number of unique horse
patients, practice type and practice size were used for the AAEP model, and type of
employment were used for the AVMA respondent model.
The coefficient in Table 55 indicates the dollar value impact of the corresponding variable on a
respondent’s annual income. For example, an AAEP respondent who is working full time earns
on average $40,911.60 more than respondents working part time, holding everything else
constant.
The last column in both the AAEP and AVMA tables, labelled “Sig. ,” represents the significant
variables. A significance, or “sig,” less than .10 indicates that there is less than a 10 percent
chance that there is no relationship between the factor and income. For AAEP respondents
who worked in Region 3, for example, the p-value is .06; this means that there exists a six
percent statistical probability that this factor has no impact on incomes and thus is significantly
different from the baseline, Region 9.
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To avoid statistical errors, baseline variables are used to compare against. The baseline
variables in the AAEP model are work in Region 9, owns a home, lives in a rural area, obtained a
bachelor’s degree, serves a community of 50,001 to 500,000 residents, private practice owned
by a single veterinarian, salary compensation method, practice size of 5 to 9 staff members,
works in an ambulatory practice, and works in the general equine industry. The baseline
variables in the AVMA model consist of work in Region 9, owns a home, lives in a rural area,
obtained a bachelor’s degree, serves a community of 50,001 to 500,000 residents, salary
compensation method, and companion animal practice.
The coefficient for gender, -$30,435.90, indicates that the mean income of AAEP respondents
who are female is $30,435.90 less than their male counterparts in this survey, holding all other
variables constant. AVMA respondents who are female earn on average $52,183.84 less annual
income than AVMA respondents who are male, holding all other variables constant.
AAEP respondents employed in the Thoroughbred racing industry have a mean income that is
$36,484.81 more than respondents working in the general equine industry. While not
significant but close to the 10 percent level is the finding that, holding all other variables
constant, respondents employed in the equine companion sector have a mean income that is
$22,912.34 more than respondents working in the general equine industry. AAEP respondents
who are compensated on production only on average have a mean income $30,594.29 more
than respondents compensated based on salary only. AAEP respondents who collect an owner
distribution with differentiation between pay for effort as a veterinarian and pay as an owner
have, on average, a mean income $37,615.92 more than respondents compensated by salary
only. AVMA respondents who are compensated with owner withdrawals have an average
mean income of $82,902.12 greater than AVMA respondents compensated by salary only, and
holding all other variables constant.
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The coefficient for AVMA respondents currently working in equine practice, -
$58,803.07, indicates that the mean income for veterinarians employed as equine practitioners
is $58,803.07 less than respondents in companion animal medicine, holding all other variables
constant.
The factors that were included in this model produced an adjusted R-square of 0.4121 in the
AAEP sample model and .0691 in the AVMA sample model. This indicates that the inclusion of
all these factors were able to explain 41 percent and 7 percent of the variation between the
individually reported income and the estimated mean income. Thus, there are important
variables that determine incomes that have not been included, and are due to other
unobservable factors.
Table 55: Factors Affecting Income
AAEP34 Coefficient Std. Err. Sig.
Graduation Year 90.77 1055.30 0.93 Age 370.10 997.94 0.71 Gender (Female=1) -30435.90 7682.23 0.00*** Hours worked 31.89 127.51 0.80 Full-time (Yes=1) 40911.60 16997.21 0.02** DVM Debt -0.04 0.06 0.44 Board Certified (Yes=1) 22584.98 19179.37 0.24 Internship (Yes=1) -3153.58 7129.53 0.66 Residency (Yes=1) -10448.39 18229.14 0.57 Housing - own (baseline) Omitted Housing - rent -5255.21 8637.22 0.54 Housing - other -24935.51 21278.21 0.24 Rural (baseline) Omitted Urban 4910.63 11730.75 0.68 Suburban 11146.14 7329.15 0.13 Region 0 10036.85 14790.51 0.50
34 Corporate practice and gaited breeds were omitted because the number of observations did not permit estimation.
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Region 1 11616.52 13703.96 0.40 Region 2 12064.52 13604.80 0.38 Region 3 25048.10 13424.66 0.06* Region 4 2627.50 13659.23 0.85 Region 5 -1891.52 13594.19 0.89 Region 6 -4354.43 16094.68 0.79 Region 7 7792.55 14476.48 0.59 Region 8 -10652.48 12166.40 0.38 Region 9 (baseline) Omitted Bachelor’s (baseline) Omitted Ph.D. 75240.41 68140.27 0.27 Master’s 3072.92 11023.65 0.78 Specialty Degree -29346.44 38847.46 0.45 DVM only 15469.68 9606.29 0.11 Practice Owner (Yes=1) 21201.45 10313.27 0.04** Under 2,500 residents 2854.65 12562.93 0.82 2,501 to 10,000 residents -4672.44 10991.24 0.67 10,001 to 25,000 residents -587.31 10571.44 0.96 25,001 to 50,000 residents 4756.15 9901.57 0.63 50,001 to 500,000 residents (baseline) Omitted 501,000 or more residents 5456.62 9806.70 0.58 General equine (baseline) Omitted Ranch or working 13299.15 24128.33 0.58 English performance 1384.12 10764.99 0.90 Companion 22912.34 15466.17 0.14 Quarter Horse racing 31058.39 31091.84 0.32 Standardbred racing 24451.78 28560.69 0.39 Thoroughbred racing 36484.81 17628.53 0.04** Reproductive 8483.85 14528.55 0.56 Western performance 21735.53 16916.80 0.20 Unique Patients 7.87 3.12 0.01*** Ambulatory (baseline) Omitted Ambulatory with haul-in facility -9467.10 8013.65 0.24 Haul-in only 3842.62 27327.60 0.89 Specialty/referral - limited service hospital -21331.26 26616.08 0.42 Specialty/referral - full service hospital -29811.74 27531.41 0.28
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Specialty/referral - limited service hospital with ambulatory
-17032.53 24790.95 0.49
Specialty/referral - full service hospital with ambulatory -13495.30 11738.21 0.25 Other business model 16009.65 20984.46 0.45 Salary (baseline) Omitted Production only 30594.29 12842.34 0.02** Hourly or per diem 4423.03 22100.33 0.84 Salary with production-based incentive 11002.89 9664.25 0.26 Other method compensation 1974.39 18397.80 0.92 Salary without production-based incentive 11608.44 29345.64 0.69 Owner with no differentiation -9349.09 11464.91 0.42 Owner with differentiation 37615.92 13344.18 0.01*** Private practice owned by a single vet (baseline) Omitted Private corporate practice 8442.02 7685.89 0.27 One staff member -21833.72 11679.42 0.06* 2 to 4 staff members -24615.14 9833.70 0.01*** 5 to 9 staff members (baseline) Omitted 11 to 19 staff members 4732.35 9860.78 0.63 20 to 49 staff members 4923.70 13652.62 0.72 50 or more staff members -18609.37 25039.92 0.46 Constant 26629.59 38237.13 0.49
Observations 264
Adjusted R-Square
0.4121
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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AVMA Coefficient Std. Err. Sig.
Graduation Year 3904.77 2666.19 0.14 Age -1059.23 2490.53 0.67 Gender (Female=1) -52183.84 20089.46 0.01*** Hours worked 251.88 722.98 0.73 Full-time (Yes=1) 32951.23 35457.27 0.35 DVM Debt 0.12 0.10 0.21 Board Certified (Yes=1) 59609.45 57217.41 0.30 Internship (Yes=1) -6982.35 22572.25 0.76 Residency (Yes=1) 121462.60 60758.30 0.05** Housing - own (baseline) Omitted Housing - rent -3296.92 21152.44 0.88 Housing - other -4602.02 56089.05 0.94 Rural (baseline) Omitted Urban -17490.19 29569.68 0.55 Suburban 5044.26 21438.69 0.81 Region 0 112935.10 38282.34 0.00*** Region 1 -13506.55 34229.79 0.69 Region 2 795.71 32433.35 0.98 Region 3 -8266.28 32994.16 0.80 Region 4 -10117.26 34118.54 0.77 Region 5 -14266.99 36606.69 0.70 Region 6 -21597.46 35466.94 0.54 Region 7 -21834.91 34285.12 0.52 Region 8 -23618.95 35434.65 0.51 Region 9 (baseline) Omitted Bachelor’s (baseline) Omitted Ph.D. 17975.67 43074.74 0.68 Master’s -25204.46 27268.15 0.36 Specialty Degree -211704.90 211545.50 0.32 DVM only -31204.51 31648.56 0.32 Practice Owner (Yes=1) 39787.38 28514.62 0.16 Under 2,500 residents -43517.98 43980.66 0.32 2,500 to 49,999 residents -11914.04 20381.15 0.56 50,000 to 499,999 residents (baseline) Omitted 500,000 or more residents 49251.33 24490.39 0.05** Salary (baseline) Omitted
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Hourly or per diem -4395.37 34163.46 0.90 Production only 24461.16 31531.01 0.44 Mix of salary with opportunity for production-based compensation
7843.65 20628.79 0.70
Owner withdrawals 82902.12 33514.08 0.01*** Companion Animal (baseline) Omitted Food Animal 52660.19 56716.36 0.35 Equine -58803.07 41664.49 0.16 Mixed Animal 199.08 35802.85 1.00 Federal Government 18956.72 99081.73 0.85 Uniformed Services -14359.85 291242.80 0.96 College/University -2559.73 82345.58 0.98 State/Local Government -9314.52 119980.30 0.94 Industry/Commercial -9957.52 97848.96 0.92 Not-for-profit -3034.22 88477.95 0.97 Other veterinary employment -59782.30 55667.82 0.28 Non-veterinary employment -76808.19 146648.40 0.60 Constant 64776.28 88448.99 0.46
Observations 1,261
Adjusted R-Square
0.0691
Note: ***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10
percent (p < .10) levels, respectively
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4.2 FRINGE BENEFITS RECEIVED
Equine respondents were asked to indicate the benefits that they received from their employer
(Table 56). A higher percentage of respondents from the AVMA sample (63.7 percent) reported
receiving medical benefits versus the Equine respondents (52.8 percent). Employers in both
samples offered respondents benefits that are primarily paid directly (e.g., veterinary licensure,
continuing education expenses, discounted veterinary care, professional association dues). Also
among Equine respondents, 6.7 percent were given paid maternity leave and 2.1 percent paid
paternity leave.
Table 56: Fringe Benefits Received
Benefit Equine (n=816) AVMA (n=2,545)
Continuing education expenses 84.1% 72.4% Licenses 77.9% 69.0%
Liability insurance 76.8% 50.5%
Association dues 75.7% 65.2%
Continuing education leave 64.1% 56.3%
Discounted veterinary care for personally-owned animals
61.3% 63.1%
Medical/ hospitalization plan 52.8% 63.7%
Paid vacation leave 51.4% 63.4%
Employer contribution/match to a tax-deferred retirement plan (i.e. 401(k), SIMPLE IRA, etc.)
44.9% 45.6%
Disability insurance 40.4% 35.5%
Personal use of practice-owned vehicle 38.7% 12.5% Paid legal holidays 35.8% 44.7%
Paid sick leave 33.6% 43.6%
Uniform/clothing allowance 31.5% NA
Tax-deferred retirement plan (i.e. 401(k), IRS- qualified profit-sharing plan)
29.9% 45.1%
Life insurance 28.8% 34.4% Dental plan 26.0% 39.4%
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Reimbursed mileage for practice use of personal vehicle
14.6% NA
Paid maternity leave 6.7% NA
No benefits provided/purchased 5.6% 8.0% Other (Specify) 3.6% 4.2%
Informal profit-sharing plan (not tax-deferred) 3.4% 3.1%
Paid paternity leave 2.1% NA
Table 57 compares the fringe benefits received by male and female Equine respondents. In a
gender comparison, males reported a higher percentage of benefits. Women, however,
reported a higher percentage of discounted veterinary care, paid vacation leave, reimbursed
gas mileage, maternity leave, and other types of (unidentified) benefit. The benefit that was
reported being received by the largest percentage of both male and female respondents was
continuing education expenses, and the rarest benefit reported was paid maternity and
paternity leave.
Table 57: Fringe Benefits Received with Respect to Gender, Excluding True Solo Practitioners
Equine Male (n=324) Female (n=483)
Continuing education expenses 88.6% 81.6% Liability insurance 82.4% 73.5% Licenses 80.9% 76.2% Association dues 79.9% 73.5% Continuing education leave 66.0% 63.6% Medical/ hospitalization plan 61.4% 46.8% Discounted veterinary care for personally owned animals
58.3% 64.0%
Disability insurance 50.0% 34.0% Employer contribution/match to a tax-deferred retirement plan (i.e. 401(k), SIMPLE IRA, etc.)
47.5% 43.7%
Paid vacation leave 46.6% 54.9% Personal use of practice-owned vehicle 44.4% 35.0% Life insurance 42.9% 19.0% Paid legal holidays 38.9% 34.0%
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Tax-deferred retirement plan (i.e. 401(k), IRS-qualified profit-sharing plan)
38.0% 24.6%
Paid sick leave 34.9% 33.1% Uniform/clothing allowance 34.3% 30.2% Dental plan 26.2% 25.9% Reimbursed mileage for practice use of personal vehicle
12.7% 16.1%
No benefits provided/purchased 6.2% 5.4% Informal profit-sharing plan (not tax-deferred)
4.3% 2.9%
Paid maternity leave 3.7% 8.7% Paid paternity leave 3.7% 1.0% Other (Specify) 2.5% 4.3%
Two questions, asked only in the AAEP survey, pertained to retirement assets. Among
respondents, 63.8 percent reported having assets for retirement. The primary asset reported
was a combination of assets (36.2 percent) followed by a 401(k)/Keogh/IRA fund (31.3 percent)
(Table 58). Nearly 80 percent reported having a 401(k)/Keogh/IRA account (Table 59), about the
same percentage (79.1) as reporting being under the Social Security program which is usually
required for full-time workers.
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Table 58: Distribution of Equine Primary Assets for Retirement
AAEP (n=594) Percent
Combination of the above 36.2% 401(k)/Keogh/IRA 31.3% Real estate holdings 9.4% Sale of practice ownership interest 8.5% Other investments 6.4% Social Security 5.2%
Table 59: Distribution of Assets for Retirement among Respondents (select all that apply)
AAEP (n=593) Percent
Social Security 79.1% 401(k)/Keogh/IRA 77.9% Real estate holdings 49.1% Other investments 45.9% Sale of practice ownership interest 39.5% Inherited funds 21.9%
Among AAEP respondents, 28.8 percent indicated they were either very or extremely confident
in their financial preparation for retirement, while 34.5 percent indicated they were not very or
not at all confident and 36.8 percent of respondents were moderately confident.
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4.3 FAMILY STATUS
Just over half of the AAEP respondents (52.1 percent) indicated they have children. Another
31.4 percent of respondents reported that they did not have children (nor planned to during
their professional career), while 16.5 percent of respondents would like to have children during
their professional career (Figure 64).
Figure 64: Distribution of AAEP Respondents’ Children Status
Among Equine respondents, the mean number of children in a household was 2.4 compared to
2.1 children in the AVMA sample (Table 60).
Of the respondents who reported having children, 48.4 percent of Equine respondents reported
that they had children under the age of 18, as well as children over the age of 18 (ages 0 +);
39.8 percent of AVMA respondents (Figure 65) responded similarly. In addition, 42.8 percent of
Equine respondents reported having children only under the age of 18 (ages 0-18), and 8.9
percent reported having only children less than five years of age (ages 0-5). 31.4 percent of
16.5%
52.1%
31.4%
Distribution of AAEP Respondents' Children Status (n=695)
Would Like To Have Children Have Children Do Not Have Children
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AVMA respondents reported having children under the age of 18 (ages 0-18), and 28.8 percent
having only children under the age of five (ages 0-5).
Table 60: Mean Number of Children in Equine and AVMA Respondents’ Household
Obs. Mean Std. Dev. Min Max
Equine 395 2.44 1.29 1 12 AVMA 1,167 2.12 1.05 1 10
Figure 65: Distribution of Equine and AVMA Respondents’ Age of Children in Household
8.9%28.8%
42.8%
31.4%
48.4% 39.8%
Equine (n=395) AVMA (n=1,149)
% o
f Res
pond
ents
Age of Children (%)
Distribution of Respondents' Age of Children in Household
Under 5 Only Under 18 only Under/Over 18
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Of respondents who stated they had children or plan to have children, 87.5 percent expressed
that their employers were supportive of their decision to have a family. Of AAEP respondents,
40.1 percent had no maternity/paternity leave offered, 31.8 percent had one-two months, 14.2
percent two-four month, 1.7 percent more than four months, and 12.2 percent indicated some
other duration. Those in the other category stated they were sole proprietors, had unlimited
leave of some kind, unpaid leave, used sick leave, or had fewer than three weeks offered
(Figure 66).
Figure 66: Distribution of AAEP Respondents’ Number of Weeks of Maternity/Paternity Leave Offered by Employer (Paid or Unpaid)
With regard to available maternity or paternity leave, 41.2 percent of AAEP respondents
reported that none of the maternity or paternity leave was eligible for compensation, 34.6
percent reported one-two months of leave was eligible for compensation, 7.0 percent reported
two to four months of compensation-eligible leave, 0.7 percent reported more than four
months eligible for compensation; and 16.5 percent had another answer: About 25 percent of
40.1%
31.8%
14.2%
1.7%
12.2%
Distribution of AAEP Respondents' Number of Weeks of Maternity/Paternity Leave Offered by Employer (Paid or
Unpaid) (n=459)
No leave offered
1 - 2 months
2 - 4 months
Over 4 months
Other
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“Other” responded that they did not know if maternity/paternity leave was eligible for
compensation (Figure 67).
Figure 67: Distribution of AAEP Respondents’ Maternity/Paternity Leave That Is Eligible for Compensation
Of AAEP respondents who have or plan to have children and have a maternity and paternity
leave benefit, 49.0 percent indicated that the employer continues to provide benefits during
maternity and paternity leave (Figure 68). Over 58 percent of respondents indicated that one-
two months of benefits are provided during maternity and paternity leave (Figure 69).
34.6%
7.0%0.7%
16.5%
41.2%
Distribution of AAEP Respondents' Maternity/Paternity Leave That is Eligible for Compensation (n=272)
1 - 2 months
2 - 4 months
Over 4 months
Other
No compensation
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Figure 68: Distribution of AAEP Respondents’ Employer That Continues to Provide Benefits during Maternity/Paternity Leave
Figure 69: Distribution of AAEP Respondents’ Length of Time Their Employer Provides Benefits during Maternity/Paternity Leave
When AAEP respondents were asked if they had ever left a position due to maternity or
paternity leave issues, 3.4 percent of respondents indicated that they had done so. Asked how
51%49%
Distribution of AAEP Respondents' Employer That Continues to Provide Benefits during Maternity/Paternity Leave (n=445)
No Yes
0.5%
58.5%23.6%
4.3%
13.2%
Distribution of AAEP Respondents' Length of Time Their Employer Provides Benefits during Maternity/Paternity Leave
(n=212)
0 months
1 - 2 months
2 - 4 months
Over 4 months
Other
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well policy relating to maternity or paternity leave had been addressed in employment
contracts, 74.9 percent of AAEP respondents stated it had not been well addressed (Figure 70).
Figure 70: Distribution of AAEP Respondents and Whether or Not Maternity/Paternity Leave Policy Has Been Well Addressed in Employment Contracts
4.4 MARKET KEY PERFORMANCE INDICATOR: NET PRESENT VALUE
Net present value of the DVM/VMD degree is a key performance indicator for the profession as
it provides an indication of the willingness of society to compensate veterinarians for the
investment in the DVM/VMD degree. The NPV provides the current value of the life-long
earnings of the veterinarian above what they would have earned had they not obtained their
DVM/VMD degree.
4.4.1 Age Earnings Profile
The age-earnings profile of equine practitioners and the general veterinary profession provided
the mean salary for veterinarians by age, and is illustrated for males and females in Figure 71.
The age-earnings profile for equine practitioners and the age-earnings profile for the general
74.9%
25.1%
Distribution of AAEP Respondents and Whether or Not Maternity/Paternity Leave Policy Has Been Well Addressed in
Employment Contracts (n=692)
No Yes
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veterinary practitioners was obtained from more than 50,00035 observations of veterinarians
from across the profession. Both were used to provide the expected labor income at any given
age. The starting point for new graduates in the age-earnings profile was based off of the
average starting salary reported by recent graduates in the 2017 AVMA Senior Survey.
The shape of the lifetime earnings path for males (both equine practitioners and general
veterinary practitioners) is similar to an inverted-U: Earnings increase quickly at the beginning
of the career as experience (human capital) is quickly accumulated, reaches a peak as
experience is maximized, and then decreases with the tendency to want to work fewer hours
with age.
The female age-earning profile for equine practitioners and the general veterinary practitioners
has a quadratic form (leveling off in the mid-years) that is different from the male’s age-earning
profile. Why these differences in the male and female age-earning profiles occur is unknown.
Because these earnings paths represent what has happened in the past, they may predict what
will occur in the future. Absent any measured factors that contribute to these differences,
however, age-earnings profiles are used to estimate the NPV of the DVM/VMD degree.
35 The 50,000 observations come from the AVMA 2010 -2015 Biennial Economic Surveys (BES), the 2014 - 2015 AVMA employment surveys, and the AVMA 2016 Census of Veterinarians. 2,700 observations from the BES were equine practitioners and were used in the equine age-earnings profile.
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Figure 71: Equine Practitioner and General Veterinary Practitioner Age-Earnings Profiles by Gender
4.4.2 Net Present Value (NPV) of the DVM Degree
Net present value is the difference between the present value of cash inflows (income) and the
present value of cash outflows (expenses). Thus, in examining the NPV of a veterinary
$- $20,000 $40,000 $60,000 $80,000
$100,000 $120,000 $140,000 $160,000 $180,000
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44
Aver
age
Annu
al In
com
e
Years of Experience
Equine Practitioner Age-Earnings Profile by Gender
Male Female
$- $20,000 $40,000 $60,000 $80,000
$100,000 $120,000 $140,000 $160,000 $180,000
0 2 4 6 8 1012141618202224262830323436384042444648
Aver
age
Annu
al In
com
e
Years of Experience
General Veterinary Practitioner Age-Earnings Profile by Gender
Male Female
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education, one would look at the present value of the expected cash flow from being employed
as a veterinarian over the course of the career minus the present value of the investment in
earning the veterinary degree. If the NPV is positive, then the investment yielded more inflow
than outflow. In the model presented here, the veterinary degree is compared with the
Bachelor’s degree to determine whether the additional investment in the DVM/VMD is borne
out by equivalently increased cash inflows over the course of the career.
The NPV has been declining in the general veterinary profession since 2010. The primary reason
for the declining NPV is the increasing opportunity costs 36: Starting salaries for bachelor degree
holders grew more than 19 percent during this time period, whereas starting salaries for the
DVM/VMD degree holders grew approximately 5.5 percent. If the earnings gap between
DVM/VMD and bachelor’s degree holders continues to narrow, veterinary students may begin
to view the DVM/VMD degree as not worth the price of admission to the veterinary profession.
The decline in the NPV for men has been much steeper than for women and this may be a
contributing factor to the changing gender distribution in the profession. Males have a much
larger opportunity cost to become a DVM than do women, as the gap between mean veterinary
income and that of a general Bachelor’s degree recipient is substantially less for men than for
women (Figure 72). However, in 2017 males crossed over into a positive net present value. This
is most likely due to a dip in the Bachelor’s degree holders’ starting salary for 2017, a rise in
male veterinarian starting salaries, and a decrease in average debt of male veterinarians.
36 The opportunity costs refer to the l ifetime income earning potential had veterinarians pursued an alternative career prior to entering veterinary college. The l ifetime mean earnings of a typical bachelor’s degree recipient are used to estimate opportunity costs. This alternative earning profile begins at graduation; a veterinarian gives up four years of alternative earning potential while in veterinary school and this must be overcome before there is a positive gain in earnings with the DVM (versus a bachelor’s degree only).
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Figure 72: Net Present Value of the DVM Degree of General Veterinary Practitioners by Gender
For equine practitioners, the NPV follows a similar pattern to the general veterinary profession,
but the NPV for female equine practitioners is lower than females in the general veterinary
profession. Male equine practitioners yielded similar NPV’s to the male general veterinary
profession from 2010-2014. In 2015, the male equine practitioner NPV started to separate, and
fall further below the males in the general veterinary profession (Figure 73).
2010 2011 2012 2013 2014 2015 2016 2017Male $140,728 $133,594 $70,292 $37,315 -$73,691 -$104,87 -$43,038 $117,23Female $438,236 $345,198 $283,583 $295,364 $236,769 $252,820 $308,892 $497,54
-$200,000
-$100,000
$0
$100,000
$200,000
$300,000
$400,000
$500,000
$600,000
Net Present Value of the DVM Degree of General Veterinary Practitioners by Gender
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Figure 73: Net Present Value of the DVM Degree of Equine Practitioners by Gender
Because of the low number of observations of Equine practitioners between 2010 and 2017,
Table 61 and Table 62 are provided for context in explaining the variability in the equine
practitioner NPV figure. Mean student debt and starting salary of equine practitioners from the
AVMA 2010-2017 Senior Surveys who accepted employment in full-time equine veterinary
medicine were reported, as well as general veterinary practioners who accepted employment
in full-time private practice are provided for comparison in Table 61. The mean debt and
income patterns vary considerably between the equine and general survey respondents.
2010 2011 2012 2013 2014 2015 2016 2017Male $138,954 $131,785 $68,506 $35,514 -$75,496 -$106,742 -$89,129 $87,110Female $353,979 $263,416 $203,182 $212,364 $152,644 $164,067 $196,609 $238,698
-$200,000
-$100,000
$0
$100,000
$200,000
$300,000
$400,000
Net Present Value of the DVM Degree of Equine Practitioners by Gender
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Table 61: Mean Veterinary Educational Debt and Mean Starting Salary of Graduating Seniors, 2010 - 201637
Female - Equine Practitioners Female - General Practitioners
Year Obs. Mean Student Debt
Mean Student Starting Salary
Obs. Mean Student Debt
Mean Student Starting Salary
2010 22 $106,427 $34,250 574 $110,589 $66,339 2011 30 $115,000 $42,621 513 $116,402 $64,390 2012 18 $97,222 $35,389 423 $124,570 $63,303 2013 26 $103,478 $42,615 724 $134,985 $65,350 2014 23 $108,580 $43,167 843 $131,546 $66,236 2015 25 $137,224 $42,096 974 $136,738 $69,879 2016 26 $123,346 $43,738 1169 $141,709 $73,330 2017 25 $118,370 $43,720 1103 $139,936 $76,661
Male - Equine Practitioners Male - General Practitioners
Year Obs. Mean Student Debt
Mean Student Starting Salary
Obs. Mean Student Debt
Mean Student Starting Salary
2010 9 $89,722 $48,778 211 $105,491 $68,786 2011 8 $97,188 $42,500 225 $103,859 $70,129 2012 3 $163,333 $31,500 167 $117,502 $69,248 2013 11 $130,591 $57,273 290 $117,136 $69,831 2014 5 $118,000 $37,500 297 $127,478 $69,994 2015 7 $110,257 $53,357 328 $129,115 $72,527 2016 7 $127,841 $51,857 271 $134,928 $75,915 2017 5 $176,490 $55,000 275 $130,787 $80,345
Examining the breakeven point, that point where the starting salary and debt from veterinary
college yield an NPV of zero, provides the best perspective on the effect of opportunity cost on
NPV (Table 62). Because of the difference between earning paths of men and women, these
tables are provided by gender. The NPV tables by gender allow a veterinary student to identify
37 Source: AVMA Senior Survey, 2001-2017
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the NPV that represents the mean for the profession based on their starting debt and income
level, and, of course, gender. Based on this table, and given the mean debt and starting salary
of the small number of observations of equine practitioners, an individual’s NPV can be
identified. On the left of the table a value of debt is provided and on the right side of the table
the income necessary, given the level of debt in the same row, that is required to obtain a zero
NPV. This table indicates that for both men and women, approximately $2,000 in starting
salary is sufficient to offset an increase in $50,000 of debt to maintain the same NPV.
Table 62: Debt-to-Income and Net Present Value by Gender38
Male
Debt Income
Break-even income:
$30,000 $40,000 $50,000 $60,000 $65,000 $ - -1,120,876 -840,868 -560,860 -280,853 -140,849 $70,030
$50,000 -1,175,639 -895,631 -615,623 -335,615 -195,612 $71,986 $100,000 -1,230,402 -950,394 -670,386 -390,378 -250,375 $73,942 $150,000 -1,285,165 -1,005,157 -725,149 -445,141 -305,138 $75,898 $200,000 -1,339,928 -1,059,920 -779,912 -499,904 -359,901 $77,854 $250,000 -1,394,691 -1,114,683 -834,675 -554,667 -414,663 $79,809 $300,000 -1,449,454 -1,169,446 -889,438 -609,430 -469,426 $81,765 $400,000 -1,558,980 -1,278,972 -998,964 -718,956 -578,952 $85,677
Break-even debt:
n/a n/a n/a n/a n/a
38 Source: 2016 AVMA Report on The Market for Veterinarians
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Male, continued
Debt Income Break-even income:
$70,000 $75,000 $80,000 $90,000 $100,000 $ - -845 139,159 279,163 559,171 839,179 $70,030
$50,000 -55,608 84,396 224,400 504,408 784,416 $71,986 $100,000 -110,371 29,633 169,637 449,645 729,653 $73,942 $150,000 -165,134 -25,130 114,874 394,882 674,890 $75,898 $200,000 -219,897 -79,893 60,111 340,119 620,127 $77,854 $250,000 -274,660 -134,656 5,348 285,356 565,364 $79,809 $300,000 -329,423 -189,419 -49,415 230,593 510,601 $81,765 $400,000 -438,949 -298,945 -158,941 121,067 401,075 $85,677
Break-even debt:
n/a $127,056 $254,883 $510,537 $766,192
Female
Debt Income Break-even
income: $30,000 $40,000 $50,000 $60,000 $65,000 $ - -680,031 -390,014 -99,998 190,019 335,028 $53,448
$50,000 -734,794 -444,777 -154,760 135,256 280,265 $55,337 $100,000 -789,557 -499,540 -209,523 80,493 225,502 $57,225 $150,000 -844,320 -554,303 -264,286 25,731 170,739 $59,113 $200,000 -899,083 -609,066 -319,049 -29,032 115,976 $61,001 $250,000 -953,846 -663,829 -373,812 -83,795 61,213 $62,890 $300,000 -1,008,609 -718,592 -428,575 -138,558 6,450 $64,778 $400,000 -1,118,135 -828,118 -538,101 -248,084 -103,076 $68,554
Break-even debt: n/a n/a n/a $173,500 $409,737
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Female, continued
Debt Income Break-even
income: $70,000 $75,000 $80,000 $90,000 $100,000 $ - 480,036 625,045 770,053 1,060,070 1,350,087 $53,448
$50,000 425,273 570,282 715,290 1,005,307 1,295,324 $55,337 $100,000 370,510 515,519 660,527 950,544 1,240,561 $57,225 $150,000 315,747 460,756 605,764 895,781 1,185,798 $59,113 $200,000 260,984 405,993 551,001 841,018 1,131,035 $61,001 $250,000 206,222 351,230 496,238 786,255 1,076,272 $62,890 $300,000 151,459 296,467 441,475 731,492 1,021,509 $64,778 $400,000 41,933 186,941 331,950 621,966 911,983 $68,554
Break-even debt: $438,290 $570,680 $703,078 $967,870 $1,232,666
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4.5 EQUINE VETERINARY PROFESSION EMPLOYMENT
This report discusses four types of employment status:
1) Currently employed in private clinical veterinary medicine. This respondent is currently
working in private practice, a category that includes equine medicine, mixed animal
medicine, companion animal medicine, food animal medicine, or some other type of
animal medicine.
2) Employed, but not in private clinical veterinary medicine. This respondent is not working
in private practice but is working in a college or university, local, state or Federal
government, industry or commercial organization, not-for-profit organization,
uniformed services, non-veterinary employment, or some other form of veterinary
employment. These respondents may have a role as a professor (assistant, associate or
full), executive (chief executive officer/vice president/chief administrator/dean),
manager (division director/department chair/section head), clinician, researcher,
consultant, or some other position.
3) Retired from the general workforce. This respondent is no longer working in the general
workforce.
4) Unemployed. This respondent currently does not hold a job due to certain
circumstances.
Slightly more than four-fifths (80.5 percent) of Equine respondents were employed in clinical
veterinary medicine (AVMA: 67.0 percent); 11.4 percent were employed but not in clinical
veterinary medicine (AVMA: 23.6 percent); 6.6 percent were retired (AVMA: 6.0 percent); and
1.5 percent were unemployed (AVMA: 3.4 percent) (Table 63).
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Table 63: Distribution of Equine and AVMA Respondents by Employment Status
Current Employment Status Equine AVMA
Employed in clinical veterinary medicine 735 80.5% 1,697 67.0% Employed, but not in clinical veterinary medicine 104 11.4% 598 23.6% Retired from the general workforce 60 6.6% 87 6.0% Unemployed 14 1.5% 152 3.4% Total 913 100.0% 2,534 100.0%
Of the Equine respondents who were not practicing in clinical veterinary medicine,
approximately 71 percent were in professor roles (AVMA: 26.1 percent) and 24.7 percent in a
clinician position (AVMA: 19.4 percent), followed by 2.2 percent of respondents who were
managers (AVMA: 21 percent), and 2.2 percent in another type of field (AVMA: 26.8 percent).
Though none of the Equine respondents reported being executives or researchers, 2.5 percent
of AVMA respondents reported being the former, and 4.2 percent the latter (Table 64).
Table 64: Distribution of Equine and AVMA Respondents by Type of Position in a Non-Clinical Veterinary Medicine Role
Non-Clinical Vet Medicine Role Equine AVMA
Professor 66 71.0% 113 26.1% Executive 0 0.0% 11 2.5% Manager 2 2.2% 91 21.0% Clinician 23 24.7% 84 19.4% Researcher 0 0.0% 18 4.2% Other 2 2.2% 116 26.8% Total 93 100% 433 100.0%
The number of hours per week respondents currently work (regular plus emergency hours)
varied widely, ranging from four hours to 142 hours for Equine respondents and one hour to
168 hours (the maximum number of hours in a week) for AVMA respondents. However, the
mean hourly work week for Equine respondents was 54.9 hours for males and 56.6 hours for
females with the majority (60.4 percent) between 40 and 60 hours per week. For the AVMA
survey respondents, the mean hourly work week was 48.5 hours for males and 45.9 hours for
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females, with the majority (68.0 percent) of AVMA respondents between 40 and 60 hours per
week (Table 65).
Table 65: Mean Number of Hours Worked per Week (Regular and Emergency Hours) by Equine and AVMA Respondents by Gender
Obs. Mean Std. Dev. Min Max
Equine - Male 257 54.91 15.99 5 118 Equine - Female 340 56.59 17.69 4 142 AVMA - Male 626 48.48 15.43 4 168 AVMA- Female 1,512 45.94 15.40 1 140
Figure 74 displays the percentage of hours (regular plus emergency) worked by female and
males. Of male Equine respondents, 89.5 percent and 89.4 percent of female Equine
respondents reported working more than 40 hours a week. By comparison, 80.8 percent of
male AVMA respondents and 78.3 percent of female AVMA respondents reported working
more than 40 hours a week.
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+
% o
f Res
pond
ents
Number of Hours per Week
Distribution of Equine Respondents' Number of Hours Worked Per Week (Regular and Emergency Hours) by Gender
Male (n=257) Female (n=340)
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Figure 74: Distribution of Equine and AVMA Respondents’ Number of Hours Worked per Week (Regular and Emergency Hours) by Gender
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+
% o
f Res
pond
ents
Number of Hours per Week
Distribution of AVMA Respondents' Number of Hours Worked Per Week (Regular and Emergency Hours) by Gender
Male (n=792) Female (n=1,463)
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4.5.1 Full-Time and Part-Time Employment
Full-time employment is classified in this report as respondents who worked 30 or more regular
hours, emergency hours, or a combination of both during the normal work week in 2015. Part-
time is classified as respondents who worked fewer than 30 regular hours, emergency hours, or
a combination of both during the work week. Statistics were drawn from Equine respondents
who were actively practicing in an equine practice (equine practitioners) and AVMA
respondents who were working in a private veterinary practice (also referred to in this report as
clinical veterinary medicine).
Among those in clinical veterinary medicine, 94.6 percent of Equine respondents reported
working full time and the remaining 5.4 percent were employed part time. In the AVMA
sample, 89.0 percent were employed full time and 11.0 percent were employed part time in
clinical veterinary medicine (Figure 75).
Figure 75: Distribution of Equine and AVMA Respondents Full- and Part-Time Employment Status in Clinical Veterinary Medicine
94.6%89.0%
5.4%11.0%
Equine (n=520) AVMA (n=1,685)
% o
f Res
pond
ents
Employment Status
Distribution of Respondents' Full- & Part-Time Employment Status in Clinical Veterinary Medicine
Full-Time Part-Time
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4.5.1.1 Full-Time
Regular Hours
The number of regular hours worked per week by Equine respondents employed full time in
equine medicine averaged 49.3 hours, while for AVMA respondents the average was 43.7 hours
per week (Table 66). The distribution of regular work hours by the Equine and AVMA samples
who are employed full time indicates that in all categories of hours worked, there was a higher
percentage of Equine respondents than AVMA respondents (Figure 76).
Table 66: Distribution of Full-Time Employee Equine and AVMA Respondents’ Regular Hours Worked per Week in Clinical Veterinary Medicine
Obs. Mean Std. Dev. Min Max
Equine 492 49.30 11.53 20 110 AVMA 1,471 43.72 10.51 0 100
Figure 76: Distribution of Equine and AVMA Respondents’ Regular Hours Worked per Week in Clinical Veterinary Medicine
0.2%
4.9%25.2%
41.3%19.3% 9.1%
2.3%
4.6%41.4%
38.1%10.4% 3.3%
0-20 hours 21-30 hours 31-40 hours 41-50 hours 51-60 hours 60 + hours
% o
f Res
pond
ents
Hours per Week
Distribution of Respondents' Regular Hours Worked per Week in Clinicial Veterinary Medicine
Equine (n=492) AVMA (n=1,537)
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Emergency Hours
On average, Equine respondents employed full time worked 10.0 emergency hours during a
typical week compared to 7.1 hours for full-time AVMA respondents (Table 67).The distribution
of emergency work hours by the Equine and AVMA samples who are employed full time
indicates that in all categories of hours worked above 30 hours there was a higher percentage
of Equine respondents than there were AVMA respondents (Figure 77). In other words,
emergency work constitutes a higher percentage of total working hours per week for Equine
than for AVMA respondents.
Table 67: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked during a Typical Week
Obs. Mean Std. Dev. Min. Max.
Equine 457 10.04 11.68 0 156 AVMA 1,281 7.05 11.69 0 128
Figure 77: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked per Week in Clinical Veterinary Medicine as a Percentage of Total Hours Worked
7.2%31.3%
35.4% 13.1% 5.9% 7.0%
30.8%35.1%
18.9% 5.4% 3.1% 6.8%
0-20 hours 21-30 hours 31-40 hours 41-50 hours 51-60 hours 60 + hours
% o
f Res
pond
ents
Total Hours Worked per Week
Distribution of Respondents' Emergency Hours Worked per Week in Clinical Veterinary Medicine as a Percentage of
Total Hours Worked
Equine (n=457) AVMA (n=1,281)
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4.5.1.2 Part-Time
Regular Hours
The number of regular hours worked per week for part-time employees averaged 14.7 hours
for Equine and 19.0 hours per week for AVMA respondents (Table 68). The maximum number
of hours worked by a part-time Equine respondent(s) was 28 hours, and 29 hours for an AVMA
respondent(s). The distribution of regular work hours by the Equine and AVMA sample
respondents who were employed part time indicates that in all categories of hours worked
above 10 hours, there was a smaller percentage of Equine respondents than there were AVMA
respondents (Figure 76).
Table 68: Distribution of Equine and AVMA Respondents’ Part-Time Regular Hours Worked per Week in Clinical Veterinary Medicine Emergency Hours
Obs. Mean Std. Dev. Min. Max.
Equine 27 14.67 8.44 0 28 AVMA 181 18.96 6.52 0 29
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Figure 78: Distribution of Equine and AVMA Respondents’ Part-Time Regular Hours Worked per Week in Clinical Veterinary Medicine
Questions were asked of both the Equine and AVMA samples about whether their part-time
work should be classified as emergency coverage, regular part-time, relief coverage, semi-
retired, or some other type of part-time work at their place of employment. The respondents
selected all that applied. 58.3 percent of part-time Equine respondents reported being semi-
retired and 41.7 percent reported working regular part-time hours. AVMA respondents
reported 68 percent working regular part-time hours and 22.2 percent relief coverage (Table
69).
Table 69: Distribution of Part-Time Equine and AVMA Respondents’ Type of Employment (select all that apply)
Type of Part-Time Employment Equine (n=24) AVMA (n=153)
Semi -Retired 58.3% 15.7% Regular Part Time 41.7% 68.0% Other 16.7% 4.6% Relief Coverage 12.5% 22.2% Emergency Coverage 8.3% 2.0%
7.4% 11.1%18.5% 40.7%
22.2%
0.6% 1.7%14.4% 43.1%
40.3%
0 hrs 1-5 hrs 6-10 hrs 11-20 hrs 21-29 hrs
% o
f Res
pond
ents
Hours per Week
Distribution of Respondents' Regular Part-Time Hours Worked per Week in Clinical Veterinary Medicine
Equine (n=27) AVMA (n=181)
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Emergency Hours
On average, Equine respondents employed part time worked four emergency hours during a
typical week , compared to 1.9 hours for AVMA respondents employed part time (Table 70).
The maximum number of emergency hours worked by an Equine respondent(s) was 16 hours,
and 24 hours for an AVMA respondent(s). The distribution of emergency work hours by the
Equine and AVMA samples who were employed part time indicates that in several categories of
hours of emergency work there was a higher percentage of Equine respondents than there
were AVMA respondents (Figure 79).
Table 70: Distribution of Equine and AVMA Respondents’ Emergency Hours Worked during a Typical Week
Obs. Mean Std. Dev. Min. Max.
Equine 22 4.01 4.47 0 16 AVMA 119 1.93 3.98 0 24
Figure 79: Distribution of Equine and AVMA Respondents’ Part-Time Emergency Hours Worked per Week in Clinical Veterinary Medicine
31.8%
50.0%4.5%
13.6%
62.2%
27.7%5.9%
3.4%
0.8%
0 hrs 1-5 hrs 6-10 hrs 11-20 hrs 21-29 hrs
Distribution of Respondents' Part-Time Emergency Hours Worked per Week in Clinical Veterinary Medicine
Equine (n=22) AVMA (n=119)
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4.5.1.3 On-call/Emergency Duty
Only the AAEP sample was asked about on-call/emergency duty. On average, approximately 49
percent of on-call or emergency duty was performed by an AAEP respondent at their place of
employment where they were working full time in equine practice. Among AAEP respondents,
65.2 percent performed more than 25 percent of the on-call/emergency duty in their practice,
and 32.6 percent were responsible for more than half of the needed on-call/emergency duty
(Figure 80).
Figure 80: Distribution of Equine Respondents and the Percentage of the Total Amount of On-Call/Emergency Duty That They Perform at Their Place of Employment
Equine veterinarians who are solo practitioners can be on call or performing emergency duty
100 percent of the time. Among 72 solo practitioners, 46 (63.9 percent) were on call or
performed emergency duty 100 percent of the time. The higher the number of full-time
equivalent (FTE) veterinarians at the place of a respondent’s employment, the more likely
respondents reported lower on-call/emergency duty percentages: 1-1.5 FTE reported an
average of 67.1 percent on-call/emergency duty at their place of employment while
9.5% 9.2%
16.2%
32.6%
4.0% 3.7%
24.9%
0% 1-10% 11-25% 26-50% 51-75% 76-99% 100%
% o
f Res
pond
ents
Percent of On-call/Emergency Duty
Distribution of Equine Respondents and the Percentage of the Total Amount of On-Call/Emergency Duty That They
Perform at Their Place of Employment (n=402)
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respondents with more than six FTE veterinarians reported on average 30.2 percent of on-call
or emergency duty (Figure 81).
Figure 81: Distribution of Equine Respondents and the Percentage of the Total Amount of On-Call/Emergency Duty That They Perform at Their Place of Employment by Number of Veterinarians at Their Place of Employment
4.5.2 Summary Statistics
The mean number of weeks it took for Equine respondents to find their current job was 6.7
weeks. AVMA respondents reported a mean of 7.5 weeks to find their current job (Table 71).
Table 71: Mean Number of Weeks It Took Equine and AVMA Respondents to Find Their Current Job
Obs. Mean Std. Dev. Min. Max.
Equine 433 6.67 10.33 0 75 AVMA 2,142 7.46 17.93 0 312
67.1%
46.0%38.8% 35.7% 32.5% 30.2%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
1-1.5 FTE 2-2.5 FTE 3-3.5 FTE 4-4.5 FTE 5-5.5 FTE 6 + FTE
% o
f Res
pond
ents
Number of Veterinarians (Full-Time Equivalent)
Distribution of Equine Respondents and the Percentage of the Total Amount of On-Call/Emergency Duty That They Perform at Their Place of Employment
by Number of Veterinarians at Their Place of Employment (n=433)
On Call/Emergency Duty
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The largest percent of Equine respondents (44.9 percent) have been with their current
employer for less than five years (AVMA: 62.8 percent), less than 20 percent have been with
their employer for 6-10 years (AVMA: 14.9 percent) and 39.7 percent of Equine respondents
(AVMA: 22.3 percent) have been with their employer for more than 10 years (Figure 82).
Figure 82: Distribution of Equine and AVMA Respondents by Years with Current Employer
Equine respondents on average received at least one other job offer before deciding to accept
employment with their current employer, while AVMA respondents had about two other job
offers before choosing their current place of employment (Table 72). The majority of Equine
respondents worked an average of 48 weeks during the year at their current job (Table 73) and
AVMA respondents worked on average approximately 47 weeks.
Table 72: Distribution of Equine and AVMA Respondents’ Number of Job Offers Received before Choosing Their Current Employment
Obs. Mean Std. Dev Min Max
Equine 455 1.20 1.42 0 10 AVMA 2,149 1.59 1.70 0 25
44.9%
15.4%
39.7%
62.8%
14.9%22.3%
Less than 5 years 6-10 years More than 10
% o
f Res
pond
ents
Number of Years
Distribution of Respondents by Years with Current Employer
Equine (n=766) AVMA (n=2,264)
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Table 73: Distribution of Equine and AVMA Respondents’ Number of Weeks Worked in 2015
Obs. Mean Std. Dev Min Max
Equine 771 47.70 7.17 0 52 AVMA 2,238 47.25 7.27 0 52
4.5.3 Employment Satisfaction
Respondents were asked to rate their satisfaction with their employment on a scale of one to
five : 1 - Not all satisfied, 2 - Not too satisfied, 3 - Moderately Satisfied, 4 - Very Satisfied, and 5 -
Extremely Satisfied.
Among Equine respondents, 77.7 percent (AVMA: 69.4 percent) of males reported being very,
to extremely satisfied with their employment and 65.7 percent (AVMA: 59.0 percent) of
females reported being very to extremely satisfied with their employment. Women in the
Equine and AVMA samples showed a higher frequency of being moderately to not too satisfied
with their employment compared to males. The overall trend of respondents showed a slightly
higher satisfaction quotient among the Equine respondents then the AVMA respondents (Table
74).
Table 74: Distribution of Equine and AVMA Respondents’ Satisfaction with Current Employment by Gender
Equine (n=764) AVMA (n=2,157)
Male Female Male Female Not at all satisfied 0.9% 1.3% 1.3% 1.8% Not too satisfied 3.5% 6.3% 5.2% 7.1% Moderately satisfied 17.9% 26.7% 24.1% 32.0% Very satisfied 36.2% 37.9% 42.8% 39.4% Extremely satisfied 41.5% 27.8% 26.6% 19.6%
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The effect of employment satisfaction was examined with respect to respondents’ gender and
was statistically significant ((p-value <.001). Equine respondent males had a greater mean
satisfaction (4.14) than females (3.85). For the AVMA sample, male mean satisfaction was
lower than that of the Equine males (3.88) and AVMA females’ mean satisfaction (3.68) was
lower than thethe Equine females’ (Table 75).
Table 75: Effect of Equine and AVMA Respondents’ Employment Satisfaction by Gender
N Mean Std. Dev. N Mean Std. Dev. Pr > |t|
Male Female Equine 318 4.14 0.89 446 3.85 0.95 0.00 AVMA 631 3.88 0.90 1,526 3.68 0.93 0.00
Employment satisfaction was also related to graduation year (years of experience), with the
respondents in both the Equine and AVMA samples reporting higher satisfaction levels (very to
extremely satisfied) as experience increased (Table 76).
Table 76: Distribution of Equine and AVMA Respondents’ Employment Satisfaction by Graduation Year
Equine (n=765) < 1966 1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Not at all satisfied 0.0% 0.0% 0.0% 1.4% 1.4% 1.8% 1.5% Not too satisfied 0.0% 2.1% 2.5% 5.0% 3.4% 7.3% 8.8% Moderately satisfied 0.0% 14.6% 15.6% 21.6% 18.5% 29.1% 33.1% Very satisfied 33.3% 33.3% 41.0% 34.5% 39.0% 36.4% 36.0% Extremely satisfied 66.7% 50.0% 41.0% 37.4% 37.7% 25.5% 20.6%
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AVMA (n=2,243) < 1966 1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Not at all satisfied 6.7% 0.0% 0.0% 0.3% 1.6% 2.1% 2.9% Not too satisfied 0.0% 3.2% 2.0% 6.2% 6.5% 6.5% 8.2% Moderately satisfied
13.3% 17.7% 19.6% 28.7% 33.2% 32.3% 29.5%
Very satisfied 26.7% 46.8% 41.8% 40.2% 35.0% 40.0% 43.7% Extremely satisfied
53.3% 32.3% 36.6% 24.6% 23.6% 19.1% 15.8%
The year of graduation of a respondent (p <.001) was a significant factor in the satisfaction level
of both Equine and AVMA respondents. The mean of employment satisfaction reported by
respondents increased the longer the respondents had been out of veterinary school (Table
77).
Table 77: Mean Employment Satisfaction of Equine and AVMA Respondents by Year of Graduation
Equine N Mean Std. Dev.
< 1967 9 4.67 0.50 1967-1976 48 4.31 0.80 1977-1986 122 4.20 0.79 1987-1996 139 4.01 0.96 1997-2006 146 4.08 0.91 2007-2011 165 3.76 0.97 2012-2016 136 3.65 0.92
AVMA N Mean Std. Dev.
< 1967 2 5 0 1967-1976 21 4.00 1.00 1977-1986 89 4.17 0.80 1987-1996 174 3.99 0.82 1997-2006 352 3.80 0.89 2007-2011 633 3.71 0.95 2012-2016 972 3.65 0.94
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When practice owners and associates were asked about employment satisfaction, 49.4 percent
of Equine respondent practice owners were extremely satisfied with their employment versus
20.2 percent of Equine associates. Among AVMA respondents, 45.2 percent of owners were
extremely satisfied versus 15.4 percent of associates. More than 40 percent of respondents in
both the Equine and AVMA samples who were not practice owners reported being not at all
satisfied to moderately satisfied with their employment. This contrasts with about 20 percent
of practice owner respondents in both samples who reported this level of satisfaction (Table
78).
Table 78: Distribution of Equine and AVMA Respondents’ Employment Satisfaction by Practice Owners and Associates
Equine (n=597) AVMA (n=1,577)
Practice Owner Associate Practice Owner Associate Not at all satisfied 0.3% 2.7% 0.0% 2.6% Not too satisfied 2.7% 8.4% 3.7% 7.9% Moderately satisfied 13.8% 31.2% 17.9% 32.9% Very satisfied 33.8% 37.6% 33.1% 41.1% Extremely satisfied 49.4% 20.2% 45.2% 15.4%
The satisfaction level of Equine and AVMA respondents was significant with regard to
ownership status (p <.001) (Table 79). On average, both Equine and AVMA respondents who
owned a practice reported they are very satisfied with their employment (Equine: 4.29; AVMA:
4.20) versus non-owner respondents (Equine: 3.64; AVMA: 3.59).
Table 79: Mean Employment Satisfaction of Equine and AVMA Respondents by Practice Owners and Associates
Practice Owner Associate
N Mean Std. Dev. N Mean Std. Dev. Pr > |t| Equine 334 4.29 0.83 263 3.64 0.98 0.00 AVMA 429 4.20 0.86 1,148 3.59 0.93 0.00
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Factors Affecting Employment Satisfaction
The difference in mean employment satisfaction level was examined with gender, year of
graduation (years of experience in the veterinary field), practice ownership, education
preparation, highest educational degree obtained, income, type of practice, internship and
residency participation, hours worked per week, full-time status, and compensation method. In
addition, type of employment was added to the AVMA sample model. An ordered logit was
used to test the ability of these specific variables.
Ordered logits are used for ordinal variables, such as the levels of employment satisfaction
(ranked 1 -5). Like the binary logit (as explained earlier in this report), the main criterion to be
observed is whether the coefficient is positive or negative. This will indicate the direction of the
relationship (i.e., negative is less likely to be satisfied with current employment and positive
more likely to be satisfied with current employment). Variables that significantly contribute to
predictive ability of the model would have a p-value of .10 or less in the column labeled “Sig.”
and the “Odds Ratio” is the odds ratio for each of the independent variables and is defined as
“the change in odds of being in one of the categories of outcome when the value of one of the
independent variables (predictors) increases by one point.”39 To interpret the odds ratio, the
odds ratio value is subtracted by one to obtain the likelihood of the event occurring.
To avoid statistical errors, baseline variables are used to compare against. The baseline
variables are private practice owned by a single veterinarian (AAEP model), sole proprietary
private practice with veterinarian(s) (AVMA model), salary compensation method, and
companion animal exclusive practice (AVMA model).
39 Barbara G. Tabachnick and Linda S. Fidell. Using Multivariate Statistics, 6th Edition (New York City, New York: Pearson, 2013), pg.8.
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According to the AAEP model (Table 80), there were several significant variables: practice
ownership, gender, education preparation, residency participation, DVM only (no additional
degree), income, private practice/private corporation, and owner compensation with
differentiation. The significant variables had a positive relationship with employment
satisfaction, except for respondents who participated in a residency, in which there was a
negative relationship with employment satisfaction. In the AVMA model, significant variables
with a positive relationship were practice ownership, education preparation, DVM only, and
income. AVMA model variables with a negative relationship were specialty degree and
residency participation.
As an example of interpretation, the odds of higher satisfaction are 2.70 greater (.59 greater in
the AVMA model) for AAEP respondents who own a practice compared to non-practice owners,
given the other variables are held constant in the model. For respondents with higher
education preparation, the odds of higher satisfaction versus the combined effect of other
levels of satisfaction is 1.39 greater (1.70 in the AVMA model), given all the other variables are
held constant. In the AAEP sample, for respondents who participated in a residency compared
to respondents who did not particpate in a residency, the odds of higher satisfaction versus the
combined effect of other levels of satisfaction is .43 lower (.35 lower in the AVMA model), given
all the other variables are held constant.
Table 80: Effect of Employment Satisfaction
Equine Coefficient Std. Error Sig. Odds Ratio
Practice Ownership (Yes=1) 0.994 0.274 0.00*** 2.70 Gender (Female=1) 0.699 0.233 0.00*** 2.01 Graduation Year 0.012 0.010 0.25 1.01 Education Preparation (5=Extremely well/1=Not well at all)
0.326 0.124 0.01*** 1.39
Bachelor’s (baseline) Omitted Ph.D. -0.498 0.911 0.59 0.61
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Master’s 0.285 0.271 0.29 1.33 Specialty Degree 0.028 1.100 0.98 1.03 DVM only 0.570 0.273 0.04** 1.77 Internship (Yes=1) 0.295 0.204 0.15 1.34 Residency (Yes=1) -0.562 0.288 0.05** 0.57 Income 0.000 0.000 0.00*** 1.00 Hours worked -0.003 0.003 0.38 1.00 Full-Time (Yes=1) 0.432 0.427 0.31 1.54 Private practice owned by a single veterinarian (baseline)
Omitted
Private practice/private corporation 0.342 0.195 0.08* 1.41 Salary (baseline) Omitted Hourly or per diem -0.169 0.687 0.81 0.84 Production only 0.241 0.311 0.44 1.27 Salary with production-based incentive 0.028 0.254 0.91 1.03 Other method -0.406 0.518 0.43 0.67 Salary without production-based incentive 0.625 0.825 0.45 1.87 Owner with no differentiation 0.111 0.298 0.71 1.12 Owner with differentiation 0.779 0.389 0.05** 2.18
Observations 503
Pseudo R-Square 0.0959
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig. Odds Ratio
Practice Ownership (Yes=1) 1.246 0.171 0.00*** 0.59 Gender (Female=1) 0.106 0.119 0.38 1.11 Graduation Year -0.007 0.006 0.22 0.99 Education Preparation (5=Extremely well/1=Not well at all)
0.533 0.066 0.00*** 1.70
Bachelor’s Ph.D. -0.124 0.241 0.61 0.88 Master’s -0.169 0.151 0.26 0.84 Specialty Degree -2.906 1.073 0.01*** 0.05
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DVM only 0.358 0.171 0.04** 1.43 Internship (Yes=1) -0.050 0.129 0.70 0.95 Residency (Yes=1) -0.437 0.212 0.04** 0.65 Income 0.000 0.000 0.00*** 1.00 Hours worked -0.002 0.004 0.61 1.00 Full-Time (Yes=1) -0.081 0.200 0.69 0.92 Salary (baseline) Omitted Hourly -0.099 0.191 0.61 0.91 Production 0.190 0.179 0.29 1.21 Mix of salary with opportunity for production-based compensation
0.158 0.122 0.20 1.17
Owner withdrawals -0.083 0.195 0.67 0.92 Companion Animal (baseline) Omitted Food Animal 0.197 0.320 0.54 1.22 Equine 0.167 0.239 0.49 1.18 Mixed Animal -0.041 0.190 0.83 0.96 Federal Government -0.330 0.491 0.50 0.72 Uniformed Services -0.736 1.610 0.65 0.48 College/University 0.594 0.446 0.18 1.81 State/Local Government 0.693 0.686 0.31 2.00 Industry/Commercial Organization 0.315 0.640 0.62 1.37 Not-for-profit 0.510 0.571 0.37 1.67 Advanced Education -0.059 0.422 0.89 0.94 Other veterinary employment 0.467 0.305 0.13 1.60 Non-veterinary employment 0.082 0.686 0.91 1.09
Observations 1,542
Pseudo R-Square 0.0591
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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Remain Employed
Another unique question asked of AAEP respondents was if they were likely to remain
employed at their organization over the next five years. The majority of AAEP respondents
reported that it was very to extremely likely that they would stay at their current job over the
next five years (Male: 72.9 percent; Female: 66.3 percent) (Figure 83). A sizeable group of
respondents, however, reported they are only moderately likely to not at all likely to stay
employed within the next five years at their current employment (25.7 percent of males and
31.2 percent of females).
Figure 83: Distribution of AAEP Respondents’ Likelihood That They Will Choose to Remain Employed at Their Organization over the Next Five Years by Gender
When the likelihood of staying at their organization over the next five years is shown with
respect to graduation year (Figure 84), 42.8 percent of AAEP respondents revealed that they
are not at all likely to moderately likely to want to stay at their job if they entered the
veterinary workforce within the last five years. Of those, 26.7 percent reported they were not
very likely to not at all likely to remain in their present position. 18.5 percent of AAEP
Not at alllikely
Not verylikely
Moderatelylikely Very likely Extremely
likely Not sure
Male (n=288) 3.1% 10.8% 11.8% 21.9% 51.0% 1.4%Female (n=401) 5.7% 8.2% 17.2% 24.2% 42.1% 2.5%
% o
f Res
pond
ents
Liklihood of Staying at Current Job
Distribution of AAEP Respondents' Likelihood That They Will Choose to Remain Employed at Their Organization over the Next Five Years by
Gender
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respondents who graduated between 2011 and 2007 reported the same. 85.7 percent of those
Equine respondents who graduated in 1967 or before reported they are extremely likely to very
likely to remain in their current employment. The occurrence of AAEP respondents reporting
they are extremely likely to stay at their workplace is more than 50 percent for those who
graduated between 1977-2006.
Figure 84: Distribution of AAEP Respondents' Likelihood That They Will Choose to Remain Employed at Their Organization over the Next Five Years by Graduation Year
About two-thirds of the AAEP respondents indicated that they had a previous employer. The
distribution of how long these AAEP respondents had been employed at their most recent
previous place of employment prior to respondents’ current employment is provided with
respect to the year they graduated from veterinary school (Figure 85).
< 1967 1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Not sure 0.0% 2.1% 0.8% 3.2% 1.6% 0.7% 4.5%Extremely likely 57.1% 42.6% 52.1% 57.9% 54.3% 37.7% 26.8%Very likely 28.6% 14.9% 26.1% 21.4% 20.9% 25.3% 25.9%Moderately likely 0.0% 21.3% 11.8% 10.3% 16.3% 17.8% 16.1%Not very l ikely 14.3% 17.0% 5.9% 4.8% 3.9% 10.3% 19.6%Not at all likely 0.0% 2.1% 3.4% 2.4% 3.1% 8.2% 7.1%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
by
Likl
ihoo
d
Year of Graduation
Distribution of AAEP Respondents' Likelihood That They Will Choose to Remain Employed at Their Organization over the Next Five Years by Graduation Year
(n=686)
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Figure 85: Distribution of AAEP Respondents' Length of Time with Most Recent Previous Place of Employment
< 1967 1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
10 years or more 0.0% 52.9% 31.7% 11.0% 4.5% 0.0% 0.0%6-10 years 25.0% 23.5% 16.8% 30.0% 23.6% 7.0% 0.0%Less than 5 years 75.0% 23.5% 51.5% 59.0% 71.9% 93.0% 100.0%
% o
f Res
pond
ents
Year of Graduation
Distribution of AAEP Respondents' Length of Time with Most Recent Previous Place of Employment (n=478)
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Level of Satisfaction with Previous Employment
Among AAEP respondents, 48.7 percent of males reported that they were very to extremely
satisfied at their previous place of employment compared to 28.9 percent of females; 39.2
percent of female respondents reported being not at all to not too satisfied, while 20.6 percent
of male respondents reported being not at all to not too satisfied; 30.8 percent of male
respondents and 31.9 percent of female respondents were moderately satisfied at their
previous place of employment (Figure 86).
Figure 86: Distribution of AAEP Respondents' Level of Satisfaction with Most Recent Previous Place of Employment by Gender
More than 40 percent of AAEP respondents that graduated from veterinary school in the last 10
years (2016-2012 and 2011-2007) were not at all to not too satisfied with their previous
employment. Satisfaction level increased as when respondents were 20 years out of veterinary
school (Figure 87).
3.6%17.1%17.0%
22.1%30.8%
31.9%
36.2%17.1%
12.5% 11.8%
Male (n=224) Female (n=263)
% o
f Res
pond
ents
Gender
Distribution of AAEP Respondents' Level of Satisfaction with Most Recent Previous Place of Employment by Gender
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Figure 87: Distribution of AAEP Respondents’ Level of Satisfaction with Most Recent Previous Place of Employment by Graduation Year
<1967
1967-1976
1977-1986
1987-1996
1997-2006
2007-2011
2012-2016
Extremely satisfied 40.0% 17.1% 18.8% 9.9% 6.7% 6.9% 19.2%Very satisfied 20.0% 34.3% 33.7% 33.7% 24.4% 14.9% 11.5%Moderately satisfied 40.0% 31.4% 30.7% 32.7% 31.1% 34.7% 23.1%Not too satisfied 0.0% 8.6% 15.8% 17.8% 23.3% 26.7% 21.2%Not at all satisfied 0.0% 8.6% 1.0% 5.9% 14.4% 16.8% 25.0%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Year of Graduation
Distribution of AAEP Respondents' Level of Satisfaction with Most Recent Previous Place of Employment by Graduation Year (n=485)
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Change Veterinary Sector
Equine respondents were asked if they could, would they change to a different veterinary
sector, and 83.3 percent indicated they would not (AVMA: 71.8 percent). When sorted by
gender, 13 percent of Equine males would change if they could the veterinary sector in which
they worked, compared to 19 percent of Equine females. Examining the respondents’ choices
in the context of satisfaction level with their current employment, 19.0 percent Equine
respondents (AVMA: 3.9 percent) who said they would if they could change their veterinary
sector were not at all satisfied with their current employment, and 13.6 percent of respondents
(AVMA: 27.2 percent) who said they would not change if they could their veterinary sector
were extremely satisfied with their current employment (Figure 88).
9.1% 19.0%19.8%
19.0%
31.4%31.0%
26.2%23.8%
13.6% 7.1%
No (n=405) Yes (n=84)
% o
f Equ
ine
Resp
onde
nts
Change Veterinary Sector
Distribution of Equine Respondents' Desire to Change the Veterinary Sector in Which They Currently Work (if they
could) by Current Employment Satisfaction
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Figure 88: Distribution of Equine and AVMA Respondents’ Desire to Change the Veterinary Sector in Which They Currently Work (if they could) by Current Employment Satisfaction
The distribution of Equine and AVMA respondents who prefer to change and not change their
veterinary sector if they could is illustrated by the year they graduated and generally indicates
that the fewer years from graduation, the more likely the respondent preferred to change
sectors (Figure 89). Among those Equine respondents that graduated from 2012-2016, just 21.3
percent reported they would like to change veterinary sectors if they could, compared to 31.1
percent of AVMA respondents.
3.9%4.0%13.0%
24.2%
44.1%43.8%
30.3%27.2%
8.8%
No (n=1,634) Yes (n=640)
% o
f AVM
A Re
spon
dent
s
Change Veterinary Sector
Distribution of AVMA Respondents' Desire to Change the Veterinary Sector in Which They Currently Work (if they
could) by Current Employment Satisfaction
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Figure 89: Distribution of Equine and AVMA Respondents’ Desire to Change the Veterinary Sector in Which They Currently Work (if they could) by Graduation Year
21.3%
33.1%
16.5%17.3%10.2%
1.6%0.0%
% o
f Res
pond
ents
Year of Graduation
Distribution of Equine Respondents' Desire to Change the Veterinary Sector in Which They Currently Work (if they
could) by Graduation Year (n=766)
No (n=639) Yes (n=127)
31.1%24.9%26.8%
13.4%3.0%0.5%0.3%
% o
f Res
pond
ents
Year of Graduation
Distribution of AVMA Respondents' Desire to Change the Veterinary Sector in Which They Currently Work (if they
could) by Graduation Year (n=2,242)
No (n=639) Yes (n=127)
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Factors Affecting Desire to Change Current Veterinary Sector
A binary logit regression was performed on several factors that might affect a respondent’s
desire to change the veterinary sector in which they work where 1=yes, a respondent would
change the veterinary sector in which they work if they could, and 0=no, if they would not if
they could. Factors that were used to attempt to explain a respondent’s desire to change their
veterinary sector were year of graduation, gender, practice ownership, full-time employment,
emergency and regular hours worked, change geographic location, relocate for better career
opportunities, satisfaction with current employment, satisfaction with compensation,
satisfaction with profession satisfaction with lifestyle, home ownership, and number of children
in household, and not married. Additionally, the variable of whether respondents would remain
employed with their current employer over the next five years and primary equine sector was
included in the AAEP sample.
The main measure to observe is whether the coefficient is positive or negative. The positive or
negative sign will indicate the direction of the relationship (i.e., negative is more likely to not
change veterinary sectors if they could and positive is a respondent would change veterinary
sectors if they could).
Factors that significantly contribute to predictive ability of the model would have a p-value of
.10 or less in the column labeled “Sig.” The “Odds Ratio” column presents the odds for each of
the independent variables that the event would occur (assuming respondents could change
veterinary sectors).
Results for AAEP respondents (Table 81) show a positive relationship between regular hours
worked during the work week, the desire to change geographic location, and Standardbred
racing with a desire to change veterinary sectors. For every one-unit increase in regular hours
worked for Equine respondents, the odds of desire to change veterinary sectors versus not
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changing veterinary sectors is 1.04 greater, given all other variables are held constant. For
respondents who desire to change their geographic location versus those who do not desire to
change their geographic location, the odds of desire to change veterinary sectors versus not
change veterinary sectors is 2.68 greater, given all other variables are held constant (1.51
greater in the AVMA model). For respondents in Standardbred racing versus the general equine
sector, the odds of desire to change veterinary sectors versus not changing veterinary sectors is
9.79 greater, given all other variables are held constant.
Variables that had a negative relationship with the desire to change veterinary sector were
practice ownership, emergency hours worked per week, and satisfaction with the profession.
For every one-unit increase in emergency hours worked for AAEP respondents, the odds of
desire to change veterinary sectors versus not changing veterinary sectors is .06 lower, holding
all other variables constant. The odds of desire of AAEP respondents changing veterinary
sectors decreases by a factor of .64 if they own a practice (versus those who do not), given
other variables are held constant in the model. For respondents who are more satisfied with
the veterinary profession as a whole versus the combined effect of other levels of satisfaction,
the odds are .33 lower than those less satisfied (.23 in the AVMA model), given all the other
variables are held constant.
In the AVMA model, positive significant variables were gender, change geographic location,
relocate, and children in the household. Negative significant variables were satisfaction with
current employment, satisfaction with profession, and satisfaction with lifestyle.
Table 81: Factors Affecting Respondents’ Desire to Change Current Veterinary Sector (if they could)
AAEP Coefficient Std. Error Sig. Odds Ratio
Gender (Female=1) 0.394 0.406 0.33 1.48 Graduation Year -0.020 0.019 0.28 0.98 Practice Ownership (Yes=1) -1.019 0.464 0.03** 0.36
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Satisfaction with current employment (5=Extremely satisfied/1=Not at all satisfied)
-0.380 0.241 0.11 0.68
Remain Employed (5=Extremely likely/1=Not at all likely)
-0.205 0.175 0.24 0.81
Full-Time (Yes=1) -1.405 0.901 0.12 0.25 Emergency hours worked -0.061 0.027 0.02** 0.94 Regular hours worked 0.043 0.017 0.01*** 1.04 Change geographic location (Yes=1) 0.987 0.368 0.01*** 2.68 Relocate (Yes=1) -0.333 0.402 0.41 0.72 Satisfaction with compensation (5=Extremely satisfied/1=Not at all satisfied)
-0.194 0.132 0.14 0.82
Satisfaction with profession (5=Extremely satisfied/1=Not at all satisfied)
-0.408 0.134 0.00*** 0.67
Satisfaction with lifestyle (5=Extremely satisfied/1=Not at all satisfied)
-0.227 0.146 0.12 0.80
Housing - own (baseline) Omitted Housing - rent -0.089 0.465 0.85 0.91 Housing - other 0.227 1.015 0.82 1.26 Not Married (Yes=1) -0.095 0.401 0.81 0.91 Children (Yes=1) -0.069 0.124 0.58 0.93 General equine (baseline) Omitted English performance -0.333 0.519 0.52 0.72 Companion 0.445 0.605 0.46 1.56 Standardbred racing 2.281 1.187 0.06* 9.79 Thoroughbred racing -1.961 1.211 0.11 0.14 Reproductive 0.100 0.692 0.89 1.11 Western performance 0.617 0.976 0.53 1.85 Constant 5.154 1.520 0.00*** 173.09
Observations 445
Pseudo R-Square 0.2839
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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Note: Ranch/working equine sector was omitted because the variable did not permit estimation.
AVMA Coefficient Std. Error Sig. Odds Ratio
Gender (Female=1) 0.360 0.168 0.03** 1.43 Graduation Year -0.007 0.009 0.40 0.99 Practice Ownership (Yes=1) -0.174 0.204 0.40 0.84 Satisfaction with current employment (5=Extremely satisfied/1=Not at all satisfied)
-0.516 0.089 0.00*** 0.60
Full-Time (Yes=1) -0.114 0.290 0.69 0.89 Emergency hours worked 0.001 0.007 0.92 1.00 Regular hours worked 0.002 0.006 0.74 1.00 Change geographic location (Yes=1) 0.410 0.143 0.00*** 1.51 Relocate (Yes=1) 0.462 0.151 0.00*** 1.59 Satisfaction with compensation (5=Extremely satisfied/1=Not at all satisfied)
0.077 0.054 0.16 1.08
Satisfaction with profession (5=Extremely satisfied/1=Not at all satisfied)
-0.260 0.053 0.00*** 0.77
Satisfaction with lifestyle (5=Extremely satisfied/1=Not at all satisfied)
-0.106 0.060 0.08* 0.90
Housing - own (baseline) Omitted Housing - rent 0.252 0.172 0.14 1.29 Housing - other -0.136 0.445 0.76 0.87 Not Married (Yes=1) -0.154 0.166 0.36 0.86 Children (Yes=1) 0.342 0.164 0.04** 1.41 Constant 1.503 0.495 0.00*** 4.50
Observations 1297
Pseudo R-Square 0.1396
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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Change Geographic Location
When asked if they would change the geographic location in which they worked if they could,
28.9 percent of Equine respondents indicated they would, while 35.5 percent of the AVMA
sample expressed a similar sentiment. About one-quarter of male Equine respondents and
nearly one-third of the females desired to change geographic location if they could.
Of the respondents who reported that they were not at all satisfied, to moderately satisfied
with their work, 47.1 percent of the Equine respondents (AVMA: 48.1 percent) would change
their work location if they could, while 21.7 percent would not (AVMA: 32.3 percent). For those
who reported they were very satisfied to extremely satisfied, 52.9 percent (AVMA: 51.9
percent) would change their work location if they could, while 78.3 percent would not (AVMA:
67.7 percent) (Figure 90).
3.3% 9.9%17.5%
35.4%37.8%
35.4%
40.5%17.5%
No (n=548) Yes (n=223)
% o
f Res
pond
ents
Change Work Geographic Location
Distribution of Equine Respondents’ Desire to Change the Geographic Location in Which They Currently Work (if they
could) by Current Employment Satisfaction
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Figure 90: Distribution of Equine and AVMA Respondents’ Desire to Change the Geographic Location in Which They Currently Work (if they could) by Current Employment Satisfaction
For both the Equine and AVMA responses concerning changing, if they could, the geographic
location in which they worked, the distribution of percentage of respondents by the year they
graduated illustrates an increasing desire to change geographic location the more recent the
respondent’s graduation year (Figure 91).
26.6%35.4%
40.8%
38.6%
26.9%13.4%
No (n=1,445) Yes (n=830)
% o
f Res
pond
ents
Change Work Geographic Location
Distribution of AVMA Respondents' Desire to Change the Geographic Location in Which They Currently Work (if they
could) by Current Employment Satisfaction
Extremely satisfied
Very satisfied
Moderately satisfied
Not too satisfied
Not at all satisfied
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Figure 91: Distribution of Equine and AVMA Respondents’ Desire to Change the Geographic Location in Which They Currently Work (if they could) by Graduation Year
27.1%25.8%19.9%
13.1%10.0%3.6%0.5%
% o
f Res
pond
ents
Year of Graduation
Distribution of Equine Respondents’ Desire to Change the Geographic Location in Which They Currently Work
(if they could) by Graduation Year (n=765)
No Yes
31.0%
20.3%26.6%
16.3%
3.8%1.8%0.2%
% o
f Res
pond
ents
Year of Graduation
Distribution of AVMA Respondents’ Desire to Change the Geographic Location in Which They Currently Work
(if they could) by Graduation Year (n=2,243)
No Yes
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Factors Affecting Desire to Change Current Geographic Work Location
A binary logit regression was performed on several factors that might affect respondents’
desire to change the geographic location in which they work if they could, where 1=yes, a
respondent does want to change the geographic location in which they work if they could, and
0=no, a respondent does not want to change geographic location if they could. Factors that
were used to attempt to explain a respondent wanting to change geographic location are year
of graduation, gender and practice ownership, satisfaction with current employment, full-time
employment, emergency and regular hours worked, desire to change current sector, relocate
for better career opportunities, satisfaction with compensation, satisfaction with the veterinary
profession, satisfaction with current lifestyle, home ownership, number of children in
household, and marital status. Additionally, the variable of whether respondents would remain
employed with their current employer over the next five years was included in the AAEP sample
calculation.
The main measure to observe is whether the coefficient is positive or negative. This will indicate
the direction of the relationship (i.e., negative is more likely to not change geographic location
if they could and positive indicates would change geographic location if they could).
Variables that significantly contribute to predictive ability of the model would have a p-value of
.10 or less in the column labeled “Sig.” The “Odds Ratio” column lists the ratio of odds that the
event would occur for each of the independent variables (assuming that respondents could
change geographic location).
Results in Table 82 for the AAEP and AVMA respondents show a positive association with a
desire to change current sector and to relocate for better career opportunities. For respondents
who desire to change the current sector in which they work versus those who do not, and have
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a desire to relocate for better career versus those who do not, the odds of desire to change
geographic location versus not change geographic location are greater by 2.09 and 6.08 for
AAEP respondents and 1.47 and 4.26 greater for AVMA respondents, given all the other
variables are held constant.
Negative association with a desire to change geographic location included the AAEP model
variables renting a home and some other type of living arrangement, and the AVMA model
variables satisfaction with current employment, and satisfaction with current lifestyle. What
these negative associations mean is that for AAEP respondents who rent or have some other
type of living arrangement (versus those who own a home), the odds of desire to change
geographic location versus not change location are .57 and .89 lower, given all the other
variables are held constant. For AVMA respondents who are more satisfied with their current
employment versus the combined effect of other levels of satisfaction, the odds of desire to
change geographic location versus not changing geographic location are .18 lower, and for
respondents who are more satisfied with their current lifestyle versus the combined effect of
other levels of satisfaction, the odds of desire to change geograhic location versus not change
geographic location are .24 lower, given all the other variables are held constant.
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Table 82: Factors Affecting a Respondents’ Desire to Change the Geographic Location Where They Work
AAEP Coefficient Std. Error Sig. Odds Ratio
Gender (Female=1) -0.195 0.257 0.53 0.82 Graduation Year -0.018 0.015 0.24 0.98 Practice Ownership (Yes=1) -0.173 0.296 0.62 0.84 Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied)
-0.141 0.174 0.48 0.87
Remain Employed (5=Extremely likely/1=Not at all likely)
-0.229 0.112 0.11 0.80
Full-Time (Yes=1) 0.394 1.119 0.60 1.48 Emergency hours worked per week 0.003 0.005 0.54 1.00 Regular hours worked per week -0.017 0.013 0.18 0.98 Change current sector (Yes=1) 0.736 0.723 0.03** 2.09 Relocate for better career opportunities (Yes=1)
1.806 1.748 0.00*** 6.08
Satisfied with compensation (5=Extremely satisfied/1=Not at all satisfied)
0.032 0.104 0.75 1.03
Satisfied with profession (5=Extremely satisfied/1=Not at all satisfied)
-0.064 0.101 0.55 0.94
Satisfied with lifestyle (5=Extremely satisfied/1=Not at all satisfied)
-0.138 0.100 0.23 0.87
Housing - own (baseline) Omitted Housing - rent -0.854 0.154 0.02** 0.43 Housing - other -2.179 0.131 0.06* 0.11 Children (Yes=1) -0.306 0.215 0.30 0.74 Not Married (Yes=1) 0.453 0.482 0.14 1.57 Constant 1.387 5.156 0.28 4.00
Observations 453
Pseudo R-Square 0.2426
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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AVMA Coefficient Std. Error Sig. Odds Ratio
Gender (Female=1) 0.173 0.158 0.28 1.19 Graduation Year 0.009 0.008 0.28 1.01 Practice Ownership (Yes=1) 0.268 0.192 0.16 1.31 Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied)
-0.203 0.087 0.02** 0.82
Full-Time (Yes=1) -0.057 0.284 0.84 0.94 Emergency hours worked per week -0.011 0.007 0.13 0.99 Regular hours worked per week -0.007 0.006 0.28 0.99 Change current sector (Yes=1) 0.385 0.145 0.01*** 1.47 Relocate for better career opportunities (Yes=1)
1.449 0.143 0.00*** 4.26
Satisfied with compensation (5=Extremely satisfied/1=Not at all satisfied)
0.054 0.052 0.30 1.06
Satisfied with profession (5=Extremely satisfied/1=Not at all satisfied)
0.017 0.051 0.74 1.02
Satisfied with lifestyle (5=Extremely satisfied/1=Not at all satisfied)
-0.276 0.059 0.00*** 0.76
Housing - own (baseline) Omitted Housing - rent 0.226 0.167 0.18 1.25 Housing - other 0.452 0.417 0.28 1.57 Children (Yes=1) -0.018 0.159 0.91 0.98 Not Married (Yes=1) -0.181 0.159 0.26 0.83 Constant 0.338 0.482 0.48 1.40
Observations 1,297
Pseudo R-Square 0.1417
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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Relocation
Respondents indicated that they were relatively open to making a move to improve their
prospects: 51.4 percent of Equine respondents (AVMA: 46.2 percent) were willing to relocate
for better career opportunities; 42.9 percent of males and 57.6 percent of females were willing
to relocate in the Equine sample compared to 42.1 percent of males and 48.6 percent of
females in the AVMA sample. As shown in Figure 92, a majority of respondents in both surveys
expressed that they were willing to relocate to wherever jobs could be found (Equine: 74.7
percent; AVMA: 81.7 percent).
Figure 92: Distribution of Equine and AVMA Respondents’ Number of Miles They Are Willing to Relocate for Better Career Opportunities
Note: The 2016 AVMA-AAEP Equine Survey of Practitioners had one extra category, “Up to 500
miles,” whereas the 2016 AVMA Census of Veterinarians did not.
Practice size preferences were also examined in the survey, which found that among Equine
respondents, 67.3 percent preferred no change (AVMA: 72.9 percent) to the size of their
Up to 25miles
Up to 50miles
Up to 100miles
Up to 500miles
Whereverthe jobs
areEquine (n=396) 2.3% 2.0% 8.1% 12.9% 74.7%AVMA (n=1,173) 4.4% 5.1% 8.8% 0.0% 81.7%
% o
f Res
pond
ents
Number of Miles
Distribution of Respondents' Number of Miles They Are Willing to Relocate for Better Career Opportunities
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workplace; 25.5 percent would prefer a larger size workplace (AVMA: 19.2 percent), and 7.2
percent a smaller size workplace (AVMA: 8.0 percent).
In both the Equine and AVMA sample, those who graduated more recently indicated that they
preferred a larger workplace. The percentage of respondents who reported this preference
increased in a linear fashion with decreasing level of experience (fewer years from graduation)
(Figure 93). More than half of all respondents in each graduation category reported wanting no
change in practice size. Approximately 10 percent of respondents, those who graduated from
1967-1976 and 2012-2016, preferred a smaller workplace. 100 percent of Equine respondents
who graduated prior to 1967 preferred no change to the size of the workplace.
9.6%6.0%4.8%8.0%7.4%10.2%
56.6%59.6%69.9%71.5%76.2%75.5%100.0%
33.8%34.3%25.3%20.4%16.4%14.3%
2012-20162007-20111997-20061987-19961977-19861967-1976< 1967
% o
f Res
pond
ents
Year of Graduation
Distribution of Equine Respondents' Preferred Workplace Size by Graduation Year
Prefer smaller work place (n=55) Prefer no change (n=515)
Prefer larger work place (n=195)
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Figure 93: Distribution of Equine and AVMA Respondents’ Preferred Workplace Size by Graduation Year
When considering the size of community, 12.8 percent of Equine respondents and 9.3 percent
of AVMA respondents indicated that they would prefer a smaller community. Those who
preferred a larger community included 11.1 percent of Equine respondents and 15.4 percent of
AVMA respondents. More than three-quarters of respondents in both samples were content
with the size of community in which they currently work and preferred no change.
When looking at community size preference by gender, about 75 percent of both samples and
genders preferred no change in community size (Figure 94). However, 16.6 percent of Equine
males and 10.1 percent of Equine females preferred a smaller community compared to 11.1
percent of AVMA males and 8.3 percent of AVMA females. At the other end of the spectrum,
7.5 percent of Equine males and 13.7 percent of Equine females preferred a larger community,
compared to 15.4 percent for both male and female AVMA respondents.
8.4%5.9%8.9%10.0%5.2%8.2%
69.0%75.8%71.6%71.2%82.4%82.0%93.3%
22.6%18.3%19.5%18.8%12.4%9.8%6.7%
2012-20162007-20111997-20061987-19961977-19861967-1976< 1967
% o
f Res
pond
ents
Year of Graduation
Distribution of AVMA Respondents' Preferred Workplace Size by Graduation Year
Prefer smaller work place( n=178) Prefer no change( n=1,632)
Prefer larger work place (n=428)
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Figure 94: Distribution of Equine and AVMA Respondents’ Preference for Community Size by Gender
16.6% 10.1% 11.1% 8.3%
75.9% 76.2% 73.4% 76.4%
7.5% 13.7% 15.4% 15.4%
Equine - Male(n=320)
Equine - Female(n=446)
AVMA - Male(n=629)
AVMA - Female(n=1,523)
% o
f Res
pode
nts
Gender
Distribution of Respondents' Preference for Community Size by Gender
Prefer smaller community Prefer no change Prefer larger community
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4.5.4 Retirement
At the time this survey was conducted, 60 Equine respondents (6.6 percent) and 152 AVMA
respondents (6.0 percent) were retired. 72.9 percent of these Equine respondents retired in the
past five years. The largest proportion of retired AVMA sample respondents, 40.9 percent, left
their work in clinical veterinary medicine more than 11 years ago (Figure 95).
Figure 95: Distribution of Equine and AVMA Respondents Who Retired with Respect to Number of Years since Retirement
The difference between the current ages of respondents and their reported expected age of
retirement indicates that, among the AVMA sample, the largest number (30.7 percent) planned
to retire in 31 to 40 years while the Equine sample reflected a steady rate of expected
retirement over the next four decades (Figure 96).
6.8%
40.9%20.3%
27.3%72.9%
31.8%
Equine (n=59) AVMA (n=22)
% o
f Res
pond
ents
Years Since Retirement
Distribution of Respondents' Who Retired with Respect to Number of Years since Retirement
0-5 years
6-10 years
11 + years
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Figure 96: Distribution of Equine and AVMA Respondents’ Anticipated Years to Retirement
Respondents were asked about retirement decisions. Both samples revealed that the majority
of respondents retired from clinical veterinary medicine on or around their anticipated time
frame. However, only 50.8 percent of Equine respondents retired on or around their
anticipated time frame (AVMA: 71.8 percent) while 32.2 percent retired from clinical veterinary
medicine earlier than anticipated (AVMA: 18.5 percent) (Table 83).
Table 83: Distribution of Equine and AVMA Respondents’ Retirement Choice
Retirement Choice Equine (n=59) AVMA (n=124)
Retired earlier from clinical veterinary medicine than anticipated
32.2% 18.5%
Delayed retirement from clinical veterinary medicine to timeframe later than anticipated
16.9% 9.7%
Retired from clinical veterinary medicine on or around anticipated time frame
50.8% 71.8%
Total 100.0% 100.0%
0-10 years 11-20years
21-30years
31-40years
40 years ormore
Equine (n=724) 23.5% 20.0% 27.4% 25.7% 3.5%AVMA (n=2,061) 16.0% 19.1% 28.3% 30.7% 6.0%
% o
f Res
pond
ents
Anticipated Years to Retirement
Distribution of Respondents' Anticipated Years to Retirement
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The 19 Equine respondents and 23 AVMA respondents who reported retiring from clinical
veterinary medicine earlier than anticipated were asked ranking questions relative to possible
reasons for doing so: 1, not relevant at all, 2, slightly relevant, 3, moderately relevant, 4, very
relevant, and 5, extremely relevant.
Equine respondents reported an average 3.05 ranking for “improve work-life balance,” and a
3.00 ranking for “stress level” the two highest ranking reasons for retiring early from equine
clinical veterinary medicine (Table 84). AVMA respondents reported an average of 4.38, “for
other reasons,” and 3.19 for “improve work-life balance.”
Table 84: Distribution of Equine and AVMA Respondents’ Reasons for Retiring Earlier from Clinical Veterinary Medicine than Anticipated
Equine - Reasons for Retiring Early Obs. Mean Std. Dev. Min. Max.
Career advancement in another field 19 1.37 1.12 1 5 Dwindling clientele 19 1.16 0.37 1 2 Health-related, caused by wear and tear of profession 19 2.47 1.54 1 5 Other health-related issue 19 1.84 1.57 1 5 Improve work-life balance 19 3.05 1.43 1 5 Lack of satisfaction with the work 19 2.47 1.54 1 5 Money or benefits gained from retirement 19 1.47 0.96 1 4 Stress level 19 3.00 1.53 1 5 Travel requirements too demanding 19 1.42 1.02 1 5 Other 5 2.40 1.95 1 5
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AVMA - Reasons for Retiring Early Obs. Mean Std. Dev.
Min. Max.
Career advancement in another field 21 1.24 0.62 1 3 Dwindling clientele 21 1.00 0.00 1 1 Health-related, caused by wear and tear of profession
21 2.24 1.67 1 5
Other health-related issue 21 1.90 1.58 1 5 Improve work-life balance 21 3.19 1.50 1 5 Lack of satisfaction with the work 21 1.90 1.37 1 5 Money or benefits gained from retirement 22 2.32 1.76 1 5 Stress level 20 2.35 1.50 1 5 Travel requirements too demanding 21 1.38 1.02 1 5 Other 8 4.38 1.41 1 5
The 10 Equine respondents and 12 AVMA respondents who reported that they delayed their
retirement from clinical veterinary medicine to a time frame later than anticipated were asked
ranking questions relative to potential reasons for their decision: 1, not relevant at all, 2,
slightly relevant, 3, moderately relevant, 4, very relevant, and 5, extremely relevant.
Equine respondents’ three reasons most attributed to delaying retirement were “enjoyment of
work,” with an average rank of 2.90, “other reason,” with an average rank of 2.75, and “need
for general income,” 2.40 (Table 85). The three reasons most attributed for AVMA respondents
were “other reasons,”( 4.50), “enjoyment of work,” (4.08) and “need for general income”
(2.73).
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Table 85: Distribution of Equine and AVMA Respondents’ Reasons for Delaying Their Retirement
Equine - Reasons for Delaying Retirement Obs. Mean Std. Dev. Min Max
Need for medical insurance 10 2.20 1.32 1 5 Unable to sell practice 10 2.00 1.63 1 5 Lack of veterinary options for existing clientele 10 1.60 1.26 1 4 Need for general income 10 2.40 1.35 1 5 Enjoyment of work 10 2.90 1.52 1 5 Other 4 2.75 1.50 1 4
AVMA - Reasons for Delaying Retirement Obs. Mean Std. Dev. Min. Max.
Need for medical insurance 9 2.00 0.87 1 3 Need for general income 11 2.73 1.10 1 4 Enjoyment of work 12 4.08 0.67 3 5 Other 2 4.50 0.71 4 5
Note: The 2016 AVMA-AAEP Survey of Equine Practitioners provided more reasons to select
from for delaying retirement then the 2016 AVMA Census of Veterinarians
4.6 EQUINE VETERINARY PROFESSION UNEMPLOYMENT
In 2015, 2.4 percent of Equine respondents were unemployed in clinical veterinary medicine at
some point that year. Of the 2.4 percent respondents, 35.3 percent of them found a job within
one month, 29.4 percent found a job between three to six months after beginning a job search,
and 35.3 percent found work within a year.
Equine respondents were asked how many periods of isolated unemployment they had over
the course of their career, and 19.4 percent said they had periods of isolated unemployment at
some point in their career. The majority of equine respondents who had periods of isolated
unemployment over their career had only one period of isolated unemployment (69.4 percent).
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4.6.1 Summary Statistics
Of the Equine respondents who were currently unemployed and who indicated their year of
graduation, five respondents graduated during the years 2012-2016 (AVMA: 17 respondents),
five respondents during the years 2007-2011 (AVMA: 23 respondents), one respondent during
the years 1997-2006 (AVMA: 27 respondents), and one respondent during the years 1987-1996
(AVMA: 13 respondents). In addition, seven AVMA respondents who are currently unemployed
graduated prior to 1996 (Figure 97).
Figure 97: Distribution of Unemployed Equine and AVMA Respondents by Graduation Year
1 15 5
1 15
13
2723
17
< 1967 1967-1976 1977-1986 1987-1996 1997-2006 2007-2011 2012-2016
# of
Res
pond
ents
Year of Graduation
Distribution of Unemployed Respondents by Graduation Year
Equine (n=12) AVMA (n=87)
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Of the Equine respondents who indicated that they were unemployed, eight respondents were
seeking employment in veterinary medicine, two respondents were seeking enrollment in
advanced education, and four respondents were currently not seeking employment or
enrollment (Figure 98). In contrast, 33 of the unemployed AVMA respondents were seeking
employment in veterinary medicine, 11 respondents were seeking enrollment in advanced
education, and 68 respondents were not seeking any employment or enrollment.
Figure 98: Distribution of Unemployed Equine and AVMA Respondents by Type of Employment/Enrollment Area They Are Seeking
82 4
33
11
68
Seeking employment inveterinary medicine
Seeking enrollment inadvanced education
Not seeking employmentor enrollment
% o
f Res
pond
ents
Area of Employment
Distribution of Unemployed Respondents by Type of Employment/Enrollment Area They Are Seeking
Equine (n=14) AVMA (n=112)
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Seven out of eight unemployed Equine respondents who were currently seeking employment in
veterinary medicine were seeking work in private practice, while one respondent reported
looking for work in the industry/commercial sector. The majority of unemployed AVMA
respondents were primarily seeking work in a mixed animal practice (three respondents) or
companion animal practice (21 respondents) (Table 86).
Table 86: Distribution of Equine and AVMA Respondents’ Type of Employment They Are Primarily Seeking
Type of Employment Seeking Equine AVMA
Mixed practice (at least 25 percent food or equine)
2 3
Companion animal practice 2 21 Equine practice 3 0 Federal Government (civil service) 0 1 College or University (Faculty or staff only)
0 1
State/Local government 0 2 Industry/commercial organizations 1 1 Not-for-profit organizations 0 1 Other 0 3 Total 8 33
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4.6.2 Factors Affecting Unemployment
Using a binary logit model, multiple factors are examined for their potential impact on
unemployment, but given the low number of observations (14 unemployed respondents) the
results are only as reliable to the extent that the sample represents the population (Table 87).
A binary logit measures the relationship between the variable of interest (dependent variable)
and the mathematically computed factors (independent variables) hypothesized to affect the
variable of interest. In the binary logistic regression, however, the dependent variable has only
two values (1=yes, 0=no) and the relationship measured is the probability of the dependent
variable occurring when the factor occurs. The dependent variable value of 1 was assigned to
veterinarians who were unemployed, and a value of 0 was assigned if they were employed.
Independent variables that were used to attempt to explain the probability of unemployment
included age, board certification, residency and internship participation, veterinary educational
debt, home ownership, and marital status.
In the table, the coefficients presented are used to calculate the probability of an individual
respondent falling into a specific category (unemployed or employed). The main objective is to
observe whether the coefficient is positive or negative. The answer will indicate the direction of
the relationship (i.e., negative is more likely to predict employment and positive is more likely
to predict unemployment).
Variables that significantly contribute to the predictive ability of the model have a p-value of .10
or less in the column labeled “Sig.” Variables that are significant at the 10, 5 and 1 percent level
are reported in explaining the factors affecting unemployment of respondents. The “Odds
Ratio” column is the odds ratio for each of the independent variables and is defined as “the
change in odds of being in one of the categories of outcome (unemployed or employed) when
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the value of one of the independent variables (predictors) increases by one point.”40 To
interpret the odds ratio, the odds ratio value is subtracted by one to obtain the likelihood of the
event occurring given all the other variables are held constant.
Results in the Equine sample show that, for a one-unit increase in age, the odds of being
unemployed versus being employed is .16 lower, given all other variables are held constant. For
every dollar increase in Equine respondent veterinary educational debt, the odds of being
unemployed versus unemployed has essentially no effect, given all the other variables are held
constant. Equine respondents who participated in an internship versus those who did not
participate in an internship have .85 lower odds of being unemployed than employed, given all
other variables are held constant. For Equine respondents who have some other type of living
arrangement, the odds of being unemployed versus employed is 27.51 greater than
respondents who own a house, given all the other variables are held constant. The AVMA
model shows a positive association with being not married in that respondents who are
unemployed versus employed, the odds of being not married versus married is 2.21 greater,
given all the other variables are held constant.
40 Barbara G. Tabachnick and Linda S. Fidell. Using Multivariate Statistics, 6th Edition (New York City, New York: Pearson, 2013), pg.8.
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Table 87: Factors Affecting Unemployment
Equine Coefficient Std. Error Sig. Odds Ratio
Age -0.176 0.073 0.016** 0.84 Board Certified (Yes=1) 2.221 2.257 0.325 8.96 DVM Debt 0.000 0.000 0.062* 1.00 Internship (Yes=1) -1.791 0.849 0.035** 0.15 Residency (Yes=1) -0.421 2.227 0.850 0.67 Housing - own (baseline) Omitted Housing - rent 0.064 1.064 0.952 1.14 Housing - other 3.318 1.004 0.001*** 27.51 Not Married (Yes=1) 0.521 0.839 0.535 1.65 Constant 3.137 2.783 0.260 27.28
Observations 605
Pseudo R-Square 0.3092
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig. Odds Ratio
Age 0.011 0.018 0.52 1.01 Board Certified (Yes=1) -1.603 1.007 0.11 0.20 DVM Debt 0.000 0.000 0.85 1.00 Internship (Yes=1) 0.448 0.339 0.19 1.57 Residency (Yes=1) 0.183 0.854 0.83 1.20 Housing - own (baseline) Omitted Housing - rent 0.218 0.378 0.56 1.24 Housing - other 0.830 0.660 0.21 2.29 Not Married (Yes=1) 0.793 0.316 0.01** 2.21 Constant -4.440 0.884 0.00*** 0.01
Observations 1,798
Pseudo R-Square 0.038
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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4.7 EQUINE VETERINARY PROFESSION UNDEREMPLOYMENT
Underemployment is defined as the measure of a person’s desire and ability to increase one’s
hours spent working. The desire and ability to increase one’s working hours is often
unattainable due to a lack of demand for one’s services, hence the status is termed
“underemployment.” The level of underemployment provides a piece of information about the
health of the labor market for veterinarians. Underemployment can be caused by people not
being able to work as many hours as they would like, or by workers accepting employment
below their skill level. In this survey, underemployment represents the number of additional
hours that veterinarians desire to work above what they are currently working. Measured in
total hours, underemployment reflects the increase or decrease in weekly hours that one
wishes to work for an equivalent increase/decrease in compensation. Figure 99 presents the
number of observations (and percentage) from both the Equine and AVMA samples of those
who state a preference to work more hours for an increase in compensation, fewer hours for a
decrease in compensation, or to work the same number of hours per week for the same
amount of compensation.
Among Equine respondents, 60 percent stated they would work, if they could, the same
number of hours per week as they are currently working with no change to their current level
of total compensation (AVMA: 65.8 percent), 16.8 percent wish to work more hours per week
than they do now, for a higher level of total compensation (AVMA: 12.0 percent), and 23.2
percent wish to work fewer hours per week for a lower level of total compensation (AVMA:
22.2 percent) (Figure 99).
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Figure 99: Distribution of Equine and AVMA Respondents’ Preference in Work Hours
By gender, 25.3 percent of female (AVMA: 23.9 percent) and 19.9 percent of male (AVMA: 18.6
percent) Equine respondents wish to work fewer hours for less compensation. Of those wishing
to work more hours for greater compensation, 16.5 percent of Equine sample females (AVMA:
12.5 percent) and 17.7 percent of Equine males (AVMA: 11.7 percent) indicated a preference
for this option (Figure 100).
23.2%
60.0%
16.8%22.2%
65.8%
12.0%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
Work fewer hours perweek
Work the samenumber of hours per
week
Work more hours perweek
% o
f Res
pond
ents
Work Hour Preference
Distribution of Respondents' Preference in Work Hours
Equine (n=766) AVMA (n=2,244)
178
178
497 1,477459 129 270
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Figure 100: Distribution of Equine and AVMA Respondents’ Preference in Hours Worked by Gender
Except for Region 3 and Region 8 (Mountain States) in the Equine sample, all regions in both the
equine and AVMA survey have a greater percentage of veterinarians who wish to work fewer
hours per week than those who wish to work more hours per week (Table 88).
Table 88: Distribution of Equine and AVMA Respondents’ Work Preference by Work Region
Equine (n=733) AVMA (n=2,059)
Work Region Fewer Hours More Hours Fewer Hours More Hours Region 0 25.0% 18.8% 21.2% 11.3% Region 1 25.8% 12.1% 26.5% 12.2% Region 2 22.8% 20.3% 19.8% 11.5% Region 3 11.8% 25.9% 18.8% 17.3% Region 4 26.9% 9.0% 25.1% 7.5% Region 5 34.0% 8.0% 28.5% 13.2% Region 6 22.9% 16.7% 20.4% 11.5% Region 7 23.7% 9.2% 21.7% 11.1% Region 8 21.0% 22.2% 22.3% 13.3% Region 9 21.7% 19.8% 22.0% 9.6%
25.3% 19.9% 23.9% 18.6%
58.1% 62.5% 63.7% 69.7%
16.5% 17.7% 12.5% 11.7%
Equine - Female(n=442)
Equine - Male(n=317)
AVMA - Female(n=1,500)
AVMA - Male(n=624)
% o
f Res
pond
ents
Work Hour Preference
Distribution of Respondents' Preference in Hours Worked by Gender
Work fewer hours No change Work more hours
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The distribution of hours currently worked per week by Equine and AVMA respondents who
wish no change in the number of hours worked per week and those who wish to change the
hours they currently work (either increasing or decreasing their current work hours) are
dispalyed in Figure 101. Almost 30 percent of Equine respondents who worked 50-59 hours per
week desired no change, and 30 percent of these respondents who worked 50-59 hours did
desire a change. There was a higher percentage of Equine respondents who desired a change to
their current work hours than respondents who desired no change if the respondents reported
working more than 60 hours a week (more than 50 hours in the AVMA sample).
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80 +
% o
f Res
pond
ents
Hours Per Week
Distribution of Equine Respondents' Current Hours Worked and Desire to Change Hours Worked
No Change (n=355) Desire Change (n=249)
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Figure 101: Distribution of Equine and AVMA Respondents’ Current Hours Worked and Desire to Change Hours Worked
To determine the average number of hours that respondents desired to increase or decrease
their working time relative to their current hours, survey subjects were asked the number of
hours by which they desired to change per week; responses are depicted in Figure 102. If a
respondent said they did not wish to change their work hours, they were not included in this
graph. Of respondents who desired a decrease in work hours, both samples had a majority of
respondents who preferred a decrease of 10 to 19 hours relative to their current schedule
(Equine 67.1 percent, AVMA 66.5 percent). There was little difference seen between male and
female respondents who desired to decrease their work hours by 10 to 19 hours (Equine male:
31.1 percent and Equine female: 36.0 percent; AVMA male: 34.1 percent and AVMA female:
32.4 percent). Of those who desired more hours, a sizeable proportion of Equine respondents
(both male and female), indicated a preference for an increase of 10 to 19 hours per week
(male: 23.5 percent; female: 19.7 percent). A smaller number of the AVMA sample, 13.0
percent of females and 14.6 percent of males, desired an increase in their work hours of 10 to
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80 +
% o
f Res
pond
ents
Hours Per Week
Distribution of AVMA Respondents' Current Hours Worked and Desire to Change Hours Worked
No Change (n=1,463) Desire Change (n=792)
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19 hours; 11.7 percent of AVMA females and 14.6 percent of AVMA males desired to increase
their work hours by one to nine hours.
Figure 102: Distribution of Equine and AVMA Respondents’ Change in Hours Desired by Gender
0.0%
10.0%
20.0%
30.0%
40.0%
% o
f Res
pond
ents
Desired Change In Hours
Distribution of Equine Respondents' Change in Hours Desired by Gender
Female (n=178) Male (n=119)
0.0%
10.0%
20.0%
30.0%
40.0%
% o
f Res
pond
ents
Desired Change In Hours
Distribution of AVMA Respondents' Change in Hours Desired by Gender
Female (n=531) Male (n=185)
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As reported by the respondents who desired a change in their hourly work week (fewer or
more hours), the most frequent average hourly work week desired by the men and women in
the Equine sample was between 40 to 49 hours (male: 21.4 percent; female: 27.7 percent).
More than one-fifth (22.6 percent) of female Equine respondents indicated a desire for a 50 to
59 hour work week compared to 16.3 percent of Equine male respondents, and 14.3 percent of
male Equine respondents desired a 30 to 39 hour work week compared to 8.8 percent of
female Equine respondents. In contrast, 30.3 percent of female AVMA respondents reported a
desire for a 30 to 39 hour work week compared to 20.3 percent of male AVMA respondents and
36.3 percent of male AVMA respondents desired a 40 to 49 hours work week compared to 27.0
percent of female AVMA respondents (Figure 103).
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%
% o
f Res
pond
ents
Current Hours Plus Desired Change In Hours
Distribution of Equine Respondents' Net Hours Desired by Gender
Male (n=98) Female (n=137)
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Figure 103: Distribution of Equine and AVMA Respondents’ Net Hours Desired by Gender
The distribution of the desired change in respondents’ hourly work week by number of years
since DVM/VMD graduation indicates that for female Equine respondents at the beginning of
their careers, an almost equal number want to work fewer hours as want to work more hours
(25.6 percent fewer hours and 23.1 percent more hours). AVMA female respondents display a
different pattern in their desired change in the hourly work week. While 25.3 percent of AVMA
female respondents within five years or fewer years since graduation desire to work fewer
hours, only 14.3 percent want to work more hours per week. The percent of female Equine
respondents who stated they wish to work more hours declines until the respondents are 20
years out from graduation, and then begins to increase, while the percent who wish to work
fewer hours is relatively stable across the post-graduate period until 40 years out (Figure 104).
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%
% o
f Res
pond
ents
Current Hours Plus Desired Change In Hours
Distribution of AVMA Respondents' Net Hours Desired by Gender
Male (n=182) Female (n=525)
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Figure 104: Distribution of Female Equine and AVMA Respondents’ Work Hour Preference by Number of Years since DVM/VMD Graduation
5 yearsout
10 yearsout
20 yearsout
30 yearsout
40 yearsout
Work fewer hours 25.6% 24.8% 25.5% 27.5% 20.7%Work more hours 23.1% 13.2% 11.7% 15.9% 20.7%
% o
f Res
pond
ents
Years Since DVM/VMD
Distribution of Female Equine Respondents' Work Hour Preference by Number of Years since DVM/VMD
Graduation (n=438)
5 yearsout
10 yearsout
20 yearsout
30 yearsout
40 yearsout
50 yearsout
Work fewer hours 25.3% 24.9% 22.4% 20.3% 34.5% 9.1%Work more hours 14.3% 10.9% 12.5% 10.2% 18.2% 9.1%
% o
f Res
pond
ents
Years Since DVM/VMD
Distribution of Female AVMA Respondents' Work Hour Preference by Number of Years since Graduation
(n=1,481)
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Looking at the desired change in respondents’ hourly work week by number of years since
DVM/VMD graduation for males, 44.4 percent of the Equine male respondents (AVMA males:
23.0 percent) who were five years out (or fewer) of veterinary school showed an increased
desire to work more hours and 22.2 percent desired fewer hours (AVMA males: 14.2 percent).
Males in the Equine sample, who graduated 20 years ago and 50 years ago, had approximately
a 15 percent greater desire to work fewer hours than to work more hours. Males in the AVMA
sample who graduated 30 years ago show a 15 percent difference in desire to work fewer hours
than desire to work more hours (Figure 105).
5 yearsout
10 yearsout
20 yearsout
30 yearsout
40 yearsout
50 yearsout
60 yearsout
Work fewer hours 22.2% 21.2% 21.6% 13.4% 19.6% 29.8% 0.0%Work more hours 44.4% 21.2% 7.8% 19.4% 16.3% 14.9% 16.7%
% o
f Res
pond
ents
Years Since DVM/VMD
Distribution of Male Equine Respondents' Work Hour Preference by Number of Years since DVM/VMD
Graduation (n=314)
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Figure 105: Distribution of Male Equine and AVMA Respondents’ Work Hour Preference by Number of Years since DVM/VMD Graduation
Respondents who would, or would not, change the number of hours they work were sorted by
their type of employment in Figure 106. Among Equine respondents, 41.1 percent in equine
exclusive practice and 34 percent in equine predominant practice would change the number of
hours worked per week (AVMA: 44.4 percent exclusive and predominant combined).
5 yearsout
10 yearsout
20 yearsout
30 yearsout
40 yearsout
50 yearsout
Work fewer hours 14.2% 18.0% 15.6% 23.5% 24.7% 12.2%Work more hours 23.0% 13.5% 8.5% 8.4% 5.4% 12.2%
% o
f Res
pond
ents
Years Since DVM/VMD
Distribution of Male AVMA Respondents' Work Hour Preference by Number of Years since DVM/VMD
Graduation(n=612)
Work fewer hours Work more hours
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Note: Not-for-profit, industry/commercial organization and state/local government were
removed because the number of observations did not permit estimation.
71.4%
35.4%
44.1%
55.6%
33.3%
36.4%
60.0%
34.0%
41.1%
28.6%
64.6%
55.9%
44.4%
66.7%
63.6%
40.0%
66.0%
58.9%
Other Veterinary Employment (n=7)
College or University (n=82)
Mixed Animal Practice (n=93)
Companion Animal Practice (Pred.) (n= 33)
Companion Animal Practice (Excl.) (n=9)
Food Animal Practice (Pred.) (n=11)
Food Animal Practice (Excl.) (n=5)
Equine Practice (Pred.) (n=97)
Equine Practice (Excl.) (n=423)
Work Preference
Type
of E
mpl
oym
ent
Distribution of Equine Respondents' Desired Work Hour Preference by Type of Employment
Would change Would not change
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Figure 106: Distribution of Equine and AVMA Respondents’ Desired Work Hour Preference by Type of Employment
When comparing practice owner versus non-practice owner Equine respondents, 23 percent of
practice owners preferred to work fewer hours per week (AVMA: 26.4 percent), 16.3 percent
would prefer more hours per week (AVMA: 9.0 percent), and 60.7 percent preferred no change
(AVMA: 64.6 percent). Of the non-practice owners among the Equine respondents, 23.1
23.1%
25.0%
48.3%
30.4%
18.6%
35.5%
19.3%
23.1%
34.5%
40.0%
37.1%
34.2%
34.8%
34.5%
44.4%
76.9%
75.0%
51.7%
69.6%
81.4%
64.5%
80.7%
76.9%
65.5%
60.0%
62.9%
65.8%
65.2%
65.5%
55.6%
Non-Veterinary Employment (n=13)
Other Veterinary Employment (n=76)
Advanced Education (n=60)
Not-for-profit Org. (n=69)
Industry/Commercial Org. (n=70)
State/Local Government (n=31)
Federal Government (n=57)
Uniformed Services (n=13)
College or University (n=174)
Mixed Animal Practice (n=120)
Companion Animal Practice (Pred.)(n=240)
Companion Animal Practice (Excl.) (n=1,182)
Food Animal Practice (Pred.) (n=23)
Food Animal Practice (Excl.) (n=29)
Equine Practice (n=81)
Work Preference
Type
of E
mpl
oym
ent
Distribution of AVMA Respondents' Desired Work Hour Preference by Type of Employment
Would change Would not change
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percent would prefer fewer hours (AVMA: 21.8 percent), 18.5 percent preferred more hours
(AVMA: 13.4 percent), and 58.4 percent preferred the same number of hours per week (AVMA:
64.8 percent) (Figure 107).
Figure 107: Distribution of Equine and AVMA Respondents’ Work Preference — Practice Owners vs. Non-Practice Owners
Examining work preference by primary equine sector (Figure 108) found AAEP respondents in
the Quarter Horse racing sector reported wanting to work fewer hours a week (40.0 percent)
23.0% 16.3%
60.7%
23.1% 18.5%
58.4%
Would prefer fewerhours/week
Would prefer morehours/week
Would prefer the samehours/week
% o
f Res
pond
ents
Work Preference
Distribution of Equine Respondents' Work Preference — Practice Ownership
Practice Owner (n=326) Non-practice owner (n=281)
26.4%9.0%
64.6%
21.8%13.4%
64.8%
Would prefer fewerhours/week
Would prefer morehours/week
Would prefer the samehours/week
% o
f Res
pond
ents
Work Preference
Distribution of AVMA Respondents' Work Preference — Practice Ownership
Practice Owner (n=421) Non-practice owner (n=1,295)
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followed by respondents in the ranch/working sector (33.3 percent). Those in the
Thoroughbred racing sector had the smallest proportion wanting to work fewer hours, at 14.3
percent. Some AAEP respondents reported wanting to work more hours: 28.6 percent of
respondents working in the Standardbred racing sector wanted to. A substantial proportion of
Equine respondents polled in the Thoroughbred racing industry were satisfied with the amount
of time devoted to their work: 71.4 percent stated they did not prefer a change in the number
of hours worked per week. Comparatively, only 42.9 percent of respondents in the
Standardbred racing sector did not prefer any change in hours worked per week.
Figure 108: Distribution of AAEP Respondents’ Work Preference by Primary Equine Sector
19.5% 24.0%40.0% 28.6% 14.3% 23.3% 33.3% 31.3% 22.8%
64.6% 56.0%
60.0%
42.9% 71.4% 56.7% 44.4% 56.3% 59.8%
15.9% 20.0% 28.6% 14.3% 20.0% 22.2% 12.5% 17.4%
% o
f Res
pond
ents
Primary Equine Sector
Distribution of AAEP Respondents' Work Preference by Primary Equine Sector
Fewer hours per week No change in hours per week More hours per week
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When examining work preference by the type of business practice among Equine respondents
(Figure 109), respondents working in haul-in facilities (33.3 percent) and specialty/referral with
limited service with an ambulatory division (33.3 percent) had the highest percentage reporting
they wanted to work fewer hours per week. One-quarter (25 percent) of veterinarians in a
specialty/referral hospital with limited service preferred to work more hours per week. The
majority of ambulatory practice respondents wanted no change in the number of hours, while
22.9 percent preferred to work more hours per week.
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Figure 109: Distribution of AAEP Respondents’ Work Preference by Business Model
21.3% 22.0%33.3%
25.0%11.1%
33.3%25.0% 23.8%
55.9%65.1%
50.0%50.0%
66.7%
53.3%61.9% 61.9%
22.9%12.9% 16.7%
25.0% 22.2%13.3% 13.1% 14.3%
% o
f Res
pond
ents
Type of Business Model
Distribution of AAEP Respondents' Work Preference by Business Model
Fewer hours per week No change in hours per week More hours per week
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4.7.1 Veterinarians Who Wish to Work More (Underemployment)
Of 766 Equine respondents, 129 (and 270 out of 2,244 AVMA respondents) reported a desire to
work more hours per week than they do now, for a higher level of compensation.
Of the respondents who desired to work more hours, the mean number of additional hours
desired was 19.7 hours compared to the mean number of hours for the AVMA sample of 19.0.
The mean additional hours for female Equine respondents who wanted to work more hours
and were working no more than 168 hours a week, was 19.7 hours, moving from 51.6 hours to
71.3 hours per week. Female AVMA respondents, having a current mean 42 hour per week,
wanted to work an additional 16.5 hours, moving to a 58.5-hour work week. The mean
additional hours for male Equine respondents who wanted to work more hours was 20.1 hours,
moving from 51.1 hours to 71.2 hours worked per week. While a large difference exists
between the female Equine and AVMA respondents in terms of the number of hours desired to
work, male Equine and AVMA respondents were similar, as male AVMA respondents reported
working a mean of 47.7 hours per week and wanting to work an additional 25 hours on
average, which totals 72.7 hours per week (Figure 110).
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Figure 110: Distribution of Equine and AVMA Respondents’ Underemployment by Gender
Of 94 Equine respondents across the nine U.S. regions three respondents in Region 5 reported
wanting to work the most hours per week (94.6 hours) and seven Equine respondents in Region
7 desired a mean of 50.4 hours a week (Figure 111).
51.6 51.142.0 47.7
71.3 71.258.5
72.7
0.0
20.0
40.0
60.0
80.0
Equine - Female(n=51)
Equine - Male(n=49)
AVMA - Female(n=182)
AVMA - Male(n=73)
# of
Hou
rs
Gender
Distribution of Respondents' Underemployment by Gender
Hours worked Hours want to work
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Figure 111: Distribution of Equine and AVMA Respondents’ Underemployment by Region
Across equine sectors, out of 82 respondents used in this analysis, 54 Equine respondents in
general equine practice reported wanting to work an average of 78.5 hours, followed by four
0.0
20.0
40.0
60.0
80.0
100.0
# of
Hou
rs
Work Region
Distribution of Equine Respondents' Underemployment by Region
Hours worked Hours want to work Median hours worked
0.010.020.030.040.050.060.070.080.0
# of
Hou
rs
Work Region
Distribution of AVMA Respondents' Underemployment by Region
Hours worked Hours want to work Median hours worked
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respondents in the Thoroughbred racing industry (77.8 hours), while the lowest total number of
desired hours was expressed by five respondents in the equine companion sector, with 53.8
hours on average (Figure 112).
Figure 112: Distribution of Equine Respondents’ Underemployment by Primary Equine Sector41
Among 83 Equine respondents working in different types of practices, the three Equine
respondents (Figure 113) in limited-service specialty/referral hospitals reported wanting to
work the least number of mean hours (63.3 hours), with 11 respondents in a full-service
specialty/referral hospital with an ambulatory division reported wanting to work the most
hours per week (80.2 hours).
41 Standardbred racing, Quarter Horse racing, ranch or working, and gaited breeds were omitted because the number of observations did not permit estimation.
48.6
37.8
58.5
47.354.5
67.9
53.8
77.8
65.8
78.5
English (n=13) Companion/Pet(n=5)
Racing-TB (n=4) Reproductive (n=6) General equine(n=54)
# of
Hou
rs
Primary Equine Sector
Distribution of Equine Respondents' Underemployment by Primary Equine Sector
Hours worked Hours want to work Median hours worked
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Figure 113: Distribution of Equine Respondents’ Underemployment by Business Model 42
Equine respondents were asked their reasons for wanting to work more hours a week, selecting
all that applied to them. Reasons that Equine respondents gave for wanting to work more hours
a week were: the desire to gain professional expertise (14.7 percent), not currently working to
capacity (42.2 percent), the desire to earn more compensation (82.6 percent), or some other
reason such as paying off student loans, providing better service to the community, satisfying
needs of the client, and social benefits (4.6 percent).
42 Full-service specialty/referral hospital, haul-in facility only, and l imited-service specialty/referral hospital with ambulatory division were omitted because the number of observations did not permit estimation.
47.353.7
40.0
57.050.0
70.8 72.663.3
80.270.0
Ambulatory (n=43) Ambulatory withHaul-in (n=23)
Specialty/referralhospital -Limited
service (n=3)
Specialty/referral hospital – Full
service with ambulatory (n=11)
Other (n=3)
# of
Hou
rs
Type of Business Model
Distribution of Equine Respondents' Underemployment by Business Model
Hours worked Hours want to work Median hours worked
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4.7.2 Veterinarians Who Wish to Work Less (Negative Underemployment)
Among respondents, 178 out of 766 Equine participants and 497 of 2,244 AVMA respondents
reported a desire to work fewer hours per week than they do now, for a lower level of
compensation.
In contrast to those who indicated a desire to work additional hours for increased
compensation, 23.2 percent of Equine respondents (AVMA: 22.2 percent) indicated they
wanted to work a mean 16.4 hours less per week for less compensation (AVMA: 14.9 hours).
The Equine respondents who wished to work less (23.2 percent) were working roughly 8.9
hours more per week (60.3 hours) on average than the Equine respondents (51.4 hours) who
wished to work more (16.8 percent).The remaining 60 percent desired to stay at their current
work hours with no change in their compensation. The AVMA data also indicate that the group
who wished to work less (22.2 percent) was working roughly 6.8 hours more per week (50.3
hours per week) than the group wishing to work more (12 percent) (43.5 hours per week) while
the remaining 65.8 percent desired no change in their current work hours.
The Equine respondents who desired more work wished to expand their work time by an
average of 19.7 hours (AVMA: 19.0 hours). The Equine respondents who desired to work fewer
hours wanted to lessen their work week by 16.4 hours (AVMA: 14.9 hours).
The total level of underemployment among Equine respondents is negative; this is because the
number of Equine respondents who desired to work less (23.2 percent) exceeds the number
who desired to work more (16.8 percent), and the Equine respondents who wanted to work
less desired to reduce their work week by an average of 16.4 hours while the Equine
respondents who wanted to work more wanted to increase their work week by an average of
19.7 hours. In other words, the surveyed sample of Equine veterinarians does not present
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enough respondents willing to work the additional amount required to replace the gap that
would materialize should respondents desiring to work less be able to do so.
The current workload of Equine respondents who desired to work fewer hours was around 60
hours per week and there was an average desire to reduce the length of the work week to
between 38 and 45 hours per week. Female Equine respondents wanted to work a mean 16.9
fewer hours a week (AVMA females: 14.5 hours), to reach a desired mean of 45 hours per week
(AVMA females: 34.9 hours). Male Equine respondents desired to work a mean 19.1 hours less
than they currently are working (AVMA males: 16.4 hours) to reach a desired mean of 38.4
hours per week (AVMA males: 36.5 hours) (Figure 114).
Figure 114: Distribution of Equine and AVMA Respondents’ Negative Underemployment by Gender
Looking at 128 Equine respondents with respect to negative underemployment by region, the
average work week among Equine respondents across regions was approximately 60 hours per
week, with the desired mean of roughly 40 hours a week. Similarly AVMA respondents, with a
current mean of roughly 50 hours per week across regions, desire to reduce their work week to
reach a desired mean of roughly 35 hours per week (Figure 115).
61.9 57.549.4 52.9
45.0 38.4 34.9 36.5
Equine - Female(n=84)
Equine - Male(n=52)
AVMA - Female(n=354)
AVMA - Male(n=116)
# of
Hou
rs
Gender
Distribution of Respondents' Negative Underemployment by Gender
Hours worked Hours want to work
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Figure 115: Distribution of Equine and AVMA Respondents’ Negative Underemployment by Region
0.010.020.030.040.050.060.070.0
# of
Hou
rs
Region
Distribution of Equine Respondents' Negative Underemployment by Region
Hours worked Hours want to work Median hours worked
0.010.020.030.040.050.060.070.0
# of
Hou
rs
Region
Distribution of AVMA Respondents' Negative Underemployment by Region
Hours worked Hours want to work Median hours worked
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Within the equine sectors, seven Equine respondents in the reproductive sector worked a mean
75.1 hours per week, and desired to work a mean 24.9 hours less per week. Five Equine
respondents who were engaged in Western performance worked a mean 47.0 hours per week,
and desired to work a mean 7.7 hours per week less (Figure 116).
Figure 116: Distribution of Equine Respondents’ Negative Underemployment by Primary Equine Sector43
43 Gaited breeds, Quarter Horse and Standardbred racing were omitted because the number of observations did not permit estimation.
0.010.020.030.040.050.060.070.080.0
# of
Hou
rs
Equine Sector
Distribution of Equine Respondents' Negative Underemployment by Primary Equine Sector
Hours worked Hours want to work Median hours worked
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Five Equine respondents out of 116 Equine respondents who reported working in a
specialty/referral limited service with ambulatory division are working a mean 73.6 hours and
wish to work a mean 41.6 hours per week. On the opposite end, 41 Equine respondents in an
ambulatory with haul-in facility practice are working a mean 57.1 hours and wish to work a
mean 41.5 hours per week (Figure 117).
Figure 117: Distribution of Equine Respondents’ Negative Underemployment by Business Model 44
44 Full-service specialty/referral hospital and haul-in facility only were omitted because the number of observations did not permit estimation.
60.8 57.161.3
73.6
60.7
72.4
45.741.5 41.3 41.6
46.4
33.8
Ambulatory (n=39) Ambulatory withHaul-in facility
(n=41)
Specialty/referralhospital-Limited
service (n=3)
Specialty/referralhospital-Limited
service withambulatory division
(n=5)
Specialty/referralhospital-Full service
with ambulatorydivision (n=21)
Other (n=5)
# of
Hou
rs
Type of Business Model
Distribution of Equine Respondents' Negative Underemployment by Business Model
Hours worked Hours want to work Median hours worked
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Reasons to Work Less
AAEP respondents cited the need to improve work-life balance as the main reason they want to
work less (77.3 percent), followed by taking care of children/childbearing. The AVMA sample
shows that 50 percent of respondents have some other reason followed by 33.7 percent to take
care of children/childbearing (Table 89).
Table 89: Reasons Equine and AVMA Respondents Want to Work Less (select all that apply)
Reasons Want to Work Less Obs. Equine Obs. AVMA
Better work-life balance 136 77.3% - - Taking care of children/childbearing 39 22.2% 165 33.7% Nearing retirement 38 21.6% 71 14.5% Medical reasons/ difficult to or unable to physically perform requirements of job
18 10.2% 26 5.3%
Other reason 13 7.4% 246 50.0% Pursuing another career 12 6.8% 44 9.0% Taking care of elderly parents 6 3.4% - -
Note: The 2016 AVMA Census of Veterinarians did not give “Better work-life balance” or “Taking
care of elderly parents” as a choice in reasons for wanting to work fewer hours.
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4.7.3 Factors Correlated with Underemployment
Following the same method used to identify the factors that are correlated with student debt
and income, a multiple linear regression was used to determine the factors that are correlated
with underemployment. Variables that are significant at the 10 percent, 5 percent and 1
percent levels are reported in explaining the factors affecting underemployment. The
dependent variable is a desired change in hours worked (underemployment) and the
independent variables explaining this variation are income, graduation year, age, gender, intern
and residency completion, board certified, highest degree obtained, veterinary educational
debt, physical and mental health condition, satisfaction with current employment, work region,
school region, home ownership, current living environment/community, community size in
which respondent works, has children , number of hours worked per week, full-time status, and
practice ownership. In addition, equine-specific variables were added to the AAEP model to see
which equine-specific factors influenced underemployment, such as business model, equine
sector, and total number of unique clients. Type of employment was included in the AVMA
model.
The coefficient in Table 90 indicates the number of hours desired, with a negative coefficient
representing a desired decrease in work hours, and a positive coefficient a desired increase in
work hours. An AAEP respondent who went to school in Region 1 , for example, desired to
decrease his or her working hours by 37.2 hours.
The column labelled “Sig.” represents the significant variables. These variables, also known as
p-values, are such that for a “sig” less than 0.10, the coefficient is statistically different from
“0.” For AAEP respondents who went to school in Region 9, for instance, the p-value is .08; this
means it is statistically, significantly different from the baseline: School Region 3.
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To avoid statistical errors, baseline factors are used. The baseline variables are school in Region
3, owns a home, lives in a rural area, works in a community size of 50,001 to 500,000 residents
in the AAEP model and 50,000 to 499,999 in the AVMA model), work Region 9, obtained a
bachelor’s degree, works in an ambulatory practice (AAEP model), works in the general equine
practice sector (AAEP model), and companion animal practice (AVMA model).
The following factors were statistically significant in explaining the variation in
underemployment of AAEP respondents, at the 10 percent or less level of significance:
completion of an internship, veterinary eductional debt, rents a dwelling, works in a community
size of 10,001 to 25,000 residents, school Region 1, school Region 9, works in a limited-service
specialty/referral hospital with ambulatory division, works in a full-service specialty/referral
hospital and some other form of business model.
The following factors were statistically significant in explaining the variation in
underemployment of AVMA respondents at the 10 percent or less level of significance: income,
gender, specialty degree, veterinary educational debt, other type of living arrangement, school
Region 1, works in Region 3 or Region 5, lives in an urban area, hours worked, and works in an
equine practice.
The coefficient for internship, 10.30, indicates that, on average, AAEP respondents who
completed an internship desire to increase their number of hours worked by 10 hours versus
the respondents who did not participate in an internship.
With regard to educational debt, both Equine and AVMA models revealed a positive coefficient,
meaning that for every thousand dollar increase in veterinary educational debt, respondents
desired to work more hours (.08 in the AAEP model and .03 in the AVMA model). In the AVMA
sample, the coefficient for equine practice indicates that respondents practicing equine
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medicine desired to decrease their work hours by almost 11 hours compared to respondents in
companion animal practice.
Within the AAEP model, respondents working in a limited-service specialty referral hospital
with an ambulatory division desired a decrease in hours worked per week of 47 hours,
respondents in a full-service specialty referral hospital with ambulatory division desired a
decrease in hours worked per week of 19 hours, and respondents in another type of business
model desired a decrease of 58 hours worked per week compared to respondents in an
ambulatory practice.
The factors that were included in this model produced an adjusted R-square of 0.0983 in the
AAEP sample and .1703 in the AVMA sample. This indicates that the inclusion of all these
factors were able to explain 9 percent and 17 percent of the variation between the individually
reported desired hours work and the estimated mean desired hours worked. Thus, there are
important variables that determine starting salaries that have not been included, and are due
to other unobservable factors.
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Table 90: Factors Affecting Underemployment
AAEP Coefficient Std. Error Sig.
Income 0.017 0.029 0.56 Graduation Year -0.188 0.934 0.84 Age 0.986 0.978 0.32 Gender (Female=1) -0.134 8.565 0.99 Internship (Yes=1) 10.298 5.801 0.08* Residency (Yes=1) -7.502 11.289 0.51 Board Certified (Yes=1) 3.192 12.046 0.79 Bachelor’s (baseline) Omitted Master’s -4.420 11.026 0.69 Specialty Degree 5.131 34.410 0.88 DVM only 8.303 10.876 0.45 DVM Debt 0.083 0.047 0.09* Physical health condition (5=Excellent/1=Very poor) -5.099 5.434 0.35 Mental health condition (5=Excellent/1=Very poor) 0.403 4.931 0.94 Satisfaction with current employment (5=Extremely satisfied/1=Not at all satisfied)
0.389 3.209 0.90
Housing - own (baseline) Omitted Housing - rent 16.235 8.188 0.05** Housing - other 7.146 18.959 0.71 Region 0 -8.045 14.150 0.57 Region 1 -11.302 14.654 0.44 Region 2 1.569 13.559 0.91 Region 3 -15.947 14.846 0.29 Region 4 -10.938 13.767 0.43 Region 5 -23.439 16.055 0.15 Region 6 -9.505 16.206 0.56 Region 7 -9.838 14.598 0.50 Region 8 13.803 10.269 0.19 Region 9 (baseline) Omitted Rural (baseline) Omitted Urban -1.443 10.091 0.89 Suburban -8.639 7.650 0.27 Children (Yes=1) -2.017 8.521 0.81 Under 2,500 residents -4.742 11.291 0.68 2,501 to 10,000 residents -4.842 10.682 0.65
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10,001 to 25,000 residents -15.824 9.243 0.09* 25,001 to 50,000 residents -7.041 9.263 0.45 50,001 to 500,000 residents (baseline) Omitted 501,000 or more residents -5.762 10.025 0.57 School Region 0 8.504 18.397 0.65 School Region 1 -37.222 16.138 0.03** School Region 2 -18.269 14.440 0.21 School Region 3 (baseline) Omitted School Region 4 -1.149 10.481 0.91 School Region 5 16.433 17.790 0.36 School Region 6 -12.878 13.783 0.36 School Region 7 2.311 12.342 0.85 School Region 8 -16.506 12.984 0.21 School Region 9 -21.100 11.970 0.08* General equine (baseline) Omitted Working 17.937 15.270 0.25 English performance 10.115 11.831 0.40 Companion 1.841 13.120 0.89 Quarter Horse racing 35.141 36.535 0.34 Standardbred racing 2.901 19.046 0.88 Thoroughbred racing 14.142 15.761 0.37 Reproductive 6.583 12.368 0.60 Western performance -18.046 12.712 0.16 Ambulatory (baseline) Omitted Ambulatory with haul-in facility -8.698 8.434 0.31 Haul-in only -16.602 23.609 0.49 Specialty/referral - limited service hospital -18.211 19.584 0.36 Specialty/referral - full service hospital 0.727 29.399 0.98 Specialty/referral - limited service hospital with ambulatory
-47.109 17.946 0.01***
Specialty/referral - full service hospital with ambulatory -18.950 11.173 0.10* Other business model -58.183 27.834 0.04** Unique Patients -0.116 2.141 0.96 Hours worked per week -0.321 0.214 0.14 Full-time (Yes=1) 2.340 16.332 0.89 Practice Owner (Yes=1) 3.331 7.942 0.68 Constant -14.235 43.141 0.74
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Observations 109
Adjusted R-Square 0.0983
Note: Ph.D. was omitted because of correlation with other variables.
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig.
Income -0.043 0.017 0.01*** Graduation Year -0.179 0.320 0.58 Age 0.217 0.302 0.47 Gender (Female=1) -8.555 2.357 0.00*** Internship (Yes=1) 2.990 2.796 0.29 Residency (Yes=1) -1.749 7.734 0.82 Board Certified (Yes=1) -0.460 7.093 0.95 Bachelor’s (baseline) Omitted Ph.D. 7.871 5.875 0.18 Master’s 4.086 3.171 0.20 Specialty Degree -48.087 20.705 0.02** DVM only 4.146 3.927 0.29 DVM debt 0.025 0.010 0.02** Health condition (5=Excellent/1= Poor) 0.727 1.097 0.51 Satisfaction with current employment (5=Extremely satisfied/1=Not at all satisfied)
0.514 1.016 0.61
Housing - own (baseline) Omitted Housing - rent 1.040 2.569 0.69 Housing - other 9.507 5.827 0.10* School Region 0 -6.218 4.830 0.20 School Region 1 8.538 4.984 0.09* School Region 2 4.722 4.698 0.32 School Region 3 (baseline) Omitted School Region 4 -5.988 3.796 0.12 School Region 5 -7.109 4.510 0.12 School Region 6 -1.541 4.977 0.76 School Region 7 3.100 5.716 0.59
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School Region 8 -1.016 5.795 0.86 School Region 9 2.296 4.344 0.60 Region 0 8.183 5.358 0.13 Region 1 3.486 4.509 0.44 Region 2 4.182 4.775 0.38 Region 3 9.936 4.735 0.04** Region 4 8.206 5.304 0.12 Region 5 9.010 5.028 0.07* Region 6 5.410 5.852 0.36 Region 7 1.077 5.688 0.85 Region 8 3.094 4.425 0.49 Region 9 (baseline) Omitted Rural (baseline) Omitted Urban 6.639 3.575 0.06* Suburban 2.872 2.669 0.28 Children (Yes=1) -2.219 2.281 0.33 Under 2,500 residents 4.358 4.824 0.37 2,500 to 49,999 residents -1.037 2.457 0.67 50,000 to 499,999 residents (baseline) Omitted 500,000 or more residents 4.782 2.992 0.11 Hours worked per week -0.408 0.079 0.00*** Full-time (Yes=1) 3.770 4.319 0.38 Practice Owner (Yes=1) -1.135 2.981 0.70 Companion Animal (baseline) Omitted Mixed Animal -3.651 3.864 0.35 Food Animal 3.924 6.541 0.55 Equine -10.932 4.468 0.02** Public Practice (Yes=1) -2.395 4.827 0.62 Constant 1.406 11.958 0.91
Observations 398
Adjusted R-Square 0.1703
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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4.8 HEALTH AND WELLNESS
A British Equine Veterinary Association (BEVA) study conducted in 2014 raised concerns about
the occupational danger of an equine veterinary career. Their findings concluded that equine
practitioners carry the highest risk of injury of any civilian occupation in the United Kingdom.
The results of the BEVA study indicated that an equine veterinarian could expect to sustain
between seven and eight work-related injuries that impeded them from practicing during a 30-
year working life. This subsection on equine veterinary profession wellness offers a view of the
physical and mental wellness of AAEP respondents compared to AVMA respondents, where
applicable.
4.8.1 Physical and Mental Health
All AAEP respondents were asked about their physical and mental health condition. Health
condition was asked of the AVMA sample, but not divided by physical or mental health, and the
interval in which health condition was measured was also different in the AVMA sample.
Approximately 99 percent of AAEP respondents reported their physical health as fair, good or
excellent, with 89.4 percent in the good to excellent range. Almost 97 percent reported their
mental health as being fair, good or excellent, with 82.2 percent in the good to excellent range.
Examining the data by gender found that approximately 90 percent of AAEP males and AAEP
females reported their physical health as being in good to excellent condition. Approximately
90 percent of the males reported their mental health as being in good to excellent condition,
and 76.4 percent of female respondents reported their mental health being in good to excellent
condition. 9.2 percent of AAEP males and 18.7 percent of females reported their mental health
to be in fair condition, and 4.6 percent of women reported their mental health as being in poor
to very poor condition (Figure 118).
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More than 90 percent of AVMA male and female respondents reported their health condition
as good to excellent (Figure 119). Around 6 percent of AVMA respondents, both male and
female, reported their health as being in fair condition, and less than 1 percent, both male and
female, reported their health condition as poor.
Figure 118: Distribution of AAEP Respondents’ Physical and Mental Health Condition by Gender
Male (n=403) Female (n=567) Male (n=403) Female (n=566)Excellent 32.9% 35.8% 50.4% 24.7%Good 55.9% 54.1% 39.7% 51.9%Fair 10.1% 9.7% 9.2% 18.7%Poor 1.0% 0.0% 0.7% 4.1%Very Poor 0.0% 0.4% 0.0% 0.5%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
% o
f Res
pond
ents
Physical Health Mental Health
Distribution of AAEP Respondents' Physical and Mental Health Condition by Gender
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Figure 119: Distribution of AVMA Respondents’ Health Condition by Gender
Overall, about 90 percent of the male and female associate AAEP respondents reported
physical health in the good to excellent range. More than 80 percent of male associate AAEP
respondents reported their mental health in the good to excellent range and nearly three-
fourths of female associate AAEP respondents reported their mental health in the good to
excellent range (Figure 120). Compared to practice owners (Figure 121), a higher percentage of
associate AAEP respondents reported being in the fair to very poor condition range for physical
and mental condition: 7.8 percent of male associates reported fair physical health condition
(6.7 percent male AAEP owners), 11.7 percent of female associates reported fair to very poor
physical health (4.1 percent female AAEP owners), 17.6 percent male associate respondents
reported fair to poor mental health (9.6 percent male AAEP owners), and more than one-
quarter of female associates reported their mental health condition in the fair to very poor
range (14.6 percent female AAEP owners). In addition, while the health condition of the AVMA
Male (n=768) Female (n=1,618)Excellent 25.9% 24.7%Very good 44.7% 45.8%Good 22.8% 22.7%Fair 6.1% 6.5%Poor 0.5% 0.4%
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%50.0%
% o
f Res
pond
ents
Health Condition
Distribution of AVMA Respondents' Health Condition by Gender
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sample is on a different interval scale than the AAEP sample, it is provided in Figure 120 and
Figure 121 for reference.
Male (n=51) Female (n=162) Male (n=51) Female (n=161)Excellent 29.4% 35.8% 35.3% 18.0%Good 62.7% 52.5% 47.1% 56.5%Fair 7.8% 11.1% 15.7% 20.5%Poor 0% 0% 2.0% 4.3%Very Poor 0.0% 0.6% 0.0% 0.6%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%
% o
f Res
pond
ents
Physical Condition Mental Condition
Distribution of AAEP Respondent Associates' Physical and Mental Health Condition by Gender
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Figure 120: Distribution of AAEP and AVMA Respondent Associates’ Physical and Mental Health Condition by Gender
Male (n=218) Female (n=860)Excellent 23.4% 24.7%Very good 49.1% 46.3%Good 19.3% 23.0%Fair 7.8% 5.7%Poor 0.5% 0.3%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%
Axis
Title
Health Condition
Distribution of AVMA Respondent Associates' Health Condition by Gender
Male (n=179) Female (n=123) Male (n=178) Female (n=123)Excellent 38.5% 42.3% 54.5% 33.3%Good 54.7% 53.7% 36.0% 52.0%Fair 6.7% 4.1% 9.0% 12.2%Poor 0% 0% 0.6% 2.4%Very Poor 0.0% 0.0% 0.0% 0.0%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%
% o
f Res
pond
ents
Physical Condition Mental Condition
Distribution of AAEP Respondent Owners' Physical and Mental Health Condition by Gender
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Figure 121: Distribution of AAEP and AVMA Respondent Owners’ Physical and Mental Health Condition by Gender
Note: Employment types besides owners and associates were not represented in this analysis
because the number of observations did not permit estimation.
When wellness of AAEP respondents was compared by graduation year, variation was seen
between those respondents who graduated most recently and those with years of experience.
The general trend was a minor decrease in physical health with the passage of years (Figure
122). When comparing the mental health condition of respondents, veterinarians who recently
graduated from veterinary college reported fair to poor to very poor mental health conditions
with greater frequency than respondents who had more experience in the veterinary field. A
higher percentage of respondents from distant graduation years reported having an excellent
mental health condition.
Male (n=212) Female (n=202)Excellent 34.9% 29.2%Very good 39.2% 47.5%Good 21.7% 14.9%Fair 4.2% 8.4%Poor 0.0% 0.0%
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%50.0%
Axis
Title
Health Condition
Distribution of AVMA Respondent Owners' Health Condition by Gender
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< 1967(n=21)
1967-1976
(n=91)
1977-1986
(n=163)
1987-1996
(n=156)
1997-2006
(n=151)
2007-2011
(n=159)
2012-2016
(n=218)Excellent 33.3% 36.3% 35.6% 34.0% 37.1% 38.4% 28.9%Good 57.1% 49.5% 50.9% 57.7% 51.7% 52.2% 61.9%Fair 9.5% 12.1% 12.3% 8.3% 10.6% 8.8% 9.2%Poor 0.0% 2.2% 1.2% 0.0% 0.0% 0.0% 0.0%Very Poor 0.0% 0.0% 0.0% 0.0% 0.7% 0.6% 0.0%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
% R
espo
nden
ts
Graduation Year
Distribution of AAEP Respondents' Physical Health Condition by Graduation Year
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Figure 122: Distribution of AAEP Respondents’ Physical and Mental Health Condition by Graduation Year
< 1967(n=21)
1967-1976
(n=90)
1977-1986
(n=163)
1987 -1996
(n =156)
1997-2006
(n=150)
2007-2011
(n=159)
2012-2016
(n=218)Excellent 47.6% 62.2% 54.0% 43.6% 34.0% 20.8% 14.2%Good 52.4% 35.6% 38.0% 43.6% 45.3% 54.7% 56.0%Fair 0.0% 1.1% 6.1% 12.2% 17.3% 18.2% 25.2%Poor 0.0% 1.1% 1.8% 0.6% 3.3% 5.0% 4.1%Very Poor 0.0% 0.0% 0.0% 0.0% 0.0% 1.3% 0.5%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
% R
espo
nden
ts
Graduation Year
Distribution of AAEP Respondents' Mental Health Condition by Graduation Year
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Among the AAEP members surveyed, 43 percent of male respondents and 40 percent of
females reported that their physical health limited them somewhat from meeting the demands
of their job or daily life. The majority of respondents reported no limitation of daily activity
from physical health issues, while about one-third of each gender reported a ”little” limitation.
Nearly one-quarter of males reported that their mental health limited them a little to a great
deal in meeting the demands of their job or daily life, while 42.5 percent of females reported
their mental health affected their ability to meet the demands of their job or daily life a little to
a great deal. However, the majority of respondents reported no limitation, and most of the
respondents who reported limitations reported that they were limited “a little” (Figure 123).
Figure 123: Distribution of AAEP Respondents’ Physical and Mental Health Limitations on Daily Activities
Male (n=305) Female(n=487) Male (n=305) Female
(n=487)A great deal 1.3% 0.6% 0.7% 0.0%A lot 2.3% 1.4% 1.0% 1.4%A moderate amount 5.6% 3.9% 4.6% 6.6%A little 33.8% 33.7% 18.0% 34.5%Not at all 57.0% 60.4% 75.7% 57.5%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%
% o
f Res
pond
ents
Physical Health Mental Health
Distribution of AAEP Respondents' Physical and Mental Health Limitations on Daily Activities
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Work Injury
Nearly four-fifths of 959 AAEP respondents reported they had been injured while performing
work as a veterinarian. Of those respondents who reported work injuries, 44.2 percent were
male and 55.8 percent were female.
Survey respondents were asked the amount of time their injuries kept them from working, if at
all, by selecting all answers that applied to them. Out of the 764 respondents who were injured
at some point during their career and who answered this question, 48.0 percent of the
respondents did not miss work due to a work injury for at least one of the injuries they
reported having, 36.7 percent indicated no more than seven days of work were missed, 10.7
percent no more than 30 days (one month), 4.7 percent no more than 90 days (three months),
and 3.4 percent more than 90 days. 2.1 percent indicated they sustained a permanent disability
from an injury that occurred while practicing veterinary medicine (Figure 124).
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Figure 124: Distribution of AAEP Respondents' Number of Days out of Work Related to Injury Suffered at Work (select all that apply)
48.0% 36.7%10.7% 4.7% 3.4% 2.1%
52.0% 63.3%89.3% 95.3% 96.6% 97.9%
0%
20%
40%
60%
80%
100%
% o
f Res
pond
ents
# Days Out of Work
Distribution of AAEP Respondents' Number of Days Out of Work Related to Injury Suffered at Work (select all that apply)
Yes No
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Of those respondents who missed work because of injuries, 62.6 percent indicated this had
occurred more than once, with 53 percent reporting two to four times, 6 percent five to eight
times, and 3.6 percent more than eight times (Figure 125).
Figure 125: Distribution of AAEP Respondents' Number of Injuries Incurred While Practicing Veterinary Medicine That Caused Missed Work Time
When AAEP respondents were asked if they had been hospitalized or had surgery as a result of
an injury received while performing work as a veterinarian, 16.7 percent reported being
hospitalized and 20.3 percent reported having surgery for a work-related injury. Of the 956
respondents answering this question, 26.1 percent of male respondents reported that they had
been hospitalized compared to 9.7 percent of females; 33.6 percent of male respondents
reported having had surgery versus 10.7 percent of females (Table 91). Of the respondents who
were injured and required hospitalization and/or surgery, more than 65 percent were males
(Figure 126). In interpreting these results, it is important to remember that male respondents
had a mean of 29 years of experience compared to 12.3 years for female respondents.
37.3%
53.0%
6.0%3.6%
Distribution of AAEP Respondents' Number of Injuries Incurred While Practicing Veterinary Medicine That
Caused Missed Work Time (n=415)
One Two to four Five to eight More than eight
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Table 91: Distribution of AAEP Respondents’ Hospitalization and Surgery as a Result of Performing Work as a Veterinarian by Gender
Was hospitalized?
Had surgery?
Yes No
Yes No
Male (n=402) 26.1% 73.9%
33.6% 66.4% Female (n=554) 9.7% 90.3%
10.7% 89.3%
Figure 126: Distribution of AAEP Respondents' Result of a Work-Related Injury by Gender
Daily Activities
A health condition may limit a veterinarian in certain types of daily activities that they may
encounter on the job or in their personal life. These health limitations may affect the desire of a
veterinarian to work more or fewer hours, and can be used as a measure for
66.0% 69.6%
34.0% 30.4%
Hospitalization(n=159)
Surgery(n=194)
% o
f Res
pond
ents
Result of Related Work Injury
Distribution of AAEP Respondents' Result of A Work Related Injury by Gender
Male Female
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underemployment45. Vigorous activities such as running, lifting heavy objects, and participating
in strenuous sports and moderate activities such carrying equipment, working on horses’
hooves, floating teeth or playing golf, can be affected by the health limitations of a veterinarian
during a typical day. Among AAEP respondents, 51 percent of males reported their health
limited them during vigorous activities, compared to 36.9 percent of females (Figure 127). 24.0
percent of male and 16.1 percent of female respondents reported they were limited by health
issues in performing moderate activities in (Figure 128).
Limitations in performing moderate and vigorous activities due to health issues among AAEP
respondents increased the longer an AAEP respondent had been practicing veterinary medicine
(Table 92).
Figure 127: Distribution of How AAEP Respondents’ Health Limited Vigorous Activities by Gender
45 Please see Section 4.7 for information regarding underemployment.
12.1% 7.6%
38.9%29.3%
49.0%63.2%
Male (n=347) Female (n=516)
% o
f Res
pond
ents
Gender
Distribution of How AAEP Respondents’ Health Limited Vigorous Activities by Gender
A lot A moderate amount Not at all
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Figure 128: Distribution of How AAEP Respondents’ Health Limited Moderate Activities by Gender
Table 92: Distribution of How AAEP Respondents’ Health Limited Vigorous and Moderate Activities by Graduation Year
< 1967 (n=18)
1967-1976 (n=73)
1977-1986
(n=135)
1987-1996
(n=131)
1997-2006
(n=130)
2007-2011
(n=153)
2012-2016
(n=210) Vigorous Activities
A lot 33.3% 28.8% 11.1% 13.7% 6.9% 3.9% 3.3% A moderate amount
50.0% 49.3% 51.9% 38.9% 20.0% 25.5% 23.8%
Not at all 16.7% 21.9% 37.0% 47.3% 73.1% 70.6% 72.9% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Moderate Activities
A lot 5.6% 9.6% 3.0% 3.1% 1.5% 2.6% 1.9% A moderate amount
61.1% 31.5% 26.9% 22.9% 7.7% 9.2% 7.6%
Not at all 33.3% 58.9% 70.1% 74.0% 90.8% 88.2% 90.5% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
20.2% 13.6%
76.0% 83.9%
Male (n=347) Female (n=516)
% o
f Res
pond
ents
Gender
Distribution of How AAEP Respondents’ Health Limited Moderate Activities by Gender
A lot A moderate amount Not at all
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Physical Health – Past Four Weeks
AAEP respondents were asked how much of the time in the four weeks prior to completing this
survey did they have certain problems with their work or other regular daily activities as a result
of their physical health. 39.8 percent of male and 37.8 percent of female AAEP respondents
reported accomplishing less than they would have liked due to their physical health a little to all
of the time while 36.9 percent of males and 30.7 percent of females felt they were limited in
the kind of work or other activities they had participated in as a result of their physical health a
little to all of the time (Table 93).
Respondents who graduated from veterinary school longer ago reported a decreasing trend in
physical health that caused them to accomplish less than they would like, as well as limiting
them in the kinds of work they performed or regular daily activities in which they participated
(Table 94).
Table 93: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in Work and Other Activities as a Result of Their Physical Health by Gender
Male (n=344) Female (n=516)
Accomplished less than you would like All of the time 2.0% 1.4% Most of the time 6.1% 2.5% Some of the time 12.8% 9.5% A little of the time
18.9% 24.4%
None of the time 60.2% 62.2% Total 100.0% 100.0%
Were limited in the kind of work or other activities All of the time 2.3% 1.4% Most of the time 4.4% 2.1% Some of the time 12.5% 6.4% A little of the time
17.7% 20.8%
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None of the time 63.1% 69.3% Total 100.0% 100.0%
Table 94: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in Work and Other Activities as a Result of Their Physical Health by Graduation Year
Graduation Year
< 1967 (n=18)
1967-1976 (n=72)
1977-1986
(n=134)
1987-1996
(n=131)
1997-2006
(n=130)
2007-2011
(n=153)
2012-2016
(n=209) Accomplished less than you would like
All of the time
5.6% 2.8% 2.2% 3.1% 0.8% 0.7% 0.5%
Most of the time
11.1% 11.1% 6.0% 5.3% 3.8% 1.3% 1.4%
Some of the time
27.8% 23.6% 14.9% 10.7% 4.6% 7.8% 8.1%
A little of the time
16.7% 18.1% 23.1% 25.2% 24.6% 21.6% 21.1%
None of the time
38.9% 44.4% 53.7% 55.7% 66.2% 68.6% 68.9%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Were limited in the kind of work or other activities
All of the time
0.0% 2.8% 2.2% 3.8% 1.5% 1.3% 0.5%
Most of the time
11.1% 13.9% 2.2% 5.4% 2.3% 0.0% 0.0%
Some of the time
33.3% 15.3% 17.2% 10.8% 3.8% 6.6% 2.4%
A little of the time
22.2% 27.8% 22.4% 18.5% 15.4% 19.1% 19.6%
None of the time
33.3% 40.3% 56.0% 61.5% 76.9% 73.0% 77.5%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
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Emotional Health – Past Four Weeks
AAEP respondents were also asked how much of the time in the four weeks prior to completing
the survey they felt they accomplished less or were limited in their daily activities by feeling
depressed or anxious. 25.9 percent of male AAEP respondents and 45.2 percent of females
reported accomplishing less than they would have liked as a result of their emotional state a
little to all of the time, and 31.1 percent of males and 53.7 percent of females felt they did work
or participated in activities with less focus than usual as a result of their emotions a little to all
of the time (Table 95).
Across graduation years, recent graduates reported their emotional state interfering with
accomplishing tasks, and doing work or activities with less focus than usual occurring in greater
number than respondents who graduated prior to 2007 (Table 96).
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Table 95: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in Work and Other Activities as a Result of Their Emotional State by Gender
Male (n=344) Female (n=516)
Accomplished less than you would like All of the time 0.3% 0.6% Most of the time 2.9% 3.5% Some of the time 8.1% 14.0% A little of the time
14.5% 27.1%
None of the time 74.1% 54.8% Total 100.0% 100.0%
Did work or activities with less focus than usual All of the time 0.3% 0.6% Most of the time 2.3% 6.5% Some of the time 10.8% 18.2% A little of the time
17.7% 28.4%
None of the time 68.9% 46.3% Total 100.0% 100.0%
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Table 96: Distribution of AAEP Respondents’ Feelings on Accomplishing and Feeling Limited in Work and Other Activities as a Result of Their Emotional State by Graduation Year
Graduation Year
< 1967 (n=18)
1967-1976
(n=73)
1977-1986
(n=134)
1987-1996
(n=128)
1997-2006
(n=130)
2007-2011
(n=150)
2012-2016
(n=209) Accomplished less than you would like
All of the time
0.0% 0.0% 0.7% 0.8% 0.8% 0.7% 0.0%
Most of the time
0.0% 4.1% 2.2% 1.6% 2.3% 5.3% 3.8%
Some of the time
5.6% 5.5% 6.0% 8.5% 12.3% 12.5% 19.1%
A little of the time
22.2% 20.5% 13.4% 19.4% 18.5% 28.9% 27.8%
None of the time
72.2% 69.9% 77.6% 69.8% 66.2% 52.6% 49.3%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Did work or activities with less focus than usual
All of the time
0.0% 0.0% 0.0% 1.6% 0.0% 0.7% 0.5%
Most of the time
0.0% 0.0% 1.5% 3.9% 4.6% 8.7% 7.2%
Some of the time
22.2% 6.8% 10.4% 5.5% 16.9% 20.7% 22.5%
A little of the time
11.1% 28.8% 16.4% 25.8% 15.4% 24.7% 31.6%
None of the time
66.7% 64.4% 71.6% 63.3% 63.1% 45.3% 38.3%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Bodily Pain and Pain Interference – Past Four Weeks
AAEP respondents were asked how much bodily pain they had experienced during the four
weeks prior to completing the survey, as well as the degree to which pain had interfered with
their normal work, including both their work outside the home and their chores in daily living.
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Approximately two-thirds of male (63.6 percent) and female (67.4 percent) AAEP respondents
reported experiencing very mild to mild pain; 26.4 percent of males and 18.8 percent females
reported experiencing moderate to severe to very severe pain. Approximately half of male
(49.1 percent) and female respondents (52.1 percent) reported that pain did not interfere with
their normal work or chores in daily living; 47.4 percent of males and 46.3 percent of females
reported a little to a moderate amount of pain interference. The remaining respondents (3.5
percent males, 1.6 percent females) reported a lot to a great deal of interference from pain
(Table 97).
Table 97: Distribution of AAEP Respondents’ Bodily Pain and Pain Interference during the Past Four Weeks by Gender
Male (n=349) Female (n=516)
How much bodily pain? None 10.0% 13.8% Very mild 35.2% 36.8% Mild 28.4% 30.6% Moderate 23.8% 16.5% Severe 2.3% 1.9% Very Severe 0.3% 0.4% Total 100.0% 100.0%
Pain interference
Not at all 49.1% 52.1% A little 37.0% 37.4% A moderate amount 10.4% 8.9% A lot 2.3% 1.2% A great deal 1.2% 0.4% Total 100.0% 100.0%
The severity of bodily pain AAEP respondents experienced increased among respondents who
were further out from their graduation from veterinary school: 70.5 percent of respondents
who graduated between 2012 and 2016 reported very mild to mild pain while 44.6 percent of
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AAEP respondents who graduated 30 years ago (1967-1976) reported moderate to very severe
bodily pain (Figure 129).
Figure 129: Distribution of AAEP Respondents’ Level of Bodily Pain during the Past Four Weeks by Graduation Year
The level of pain interference with work and daily activities of life among AAEP respondents
increased as more time elapsed since a respondent’s graduation from veterinary college. While
1.8 percent of respondents who recently graduated from veterinary college (2007-2011 and
2012-2016 combined) reported a lot to a great deal of pain interference, 15.9 percent of
< 1967(n=18)
1967-1976
(n=74)
1977-1986
(n=136)
1987-1996
(n=131)
1997-2006
(n=130)
2007-2011
(n=153)
2012-2016
(n=210)Very Severe 0.0% 1.4% 0.0% 0.0% 0.8% 0.7% 0.0%Severe 0.0% 2.7% 2.2% 3.8% 2.3% 2.6% 0.5%Moderate 11.1% 40.5% 28.7% 23.7% 16.9% 11.8% 12.4%Mild 38.9% 25.7% 28.7% 31.3% 25.4% 29.4% 32.4%Very mild 38.9% 24.3% 33.8% 32.1% 41.5% 39.2% 38.1%None 11.1% 5.4% 6.6% 9.2% 13.1% 16.3% 16.7%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Graduation Year
Distribution of AAEP Respondents' Level of Bodily Pain during the Past Four Weeks by Graduation Year
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respondents who graduated prior to 2007 experienced a lot to a great deal of pain interference
(Figure 130).
Figure 130: Distribution of AAEP Respondents’ Level of Pain Interference during the Last Past Four Weeks by Graduation Year
< 1967(n=17)
1967-1976
(n=74)
1977-1986
(n=134)
1987-1996
(n=131)
1997-2006
(n=130)
2007-2011
(n=153)
2012-2016
(n=210)A great deal 0.0% 1.4% 0.7% 1.5% 0.8% 0.7% 0.0%A lot 0.0% 5.4% 2.2% 2.3% 1.5% 0.7% 0.5%A moderate amount 11.8% 20.3% 13.4% 10.7% 10.8% 5.9% 5.2%A little 47.1% 36.5% 41.0% 40.5% 28.5% 35.9% 37.1%Not at all 41.2% 36.5% 42.5% 45.0% 58.5% 56.9% 57.1%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Graduation Year
Distribution of AAEP Respondents' Level of Pain Interference during the Past Four Weeks by Graduation Year
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4.8.2 PROFESSIONAL QUALITY OF LIFE
External factors that can affect wellness of an equine veterinarian include but are not limited
to: a veterinarian’s involvement in certain competitive sectors or business components of the
industry, frequent interaction with multiple stakeholders (e.g., owners, riders, trainers), and the
physically grueling and dangerous environment of an equine practice. In addition, changing
technology has allowed new ways to communicate with clients, but at the same time has
presented challenges to the overall wellness of an equine veterinarian due to expectations for
immediate responses in communication along multiple channels. Also affecting quality of life is
a veterinarian’s outlook on the work he or she performs. Questions from the Professional
Quality of Life (ProQOL) tool were included in the AVMA-AAEP 2016 Survey of Equine
Practitioners to investigate the effect that expending compassion in the course of a
veterinarian’s work has on the practitioner’s well-being (Stamm, 2010).
The ProQOL application is used to measure compassion satisfaction, burnout and secondary
traumatic stress associated with helping others who have experienced suffering. Compassion
satisfaction is about the pleasure someone derives from their work. An individual might, for
example, feel like it is a pleasure to help others through the work that he or she does, and
might feel positively about colleagues or his or her ability to contribute to the work setting or
the greater good of society by working with people who need care. On the other hand, negative
feelings derived from work is measured by scoring of burnout (exhaustion, frustration, anger,
depression) and secondary traumatic stress (work-related trauma) (Stamm, 2010).
Responses to the ProQOL questions are scored based on the responses of thousands of
individuals across a number of occupations. The scores have been established to describe low-,
normal- and high-compassion satisfaction, burnout and secondary traumatic stress. This tool
relies on a different set of 10 ranking questions for compassion satisfaction, burnout and
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secondary traumatic stress. Respondents are asked to rank each question using the rank scale:
1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = very often. The rank sum of each set of
questions is used in determining the ProQOL score for each of the three areas: Less than a sum
of 22 is considered a low score (equates to a ProQOL score of 43 or less), between 23 and 41 is
considered average (equates to a ProQOL score around 50), and 42 or more is considered high
(equates to a ProQOL score of 57 or more). For all intents and purposes, however, the
summation of each set of questions is also referred to the raw score and is used for reporting
purposes. The ProQOL average scores are based on the average across all professions and not
specific groups. Table 98 can be used to convert the raw score to the 1-100 scale.46 The
maximum raw score on the ProQOL is 50 and the total percentiles available are 100 (Stamm,
2010).47
Table 98: Raw Scores to ProQOL T-Score Conversion Chart
Compassion Satisfaction Burnout Secondary Traumatic Stress %tile Raw score t score %tile Raw Score t score %tile Raw Score t score
1 13 19 1 5 28 1 1 34 2 16 23 2 7 31 2 2 35 3 19 27 3 8 32 3 2 35 4 22 31 4 9 34 4 3 36 5 24 34 5 10 35 5 3 36 6 24 34 6 10 35 6 3 36 7 25 35 7 11 37 7 4 38 8 26 36 8 11 37 8 4 38 9 27 37 9 11 37 9 4 38
46 From the ProQOL website: “When using this table to convert scores, it should be noted that the conversion from raw scores to standardized t-scores is not strictly numeric as there are more scores available on a standardized t-score than on the raw score. Calculations using the SPSS scoring scheme will have some variance in compassion to the table. The variance is trivial, and only applies if a person is on the border of a cut score. The maximum score on the ProQOL is 50 and the total percentiles available are 100.” http://proqol.org/uploads/ProQOL_Concise_2ndEd_12-2010.pdf, page .31 47 http://proqol.org/uploads/ProQOL_Concise_2ndEd_12-2010.pdf, page .31
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Compassion Satisfaction Burnout Secondary Traumatic Stress %tile Raw score t score %tile Raw score t score %tile Raw score t score
10 27 37 10 12 38 10 4 38 11 27 37 11 12 38 11 5 39 12 28 39 12 12 38 12 5 39 13 28 39 13 13 39 13 5 39 14 29 40 14 13 39 14 5 39 15 29 40 15 13 39 15 5 39 16 30 41 16 14 41 16 5 39 17 30 41 17 14 41 17 6 41 18 30 41 18 14 41 18 6 41 19 31 43 19 14 41 19 6 41 20 31 43 20 14 41 20 6 41 21 31 43 21 15 42 21 6 41 22 31 43 22 15 42 22 7 42 23 32 44 23 15 42 23 7 42 24 32 44 24 15 42 24 7 42 25 32 44 25 15 43 25 7 42 26 32 44 26 16 44 26 7 42 27 33 45 27 16 44 27 8 43 28 33 45 28 16 44 28 8 44 29 33 45 29 16 44 29 8 44 30 33 45 30 16 44 30 8 44 31 34 47 31 16 44 31 8 44 32 34 47 32 17 45 32 8 44 33 34 47 33 17 45 33 8 44 34 34 47 34 17 45 34 9 45 35 35 48 35 17 45 35 9 45 36 35 48 36 17 45 36 9 45 37 35 48 37 18 46 37 9 45 38 35 48 38 18 46 38 9 45 39 35 48 39 18 46 39 10 46 40 36 49 40 18 46 40 10 47 41 36 49 41 19 48 41 10 47 42 36 49 42 19 48 42 10 47
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Compassion Satisfaction Burnout Secondary Traumatic Stress %tile Raw score t score %tile Raw score t score %tile Raw score t score
43 36 49 43 19 48 43 10 47 44 36 49 44 19 48 44 10 47 45 36 49 45 19 48 45 11 48 46 37 51 46 19 48 46 11 48 47 37 51 47 19 48 47 11 48 48 37 51 48 20 49 48 11 48 49 37 51 49 20 49 49 11 48 50 37 20 50 20 50 50 11 49 51 38 52 51 20 50 51 12 50 52 38 52 52 20 50 52 12 50 53 38 52 53 21 51 53 12 50 54 38 52 54 21 51 54 12 50 55 38 52 55 21 51 55 12 50 56 39 53 56 21 51 56 12 50 57 39 53 57 21 51 57 13 51 58 39 53 58 21 51 58 13 51 59 39 53 59 21 51 59 13 51 60 39 53 60 22 52 60 13 51 61 39 53 61 22 52 61 13 52 62 40 55 62 22 52 62 14 52 63 40 55 63 22 52 63 14 52 64 40 55 64 23 53 64 14 52 65 40 55 65 23 53 65 14 52 66 40 55 66 23 53 66 15 54 67 40 55 67 23 53 67 15 54 68 41 56 68 23 53 68 15 54 69 41 56 69 24 55 69 15 54 70 41 56 70 24 55 70 15 54 71 41 56 71 24 55 71 16 55 72 41 56 72 25 56 72 16 55 73 42 57 73 25 56 73 16 55 74 42 57 74 25 56 74 16 55 75 42 57 75 25 56 75 17 56
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Compassion Satisfaction Burnout Secondary Traumatic Stress %tile Raw score t score %tile Raw score t score %tile Raw score t score
76 42 57 76 26 58 76 17 57 77 42 57 77 26 58 77 17 57 78 43 59 78 26 58 78 17 57 79 43 59 79 26 58 79 17 57 80 43 59 80 27 59 80 18 58 81 43 59 81 27 59 81 18 58 82 43 59 82 28 60 82 18 58 83 44 60 83 28 60 83 19 60 84 44 60 84 28 60 84 19 60 85 44 60 85 29 62 85 19 60 86 44 60 86 29 62 86 20 61 87 45 61 87 29 62 87 20 61 88 45 61 88 30 63 88 21 62 89 45 61 89 30 63 89 21 62 90 46 62 90 31 65 90 22 64 91 46 62 91 31 65 91 22 64 92 46 62 92 31 65 92 23 65 93 46 62 93 32 66 93 23 66 94 46 62 94 32 66 94 24 67 95 47 64 95 33 68 95 26 70 96 47 64 96 34 69 96 27 71 97 48 65 97 34 69 97 28 73 98 49 66 98 36 72 98 29 75 99 50 68 99 37 73 99 31 77
The results from the AVMA-AAEP 2016 Survey of Equine Practitioners indicated that mean
ProQOL scores for burnout and secondary traumatic stress were in the lower normal range,
while compassion satisfaction was in the higher normal range. But these mean scores fail to
illustrate the number of respondents who were in the high range for burnout and secondary
traumatic stress. The results of the ProQOL sums were plotted against the percentage of
respondents.
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4.8.2.1 Compassion Satisfaction
The mean sum of Equine respondents’ compassion satisfaction was slightly higher than AVMA
respondents’: 37.5 vs. 36.4. The distribution of compassion satisfaction scores followed a
normal distribution in both the Equine and AVMA samples that was skewed left. The average
raw ProQOL score for compassion satisfaction is between 23 and 41 (average ProQOL score
around 50). Less than a 22 is considered a low score for compassion satisfaction. Several Equine
respondents reported higher levels of compassion satisfaction than did AVMA respondents
(Figure 131).
Figure 131: Distribution of Equine and AVMA Respondents’ Compassion Satisfaction Score
The mean compassion satisfaction score by graduation year increased with experience or years
from graduation. Equine respondents who graduated between 2012 and 2016 had a mean
score of 36.2, while those who graduated prior to 1967 had a mean score of 43.7 (Table 99).
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
0 5 10 15 20 25 30 35 40 45 50 55
% o
f Res
pond
ents
Compassion Satisfaction Score
Distribution of Respondents' Compassion Satisfaction Score
Equine (n=808) AVMA (n=2,323)
Average across all professions
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Table 99: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Graduation Year
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. < 1967 6 43.7 3.4 40 50 59 39.3 6.4 21 50 1967-1976 49 40.6 6.0 26 50 102 39.1 6.0 24 50 1977-1986 118 39.9 6.3 24 50 173 39.1 6.2 23 50 1987-1996 134 38.3 6.3 20 50 334 37.8 6.4 21 50 1997-2006 141 37.3 6.3 23 50 591 35.8 6.9 14 50 2007-2011 163 35.7 6.8 16 50 473 35.4 6.8 12 50 2012-2016 189 36.2 5.9 12 50 557 35.3 6.2 16 50
The mean compassion satisfaction score between males and females was significantly different
for both Equine and AVMA samples (p-value < .001). For both samples the mean score was
higher for males than females (Table 100).
Table 100: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Gender
Equine AVMA
Obs. Mean Std. Dev. Min Max Obs. Mean Std. Dev. Min. Max. Male 326 38.7 6.7 16 50 733 37.3 6.7 14 50 Female 480 36.6 6.2 12 50 1,583 35.9 6.6 12 50
The mean compassion satisfaction score was significantly different between Equine
respondents who participated in an internship and those who did not (p-value < .001), but it
was not significant for the AVMA sample, whose scores for intern participants and non-intern
participants were almost identical. Because older practitioners rarely did internships and
younger equine veterinarians often did, the following mean compassion satisfaction is broken
out by internship and year of graduation. Among the Equine respondents who participated in
an internship and who did not participate in an internship, the mean score increased the longer
the respondents have been out of veterinary school, with Equine respondents who did not
participate in an internship having a higher mean compassion satisfaction score. Among the
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AVMA sample, they reveal a similar distribution of mean compassion satisfaction increasing the
longer a respondent has been out of veterinary college (Table 101).
Table 101: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Internship
Equine Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 148 36.29 5.59 23 49 6-10 years 121 35.35 6.70 16 50 11-20 years 90 36.56 6.30 23 49 21-30 years 58 38.02 6.94 21 50 31 or more years 46 39.59 5.62 26 50
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 41 35.68 7.07 12 50 6-10 years 42 36.52 7.25 21 50 11-20 years 51 38.73 6.00 23 50 21-30 years 76 38.51 5.81 20 50 31 or more years 127 40.45 6.34 24 50
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AVMA Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 151 35.10 6.28 16 49 6-10 years 164 35.84 6.49 16 50 11-20 years 158 35.94 7.27 14 50 21-30 years 70 38.27 6.67 25 50 31 or more years 49 39.73 5.51 29 50
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 406 35.42 6.13 19 50 6-10 years 308 35.07 6.96 12 50 11-20 years 432 35.73 6.84 17 50 21-30 years 263 37.67 6.27 21 50 31 or more years 284 39.06 6.25 21 50
In terms of ownership status, the results indicated that for both AVMA and Equine samples
practice owners had a higher mean compassion satisfaction score than associates. The mean
score for Equine respondent owners was 39 vs. 36.2 for Equine respondent associates. The
AVMA sample yielded a mean score of 38.4 for owners and 35.4 for associates. Differences in
both samples were statistically significant at p-value <.001 (Table 102).
Table 102: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Practice Ownership
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Owner 323 39.0 6.3 23 50 408 38.4 6.2 21 50 Associate 255 36.2 6.5 12 50 1,066 35.4 6.7 12 50
Differences were found to be statistically significant between board- and non-board-certified
respondents in both the Equine and AVMA samples (Equine: p-value = .016; AVMA: p-value
=.027). In the Equine sample, non-board certified respondents had a higher mean compassion
satisfaction score than board-certified respondents, compared to the AVMA sample where
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board-certified respondents had a higher mean score than non-board-certified respondents
(Table 103).
Table 103: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Board Certification
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Board Certified
142 36.3 6.6 18 50 335 37.1 6.5 18 50
Non-Board Certified
666 37.7 6.4 12 50 1,984 36.3 6.7 12 50
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The mean compassion satisfaction score increased with level of income. Scores were typically
lower for lower income categories but then increased along with income (Table 104).
Table 104: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Professional Income
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. $20,000 to $29,999
31 37.7 6.1 24 50 59 37.1 6.1 22 50
$30,000 to $39,999
29 36.4 8.3 12 50 87 35.6 6.8 19 49
$40,000 to $49,999
49 37.6 4.8 26 48 110 35.4 6.7 19 50
$50,000 to $59,999
45 35.3 6.7 18 50 129 35.8 6.2 21 50
$60,000 to $69,999
74 36.1 6.8 20 50 213 35.3 6.6 12 50
$70,000 to $79,999
85 35.5 6.4 16 50 248 35.3 6.7 16 50
$80,000 to $89,999
62 37.0 6.4 19 50 241 35.9 6.2 18 50
$90,000 to $99,999
39 36.5 7.1 20 50 163 35.8 6.7 16 50
$100,000 to $124,999
111 37.5 6.9 21 50 310 36.6 7.2 16 50
$125,000 to $149,999
48 39.1 4.9 28 50 153 36.8 6.2 19 50
$150,000 to $174,999
47 39.1 5.5 26 50 81 38.7 6.3 22 50
$175,000 to $199,999
22 40.4 5.6 30 50 48 38.9 6.0 27 50
$200,000 to $249,999
22 41.1 5.9 30 50 83 38.6 6.0 24 50
$250,000 to $500,000
42 40.9 5.9 25 50 77 38.3 6.8 21 50
> $500,000 6 43.3 3.5 40 50 19 39.4 6.2 27 50
Respondents who currently had veterinary educational debt had a lower mean satisfaction
compassion score than those respondents, both Equine and AVMA, who did not currently have
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such debt. Mean score differences among those who currently owed and those who did not
currently owe in both samples were statistically significant (p-value < .001) (Table 105).
Table 105: Mean Equine and AVMA Respondents’ Compassion Satisfaction Score by Veterinary Educational Debt
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Currently Owe 344 35.9 6.5 12 50 1,171 35.3 6.8 12 50 Do not currently owe
269 39.0 6.3 20 50 677 37.4 6.6 12 50
Within the primary equine sectors of AAEP respondents, the lowest mean compassion
satisfaction score was reported by respondents in equine companion (36.8) and reproductive
(36.8) sectors. The highest mean score was reported by respondents in the Standardbred racing
sector (40.9), followed closely by respondents in the Western performance sector (40.5) (Table
106).
Table 106: Mean AAEP Respondents’ Compassion Satisfaction Score by Primary Equine Sector48
AAEP
Obs. Mean Std. Dev. Min. Max. English performance 80 38.4 6.1 21 50 Equine companion 25 36.8 7.0 24 50 Racing - Quarter Horse 5 38.4 8.0 30 50 Racing - Standardbred 7 40.9 7.0 29 50 Racing - Thoroughbred 27 37.4 7.4 24 50 Reproductive 29 36.8 7.8 20 50 Ranch or working 9 39.4 5.7 30 48 Western performance 17 40.5 5.9 30 50 General equine 317 37.8 6.5 12 50
Examining compassion satisfaction by the primary business model of AAEP respondents
revealed the lowest mean compassion satisfaction score was reported by respondents working
48 Gaited breeds was omitted because the number of observations did not permit estimation.
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in a haul-in only facility (35.7). The highest mean score was reported by respondents in an
ambulatory practice with haul-in facility (38.4) (Table 107).
Table 107: Mean AAEP Respondents’ Compassion Satisfaction Score by Business Model
AAEP
Business Model Obs. Mean Std. Dev. Min. Max. Ambulatory 190 37.6 6.5 21 50 Ambulatory with Haul-in facility 183 38.4 6.7 12 50 Haul-in only facility 7 35.7 6.7 27 44 Specialty/referral hospital-Limited service (e.g., no colic surgery, isolation, neonatology)
12 38.2 7.0 21 49
Specialty/referral hospital-Full service 9 37.8 7.4 26 50 Specialty/referral hospital-Limited service with ambulatory division
15 38.1 6.5 28 48
Specialty/referral hospital-Full service with ambulatory division
83 38.2 6.5 20 50
Other 20 37.7 7.2 24 50
Factors Affecting Compassion Satisfaction
To examine what factors were associated with low compassion satisfaction, a multiple linear
regression was conducted with the variables thought might contribute to the variation in
compassion satisfaction. Variables that are significant at the 10 percent, 5 percent and 1
percent level are reported in explaining the factors affecting compassion satisfaction. The main
factors under observation were: satisfaction with current employment, how well a
respondent’s education prepared them to become a veterinarian, professional income, current
debt, hours worked per week, gender, year of graduation, community size in which a
respondent practices, compensation method, internship and residency participation, board
certification, practice ownership, and marital status. Additional variables were added to the
AAEP model to investigate what equine-specific factors influenced compassion satisfaction,
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such as practice type and business model and sector. Additional variables in the AVMA model
included type of employment.
To avoid statistical errors, baseline variables are used to compare with other variables in
respective groups. The baseline variables were: community size of 50,001 to 500,000 residents
in the AAEP model and 2,500 to 49,999 in the AVMA model, and salary compensation method.
Specific AAEP sample baseline variables were: general equine practice sector and ambulatory
practice business model, and for the AVMA sample, companion animal practice.
The coefficient in Table 108 indicates a positive or negative association with compassion
satisfaction, and the impact on the increase or decrease of a variable’s score. An AAEP
respondent who is not married has a coefficient of -1.60, for example, meaning that there is a
negative association with compassion satisfaction compared to a married respondent; for a
respondent who is single, compassion satisfaction on average decreases by 1.60.
The final column labeled “Sig.” represents the significant variables. These variables, also known
as p-values, are such that for a “sig” less than 0.10, the coefficient is statistically different from
“0.” For AAEP respondents who work in a community size of 500,001 or more residents, for
instance, the p-value is 0.06; this means it is statistically significantly different from the baseline
working in a community with 50,001 to 500,000 residents.
The results of this analysis indicate that several factors in both samples were statistically
significant. In the AAEP sample, private practice owned by a single veterinarian, participation in
an internship, practice ownership, and not married were found to have a negative association
with compassion satisfaction, while being satisfied with employment, feeling prepared from
veterinary education, serving an area with 501,000 or mores residents, and working in an
ambulatory with haul-in facility practice were positively associated with compassion
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satisfaction. Among the AVMA sample, being satisfied with employment, feeling prepared from
veterinary education, working in non-veterinary employment and in advanced education had a
positive association with compassion satisfaction, while current veterinary educational debt,
serving an area with 500,000 or more residents, being compensated on an hourly basis, and
working in the federal government revealed a negative association with compassion
satisfaction.
The factors that were included in this model produced an adjusted R-square of 0.2938 in the
AAEP sample and .3301 in the AVMA sample. This indicates that the inclusion of all these
factors was able to explain 29 percent and 33 percent of the variation between the individually
reported compassion satisfaction score and the estimated mean compassion. Thus, there are
important variables that determine compassion satisfaction that have not been included and
are due to other unobservable factors.
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Table 108: Factors Affecting Compassion Satisfaction
AAEP Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) 2.170 0.363 0.00*** Education Preparation (5=Extremely well/1=Not well at all) 1.820 0.432 0.00*** Income 0.000 0.000 0.26 Currently owe debt (Yes=1) -1.297 0.926 0.16 Hours worked per week -0.007 0.012 0.53 Graduation Year 0.047 0.044 0.29 Gender (Female=1) 0.433 0.794 0.59 Under 2,500 residents 0.026 1.242 0.98 2,501 to 10,000 residents -0.345 1.001 0.73 10,001 to 25,000 residents -0.274 0.965 0.78 25,001 to 50,000 residents 1.131 1.018 0.27 50,001 to 500,000 residents (baseline) Omitted 501,000 or more residents 1.901 0.992 0.06* Private practice owned by a single veterinarian (Yes=1) -2.525 0.704 0.00*** Private practice/private corporation (baseline) Omitted Salary (baseline) Omitted Hourly or per diem -0.353 2.351 0.88 Production only -0.762 1.109 0.49 Salary with production-based incentive 0.019 0.943 0.98 Salary without production-based incentive 1.993 2.790 0.48 Owner with no differentiation 0.006 1.160 1.00 Owner with differentiation 0.865 1.329 0.52 Other method -2.498 1.976 0.21 Internship (Yes=1) -1.336 0.708 0.06* Residency (Yes=1) -0.002 1.405 1.00 Board Certified (Yes=1) -1.612 1.467 0.27 Practice Ownership (Yes=1) -1.719 0.964 0.08* General equine (baseline) Omitted
Working 0.610 2.544 0.81 English performance 0.576 0.910 0.53 Companion -1.393 1.427 0.33 Quarter Horse racing 3.357 3.018 0.27 Standardbred racing 2.051 2.906 0.48
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Thoroughbred racing -0.551 1.551 0.72 Reproductive 2.091 1.454 0.15 Western performance 2.285 1.712 0.18 Ambulatory (baseline) Omitted
Ambulatory with haul-in facility 1.325 0.757 0.08* Haul-in only 0.463 2.795 0.87 Specialty/referral - limited service hospital 2.155 2.354 0.36 Specialty/referral - full service hospital 1.927 2.513 0.44 Specialty/referral - limited service hospital with ambulatory -0.445 2.058 0.83 Specialty/referral - full service hospital with ambulatory 1.587 1.006 0.12 Other business model 0.334 1.877 0.86 Not Married (Yes=1) -1.600 0.729 0.03** Constant 23.119 2.660 0.00***
Observations 365
Adjusted R-Square 0.2938
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) 3.337 0.179 0.00*** Education Preparation (5=Extremely well/1=Not well at all) 1.715 0.217 0.00*** Income 0.000 0.000 0.11 Currently owe debt (Yes=1) -1.162 0.464 0.01*** Hours worked per week -0.014 0.012 0.25 Graduation Year -0.004 0.026 0.89 Gender (Female=1) -0.120 0.392 0.76 Under 2,500 residents -0.508 0.789 0.52 2,500 to 49,999 residents (baseline) Omitted 50,000 to 499,999 residents -0.496 0.380 0.19 500,000 or more residents -0.871 0.482 0.07* Companion animal (baseline) Omitted Food Animal 0.485 1.026 0.64
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Equine 0.331 0.794 0.68 Mixed Animal 1.021 0.664 0.12 Federal Government -7.876 3.216 0.01*** College/University 2.039 2.773 0.46 State/Local Government 0.079 2.762 0.98 Industry/Commercial -3.544 2.468 0.15 Not-for-profit -2.166 1.965 0.27 Advanced education 3.089 1.340 0.02** Other Vet Employment 0.774 1.175 0.51 Non-Vet Employment 6.086 3.184 0.06* Salary (baseline) Omitted Hourly -1.935 0.738 0.01*** Production only 0.599 0.599 0.32 Mix of salary with opportunity for production-based compensation 0.089 0.397 0.82 Owner withdrawals -0.968 0.645 0.13 Internship (Yes = 1) -0.254 0.443 0.57 Residency (Yes = 1) -0.186 1.161 0.87 Board Certified (Yes=1) -0.252 1.072 0.81 Practice Ownership (Yes=1) 0.454 0.568 0.42 Not Married (Yes=1) -0.094 0.368 0.80 Constant 19.132 1.356 0.00***
Observations 1,182
Adjusted R-Square 0.3315
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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4.8.2.2 Burnout
The mean sum of Equine respondents’ burnout score was a little less than the AVMA
respondents: 24.8 vs. 27.0. The average raw ProQOL score for burnout is between 23 and 41
(average ProQOL score around 50). The burnout scores from both the Equine and AVMA
samples were normally distributed with the mean at the low end of the normal range.
However, 5.8 percent of Equine respondents (AVMA: 9.2 percent) had scores in excess of 35
(Figure 132). A score above 35 on the burnout scale may suggest a need to seek help to deal
with the factors that are causing burnout.
Figure 132: Distribution of Equine and AVMA Respondents’ Burnout Score
The mean burnout score by graduation year decreased with experience or years since
graduation. Equine respondents who graduated between 2012 and 2016 had a mean score of
26.4, which increased among respondents who graduated in 2007-2011 (27.1). Those who
graduated prior to 1967 had a mean score of 19 (Table 109).
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
0 5 10 15 20 25 30 35 40 45 50
% o
f Res
pond
ents
Burnout Score
Distribution of Respondents' Burnout Score
Equine (n=809) AVMA (n=2,326)
Average across all professions
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Table 109: Mean Equine and AVMA Respondents’ Burnout Score by Graduation Year
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. < 1967 6 19.0 3.2 13 22 59 20.1 4.5 13 36 1967-1976 48 19.8 4.5 10 32 104 21.7 4.4 14 33 1977-1986 118 22.2 6.0 11 40 174 23.5 5.1 12 40 1987-1996 133 23.3 5.8 12 38 334 25.6 5.7 12 41 1997-2006 143 25.6 6.5 12 42 591 27.5 5.9 13 44 2007-2011 163 27.1 6.1 11 42 473 28.5 5.8 15 43 2012-2016 190 26.4 5.9 14 40 556 28.6 5.6 15 45
The mean burnout score between males and females was significantly different for both the
Equine and AVMA samples (p < .001). For both samples the mean score was lower for males
than it was for females (Table 110).
Table 110: Mean Equine and AVMA Respondents’ Burnout Score by Gender
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Male 327 22.9 6.0 10 40 738 24.9 6.0 12 44 Female 480 26.2 6.1 13 42 1,582 27.9 5.8 14 45
The mean burnout score was significantly different between Equine and AVMA respondents
who participated in an internship and those who did not participate in an internship (Equine: p
< .001; AVMA: p = .021). The mean burnout score for internship participation is examined by
graduation year, as internship participation rates have increased in more recent years. Overall,
in both samples (those respondents who participated in an internship and those who did not),
burnout score on average decreased the longer a respondent was out of veterinary school. The
average burnout score among AVMA respondents was a little higher than AAEP respondents
(Table 111).
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Table 111: Mean Equine and AVMA Respondents’ Burnout Score by Internship
Equine Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 149 26.17 5.78 14 39 6-10 years 120 27.73 6.25 11 42 11-20 years 91 26.04 6.38 13 42 21-30 years 58 24.12 6.45 13 38 31 or more years 47 21.81 5.53 11 36
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 41 27.02 6.20 14 40 6-10 years 43 25.42 5.39 14 38 11-20 years 52 24.94 6.74 12 42 21-30 years 75 22.75 5.14 12 34 31 or more years 125 21.30 5.68 10 40
AVMA Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 150 29.03 5.83 18 45 6-10 years 166 28.42 5.77 16 42 11-20 years 162 27.72 6.27 14 44 21-30 years 71 24.93 5.75 14 40 31 or more years 49 21.55 4.27 14 31
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 406 28.41 5.58 15 42 6-10 years 306 28.50 5.81 15 43 11-20 years 428 27.39 5.71 13 43 21-30 years 262 25.79 5.65 12 41 31 or more years 287 22.45 5.04 12 40
For both the Equine and AVMA samples, practice owners had a lower mean burnout score than
did associates. The mean score for Equine respondent owners was 23.5 vs. 26.4 for Equine
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respondent associates. The AVMA sample yielded a mean score of 25.9 for owners and 28.2 for
associates. The AAEP and AVMA samples’ ownership status with respect to burnout score were
statistically significant at p < .001 (Table 112).
Table 112: Mean Equine and AVMA Respondents’ Burnout Score by Practice Ownership
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Owner 321 23.5 6.3 10 42 407 25.9 5.9 12 43 Associate 257 26.4 6.1 11 42 1,065 28.2 5.9 12 45
Burnout scores were significant between board-certified and non-board-certified respondents
in the AVMA sample (p<.001) but not in the Equine sample (Table 113).
Table 113: Mean Equine and AVMA Respondents’ Burnout Score by Board Certification
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Board Certified
142 25.4 6.4 11 42 343 25.7 6.0 13 44
Non-Board Certified
667 24.7 6.3 10 42 1,979 27.2 6.0 12 45
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The mean burnout score decreased with the level of income of Equine and AVMA respondents.
The trend showed that scores were typically higher for lower income categories but decreased
as the income categories got larger; also the mean of Equine respondents tended to be lower
than AVMA respondents (Table 114).
Table 114: Mean Equine and AVMA Respondents’ Burnout Score by Professional Income
Income Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. $20,000 to $29,999
30 25.6 6.3 13 40 59 26.7 5.8 17 43
$30,000 to $39,999
31 24.4 6.7 15 37 84 28.2 5.7 14 40
$40,000 to $49,999
49 26.3 5.2 15 37 109 27.5 5.6 16 41
$50,000 to $59,999
45 27.5 7.1 15 41 129 27.9 5.4 16 42
$60,000 to $69,999
74 26.9 6.0 14 42 212 28.3 5.5 18 44
$70,000 to $79,999
86 27.0 6.5 13 42 245 28.3 5.9 13 41
$80,000 to $89,999
62 25.1 6.1 14 39 242 27.7 5.5 15 45
$90,000 to $99,999
38 23.8 5.6 13 35 163 27.3 5.5 12 42
$100,000 to $124,999
111 24.5 6.6 11 41 313 27.4 6.3 14 43
$125,000 to $149,999
49 24.3 5.5 12 38 153 27.8 6.1 17 44
$150,000 to $174,999
48 22.4 5.8 11 38 81 24.5 5.4 13 37
$175,000 to $199,999
22 22.6 5.4 13 33 48 24.1 5.2 17 44
$200,000 to $249,999
21 21.9 4.5 14 31 86 25.2 5.9 14 39
$250,000 to $500,000
41 20.1 4.8 10 33 76 25.7 6.1 15 41
> $500,000 6 18.2 3.4 13 23 19 23.6 6.4 14 37
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Respondents who had current veterinary educational load debt had a higher mean burnout
score than those respondents, both Equine and AVMA, who did not currently owe any
veterinary educational debt. Those who currently owed and who did not currently owe in the
AAEP and AVMA samples were statistically significant with respect to burnout score (p < .010)
(Table 115).
Table 115: Mean Equine and AVMA Respondents’ Burnout Score by Veterinary Educational Debt
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Currently Owe
346 26.7 6.2 12 42 1,173 28.5 5.9 14 44
Do not currently owe
269 23.2 6.1 11 42 677 25.8 5.7 13 45
Within the primary equine sectors of AAEP respondents, the lowest mean burnout score was
reported by respondents in Western performance (20.8). The highest mean score was reported
by respondents in the equine companion sector (26.8) (Table 116).
Table 116: Mean AAEP Respondents’ Burnout Score by Primary Equine Sector
AAEP
Obs. Mean Std. Dev. Min Max English performance 80 24.7 6.1 13 40 Equine companion 24 26.8 8.4 15 42 Racing - Quarter Horse 5 22.6 7.1 13 30 Racing - Standardbred 7 22.4 8.6 13 38 Racing - Thoroughbred 27 23.7 6.5 14 41 Reproductive 30 24.0 5.2 14 34 Ranch or working 9 25.3 4.9 18 32 Western performance 17 20.8 5.1 12 32 General equine 318 24.5 6.3 10 42
Within the primary business model of AAEP respondents, the lowest mean burnout score was
reported by respondents working in a full-service specialty/referral hospital with ambulatory
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division (23.8). The highest mean score was reported by respondents in a haul-in only facility
(25.9) (Table 117).
Table 117: Mean AAEP Respondents’ Burnout Score by Business Model
AAEP Obs. Mean Std. Dev. Min. Max.
Ambulatory 189 24.6 6.7 12 42 Ambulatory with Haul-in facility 182 24.3 6.2 10 42 Haul-in only facility 7 25.9 6.4 13 32 Specialty/referral hospital-Limited service (e.g., no colic surgery, isolation, neonatology)
12 24.6 6.6 17 36
Specialty/referral hospital-Full service 9 24.7 6.4 14 33 Specialty/referral hospital-Limited service with ambulatory division
15 25.3 6.9 17 40
Specialty/referral hospital-Full service with ambulatory division
84 23.8 6.0 11 41
Other 21 24.9 6.4 14 36
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Factors Affecting Burnout
Using the same approach to examine the factors associated with burnout that was used with
compassion satisfaction, several factors were found to be statistically significant in both the
AAEP and AVMA samples. Factors associated with a lower burnout score (negative coefficient)
among AAEP respondents were: satisfaction with their current employment, a belief that their
education prepared them well for veterinary medicine, working in a private practice owned by
a single veterinarian, and working in Western and reproductive equine sectors. Among AVMA
respondents, these factors were: satisfaction with their current employment, believing that
their education prepared them well for veterinary medicine, graduation year (increased
experience), and working in mixed animal or food animal sectors or at a college/university.
Increased coefficients associated with burnout scores among AAEP respondents were: current
debt, hours worked (each additional hour worked adds .02 to burnout score), other form of
compensation, and internship participation. Among AVMA respondents, being female, hours
worked per week, and being a practice owner were correlated with higher mean levels of
burnout (Table 118).
The factors that were included in this model produced an adjusted R-square of 0.2856 in the
AAEP sample and .2979 in the AVMA sample. This indicates that the inclusion of all these
factors was able to explain 29 percent and 30 percent of the variation between the individually
reported burnout score and the estimated mean burnout. Thus, there are important variables
that determine burnout that have not been included and are due to other unobservable
factors.
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Table 118: Factors Affecting Burnout
AAEP Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) -1.971 0.358 0.00*** Education Preparation (5=Extremely well/1=Not well at all) -0.966 0.426 0.02** Income 0.000 0.000 0.28 Currently owe debt (Yes=1) 1.994 0.910 0.03** Hours worked per week 0.023 0.012 0.05** Graduation Year -0.035 0.044 0.42 Gender (Female=1) 0.447 0.779 0.57 Under 2,500 residents 0.074 1.224 0.95 2,501 to 10,000 residents 1.303 0.987 0.19 10,001 to 25,000 residents 0.495 0.954 0.60 25,001 to 50,000 residents 0.028 1.000 0.98 50,001 to 500,000 residents (baseline) Omitted 501,000 or more residents -1.012 0.979 0.30 Private practice owned by a single veterinarian -1.757 0.694 0.01*** Private practice/private corporation (baseline) Omitted Salary (baseline) Omitted Hourly or per diem -1.502 2.352 0.52 Production only -0.839 1.099 0.45 Salary with production-based incentive 0.044 1.038 0.97 Salary without production-based incentive -3.255 2.776 0.24 Owner with no differentiation 0.855 1.124 0.45 Owner with differentiation -1.123 1.262 0.37 Other compensation method 4.845 1.971 0.01*** Internship (Yes=1) 1.632 0.698 0.02** Residency (Yes=1) 0.144 1.384 0.92 Board Certified (Yes=1) 0.327 1.446 0.82 Practice Ownership (Yes=1) 1.467 0.959 0.13 General equine (baseline) Omitted
Working 0.271 2.505 0.91 English performance 0.606 0.897 0.50 Companion 1.849 1.444 0.20 Quarter Horse racing -4.742 2.973 0.11 Standardbred racing 0.835 2.863 0.77
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Thoroughbred racing 0.063 1.529 0.97 Reproductive -3.792 1.432 0.01*** Western performance -4.111 1.686 0.02** Ambulatory (baseline) Omitted
Ambulatory with haul-in facility -0.184 0.749 0.81 Haul-in only 2.614 2.754 0.34 Specialty/referral - limited service hospital 0.804 2.319 0.73 Specialty/referral - full service hospital 1.767 2.476 0.48 Specialty/referral - limited service hospital with ambulatory 2.073 2.029 0.31 Specialty/referral - full service hospital with ambulatory -0.846 0.991 0.39 Other business model 0.791 1.850 0.67 Not Married (Yes=1) 1.127 0.718 0.12 Constant 34.242 2.716 0.00***
Observations 364
Adjusted R-Square 0.2856
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) -2.739 0.154 0.00*** Education Preparation (5=Extremely well/1=Not well at all) -0.892 0.187 0.00*** Income 0.000 0.000 0.79 Currently owe debt (Yes=1) 0.323 0.394 0.41 Hours worked per week 0.073 0.010 0.00*** Graduation Year -0.068 0.022 0.00*** Gender (Female=1) 1.110 0.340 0.00*** Less than 2,500 residents -0.290 0.684 0.67 2,500 to 49,999 residents (baseline) Omitted 50,000 to 499,999 residents 0.235 0.327 0.47
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500,000 or more residents 0.129 0.408 0.75 Companion animal (baseline) Omitted Food Animal -1.896 0.918 0.04** Equine -0.810 0.707 0.25 Mixed Animal -1.146 0.592 0.05** Federal Government 3.134 1.772 0.08 College/University -2.143 1.300 0.10* State/Local Government 0.062 2.026 0.98 Industry/Commercial -0.623 1.659 0.71 Not-for-profit -0.416 1.506 0.78 Advanced education -1.070 1.146 0.35 Other Vet Employment -0.451 0.943 0.63 Non-Vet Employment -1.005 2.214 0.65 Salary (baseline) Omitted Hourly 0.207 0.542 0.70 Production only -0.710 0.527 0.18 Mix of salary with opportunity for production-based compensation 0.230 0.349 0.51 Owner withdrawals -0.360 0.561 0.52 Internship (Yes=1) -0.258 0.376 0.49 Residency (Yes=1) -0.567 1.014 0.58 Board Certified (Yes=1) 0.994 0.943 0.29 Practice Ownership (Yes=1) 1.147 0.485 0.02** Not Married (Yes=1) 0.022 0.317 0.95 Constant 37.544 1.154 0.00*** Observations 1,291 Adjusted R-Square 0.2979
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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4.8.2.3 Secondary Traumatic Stress
Secondary traumatic stress scores had a similar distribution to that of the burnout scores. The
mean secondary traumatic stress score of Equine respondents (21.2) was to the left of the low
end, however, and that of the AVMA respondents (23.1) was in the low end of the normal
range. The percent of respondents with a score above 35 (Equine: 1.6 percent; AVMA: 4.6) was
lower than for burnout. A score above 35 on the secondary traumatic stress scale may suggest
a need to seek help to deal with the factors that are causing secondary traumatic stress. The
average raw ProQOL score for secondary traumatic stress is between 23 and 41 (average
ProQOL score around 50) (Figure 133).
Figure 133: Distribution of Equine and AVMA Respondents’ Secondary Traumatic Stress Score
The mean compassion secondary traumatic stress score by graduation year decreased with
experience or years from graduation. Equine respondents who graduated between 2012 and
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
0 5 10 15 20 25 30 35 40 45 50
% o
f Res
pond
ents
Traumatic Stress Score
Distribution of Respondents' Secondary Traumatic Stress Score
Equine (n=826) AVMA (n=2,313)
Average across all professions
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2016 had a mean score of 22.8 while those who graduated prior to 1967 had a mean score of
18.0 (Table 119).
Table 119: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Graduation Year
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. < 1967 6 18.0 4.3 11 23 59 18.0 4.9 10 31 1967-1976 49 17.7 4.4 10 28 101 19.0 4.6 10 31 1977-1986 122 19.2 5.0 11 40 175 20.7 5.9 11 37 1987-1996 138 19.9 5.4 10 33 330 21.6 6.2 10 41 1997-2006 145 20.7 5.4 11 37 589 22.9 6.4 10 45 2007-2011 165 23.6 6.2 8 40 471 24.5 6.6 10 47 2012-2016 191 22.8 5.6 10 38 554 24.9 6.8 11 46
The mean secondary traumatic stress score was significantly different between males and
females for both Equine and AVMA samples (p < .001). For both samples the mean score was
lower for males than for females (Table 120).
Table 120: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Gender
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Male 332 19.5 5.3 10 38 726 21.2 6.3 10 46 Female 492 22.4 5.7 8 40 1,578 24.0 6.6 10 47
The mean secondary traumatic stress score was significantly different between Equine
respondents who participated in an internship and those who did not participate in an
internship (p < .001), but the difference is not significant in the AVMA sample. The mean
secondary traumatic stress score for internship participation is examined by graduation year, as
internship participation rates have increased in more recent years. In both samples the
secondary traumatic stress score for respondents who participated in an internship and
respondents who did not decreased, on average, the longer a respondent was out of veterinary
school (Table 121).
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Table 121: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Internship
Equine Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 148 22.46 5.62 10 36 6-10 years 116 24.14 6.25 12 40 11-20 years 91 20.71 5.29 11 33 21-30 years 60 20.55 5.25 11 33 31 or more years 47 18.53 5.52 10 40
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 42 23.83 5.43 16 38 6-10 years 43 22.98 5.54 13 35 11-20 years 51 20.43 5.42 12 37 21-30 years 75 19.31 5.57 10 33 31 or more years 125 18.85 4.62 10 31
AVMA Obs. Mean Std. Dev. Min. Max.
With Internship 0-5 years 148 24.90 6.36 13 45 6-10 years 165 24.93 6.95 11 47 11-20 years 159 22.97 6.31 13 45 21-30 years 71 20.03 5.77 10 33 31 or more years 49 19.14 5.08 10 31
No Internship Obs. Mean Std. Dev. Min. Max. 0-5 years 406 24.95 6.95 11 46 6-10 years 305 24.32 6.40 10 43 11-20 years 429 22.78 6.38 10 44 21-30 years 258 22.05 6.20 11 41 31 or more years 285 19.75 5.48 10 37
In terms of ownership status, the results indicated that practice owners had a lower mean
secondary traumatic stress score than associates for both samples. The mean score for Equine
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respondent owners was 20.3 vs. 23.0 for Equine respondent associates. The AVMA sample
yielded a mean score of 22.2 for owners and 24.3 for associates. These differences in both
samples were statistically significant at p < .001 (Table 122).
Table 122: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Practice Ownership
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Owner 331 20.3 5.5 10 40 401 22.2 6.3 10 43 Associate 258 23.0 5.9 8 40 1,061 24.3 6.7 10 47
Respondents’ scores relative to board certification showed statistical significance between
board-certified and non-board-certified respondents in the AVMA sample (p<.001) but not in
the Equine sample (Table 123).
Table 123: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Board Certification
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Board Certified
146 20.9 6.3 10 40 340 21.4 6.4 10 45
Non-Board Certified
680 21.3 5.7 8 40 1,970 23.4 6.6 10 47
The mean secondary traumatic stress score of respondents decreased with level of income. The
trend showed that scores were typically higher for lower income categories but then decreased
as income level climbed (Table 124).
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Table 124: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Professional Income
Income Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. $20,000 to $29,999
32 23.0 6.0 14 40 59 23.3 6.1 15 40
$30,000 to $39,999
31 20.7 4.6 13 33 88 24.4 7.0 12 43
$40,000 to $49,999
49 22.4 4.5 12 33 109 23.0 5.8 12 40
$50,000 to $59,999
46 23.0 7.0 8 38 128 23.9 6.3 12 44
$60,000 to $69,999
74 23.3 6.3 12 38 209 24.6 6.9 10 47
$70,000 to $79,999
87 23.3 6.2 12 38 245 24.3 6.5 11 42
$80,000 to $89,999
64 21.1 5.1 10 36 238 23.7 6.3 11 42
$90,000 to $99,999
39 20.3 5.6 12 35 164 23.5 6.8 11 46
$100,000 to $124,999
112 20.0 5.7 10 40 307 23.0 6.8 10 46
$125,000 to $149,999
50 21.3 6.2 11 40 152 23.1 6.4 11 41
$150,000 to $174,999
48 19.1 4.9 10 33 82 20.9 6.5 10 41
$175,000 to $199,999
22 19.6 4.7 11 29 48 21.8 6.8 11 45
$200,000 to $249,999
22 18.1 4.3 12 27 83 21.2 5.8 11 37
$250,000 to $500,000
44 18.1 4.8 11 30 77 22.2 6.5 11 38
> $500,000 7 17.7 3.7 13 24 19 20.9 5.6 12 31
Respondents who had current veterinary educational debt had a higher mean secondary
traumatic stress score than those respondents, both Equine and AVMA, who did not currently
have such debt. The difference between those who currently owed debt and those who did not
currently owe were statistically significant in both samples (p < .001) (Table 125).
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Table 125: Mean Equine and AVMA Respondents’ Secondary Traumatic Stress Score by Veterinary Educational Debt
Equine AVMA
Obs. Mean Std. Dev. Min. Max. Obs. Mean Std. Dev. Min. Max. Currently Owe
350 22.5 5.9 8 40 1,162 24.3 6.8 10 47
Do not currently owe
277 20.0 5.4 10 40 681 22.0 6.1 10 42
Within the primary equine sectors of AAEP respondents, the lowest mean secondary traumatic
stress score was reported by respondents in the Quarter Horse racing sector (17.0). The highest
mean score was reported by respondents in the ranch or working sector (22.7) and equine
companion sector (22.7) (Table 126).
Table 126: Mean AAEP Respondents’ Secondary Traumatic Stress Score by Primary Equine Sector
AAEP Obs. Mean Std. Dev. Min. Max.
English performance 82 21.5 5.5 12 35 Equine companion 25 22.7 5.6 13 38 Racing - Quarter Horse 5 17.0 3.9 13 23 Racing - Standardbred 7 22.1 5.8 12 28 Racing - Thoroughbred 29 21.0 8.3 10 40 Reproductive 30 20.5 5.1 10 33 Ranch or working 9 22.7 5.6 12 29 Western performance 17 19.9 5.2 12 30 General equine 321 21.3 5.7 8 40
Within the primary business model of AAEP respondents, the lowest mean score was reported
by respondents in some other type of business model respondents reported working at the
race track, integrative therapies, and some other combination of business models followed
closely by respondents in a full-service specialty/referral hospital (20.9). The highest mean
score was reported by respondents in a limited-service specialty/referral hospital (23.1) (Table
127).
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Table 127: Mean AAEP Respondents’ Secondary Traumatic Stress Score by Business Model
AAEP Obs. Mean Std. Dev. Min. Max.
Ambulatory 193 21.3 5.9 10 38 Ambulatory with Haul-in facility 187 21.2 5.4 8 38 Haul-in only facility 7 21.9 5.5 13 30 Specialty/referral hospital - Limited service (e.g., no colic surgery, isolation, neonatology)
12 23.1 7.2 14 40
Specialty/referral hospital - Full service 9 20.9 6.7 14 33 Specialty/referral hospital - Limited service with ambulatory division
15 21.1 6.3 12 30
Specialty/referral hospital - Full service with ambulatory division
84 21.4 5.9 12 40
Other 21 20.7 6.2 11 35
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Factors Affecting Secondary Traumatic Stress
Again, using the same approach to examine the factors associated with secondary traumatic
stress that was used with compassion satisfaction and burnout, several factors were found to
be statistically significant. Among AAEP respondents, owner compensation with no
differentiation between pay for effort as a veterinarian and pay as an owner, some other form
of compensation, were female, internship participation, and working in a limited-service
specialty/referral hospital correlated on average with greater secondary traumatic stress.
Respondents in the AVMA sample who worked more hours a week, were female, worked in
federal and state/local government, and mix of salary with oppurtunity for production-based
compensation, on average, greater secondary traumatic stress.
Factors identified with a lower secondary traumatic stress score among AAEP respondents were
satisfaction with current employment or working in the reproductive and Quarter Horse racing
sectors. Among AVMA respondents, satisfaction with current employment, respondents who
felt their education prepared them well for their career in veterinary medicine, and
respondents who had more veterinary experience (graduation year), on average, had lower
secondary traumatic stress scores (Table 128).
The factors that were included in this model produced an adjusted R-square of 0.1600 in the
AAEP sample and .1144 in the AVMA sample. This indicates that the inclusion of all these
factors were able to explain 16 percent and 11 percent of the variation between the
individually reported secondary traumatic stress score and the estimated mean secondary
traumatic stress. Thus, there are important variables that determine secondary traumatic stress
that have not been included, and are due to other unobservable factors.
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Table 128: Factors Affecting Secondary Traumatic Stress
AAEP Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) -1.171 0.350 0.00*** Education Preparation (5=Extremely well/1=Not well at all) 0.040 0.413 0.92 Income 0.000 0.000 0.19 Currently owe debt (Yes=1) 1.272 0.885 0.15 Hours worked per week 0.013 0.012 0.26 Graduation Year -0.015 0.043 0.73 Gender (Female=1) 1.413 0.763 0.07* Under 2,500 residents 0.075 1.189 0.95 2,501 to 10,000 residents 1.131 0.960 0.24 10,001 to 25,000 residents -0.019 0.930 0.98 25,001 to 50,000 residents 0.405 0.977 0.68 50,001 to 500,000 residents (baseline) Omitted 501,000 or more residents 0.081 0.952 0.93 Private practice owned by a single veterinarian -0.620 0.674 0.36 Private practice/private corporation (baseline) Omitted Salary (baseline) Omitted Hourly or per diem 2.319 2.248 0.30 Production only 1.012 1.070 0.35 Salary with production-based incentive 0.649 0.909 0.48 Salary without production-based incentive -4.123 2.984 0.17 Owner with no differentiation 2.107 1.113 0.06* Owner with differentiation -0.528 1.280 0.68 Other compensation method 5.780 1.891 0.00*** Internship (Yes=1) 1.119 0.683 0.10* Residency (Yes=1) -1.075 1.345 0.43 Board Certified (Yes=1) 0.034 1.403 0.98 Practice Ownership (Yes=1) 0.008 0.941 0.99 General equine (baseline) Omitted Working -2.416 2.433 0.32 English performance 0.463 0.889 0.60 Companion 0.257 1.365 0.85 Quarter Horse racing -5.119 2.918 0.08* Standardbred racing 2.351 2.778 0.40
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Thoroughbred racing 1.991 1.488 0.18 Reproductive -3.406 1.430 0.02** Western performance -1.955 1.637 0.23 Ambulatory (baseline) Omitted Ambulatory with haul-in facility 0.492 0.730 0.50 Haul-in only 2.123 2.674 0.43 Specialty/referral - limited service hospital 4.633 2.269 0.04** Specialty/referral - full service hospital 3.066 2.415 0.21 Specialty/referral - limited service hospital with ambulatory 1.379 1.969 0.48 Specialty/referral - full service hospital with ambulatory 0.203 0.969 0.83 Other business model -0.554 1.870 0.77 Not Married (Yes=1) 0.625 0.701 0.37 Constant 23.046 2.609 0.00*** Observations 361 Adjusted R-Square 0.1600
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
AVMA Coefficient Std. Error Sig.
Satisfied with current employment (5=Extremely satisfied/1=Not at all satisfied) -1.550 0.194 0.00*** Education Preparation (5=Extremely well/1=Not well at all) -0.878 0.235 0.00*** Income 0.000 0.000 0.59 Currently owe debt (Yes=1) -0.109 0.494 0.83 Hours worked per week 0.057 0.013 0.00*** Graduation Year -0.069 0.027 0.01*** Gender (Female=1) 1.331 0.426 0.00*** Less than 2,500 residents -0.151 0.863 0.86 2,500 to 49,999 residents (baseline) Omitted 50,000 to 499,999 residents -0.186 0.410 0.65 500,000 or more residents -0.008 0.510 0.99 Companion animal (baseline) Omitted Food Animal -1.719 1.165 0.14 Equine -1.019 0.885 0.25
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Mixed Animal -1.093 0.741 0.14 Federal Government 3.693 2.214 0.10* College/University -1.236 1.625 0.45 State/Local Government 4.229 2.532 0.10* Industry/Commercial 0.741 2.073 0.72 Not-for-profit -2.372 1.882 0.21 Advanced education 0.158 1.433 0.91 Other Vet Employment 0.169 1.162 0.88 Non-Vet Employment -2.563 2.766 0.35 Salary (baseline) Omitted Hourly -0.062 0.677 0.93 Production only -0.159 0.658 0.81 Mix of salary with opportunity for production-based compensation 0.777 0.438 0.08* Owner withdrawals 0.014 0.705 0.98 Internship (Yes=1) -0.177 0.472 0.71 Residency (Yes=1) -0.938 1.257 0.46 Board Certified (Yes=1) 0.674 1.181 0.57 Practice Ownership (Yes=1) 0.631 0.609 0.30 Not Married (Yes=1) -0.200 0.397 0.61 Constant 30.172 1.452 0.00***
Observations 1,284
Adjusted R-Square 0.1144
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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In addition to the ProQOL questions, respondents were asked similar questions that were
specifically tailored to the equine veterinarian regarding their quality of life. The results are
presented in the context of the gender of the respondents (Table 129). For each question, the
mean rank (1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = very often) is given along
with the standard deviation and significance between gender. The difference in means was
statistically significant in most cases, meaning that in this sample, female and male
veterinarians are affected differently by helping others.
Table 129: Mean AAEP Respondents’ Equine Quality of Life Questions by Gender
Male Female
N Mean Std. Dev N Mean Std. Dev Pr > |t|
I am often exhausted at the end of the day.
227 3.54 0.93 299 4.10 0.84 0.00***
I have difficulty staying organized with all that I need to do and remember.
228 2.97 0.95 299 3.52 1.06 0.00***
I feel l ike I am so busy that things fall through the cracks.
228 2.88 0.97 299 3.42 0.95 0.00***
I feel l ike I’m on a treadmill. 228 2.59 1.20 299 3.24 1.19 0.00***
I feel trapped by my job. 228 2.36 1.22 299 2.87 1.25 0.00***
I am exhilarated by my success in helping my patients and clients.
228 3.71 0.94 299 3.46 0.86 0.00***
I love learning new clinical skills and diagnostic techniques.
228 3.71 1.00 298 3.59 1.07 0.19
I feel fulfi l led when I can solve a patient’s difficult problem.
228 4.21 0.76 299 4.00 0.82 0.00***
Being on call for emergencies is stressful.
227 2.90 1.24 297 3.59 1.14 0.00***
Being on call for emergencies is affecting my most important relationships.
228 2.60 1.24 297 3.30 1.21 0.00***
I am happy when I can help a client and their horse through a frightening injury or i l lness.
227 4.04 0.80 296 3.93 0.79 0.10*
I am frequently tearful over minor things.
227 1.40 0.68 297 2.14 1.04 0.00***
I am frequently irritable with the practice staff.
228 2.37 0.94 297 2.62 1.03 0.01***
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I am frequently irritable with my family.
227 2.48 0.86 297 2.85 0.90 0.00***
I am proud of my contribution to the equine community.
228 3.79 0.92 297 3.48 0.86 0.00***
I look forward to going to work. 228 3.99 0.90 298 3.49 0.98 0.00***
When my phone rings I have a surge of adrenaline.
228 2.62 1.10 297 3.13 1.22 0.00***
I feel l ike I make a difference every day in my work.
228 3.62 0.90 298 3.30 0.86 0.00***
I love my job. 228 3.92 1.01 298 3.64 1.00 0.00***
My responsibilities frequently feel l ike too much pressure.
228 2.40 0.97 298 3.00 1.03 0.00***
I have been bull ied on social media as a result of my work as a veterinarian.
228 1.21 0.54 299 1.31 0.62 0.07*
Sometimes I am scared by my patients’ dangerous behavior.
228 1.90 0.75 298 2.29 0.77 0.00***
I worry about getting injured at work.
228 2.33 0.93 299 2.73 0.89 0.00***
I sometimes feel l ike my work has consumed my life.
228 2.89 1.18 299 3.50 1.15 0.00***
I wish I had time for doing something fun.
228 3.18 1.08 298 3.73 1.01 0.00***
I feel l ike I have no control over my life.
228 2.47 1.15 298 3.03 1.19 0.00***
I feel very satisfied by my work. 228 3.93 0.94 298 3.60 0.90 0.00***
I feel happy. 228 4.01 0.87 298 3.77 0.85 0.00***
I enjoy being around the people I work with.
227 4.12 0.75 298 3.82 0.83 0.00***
I feel supported by the people I work with.
227 4.13 0.86 298 3.72 0.96 0.00***
I spend time with good friends outside of my work l ife.
228 3.23 1.07 298 2.74 0.88 0.00***
I feel overwhelmed. 228 2.40 1.08 298 3.21 1.00 0.00***
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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4.9 GEOGRAPHIC DISTRIBUTION OF EQUINE PRACTITIONERS
The geographic location of Equine respondents, AAEP members, and AVMA respondents who
provided their ZIP code is depicted in the next three figures. Respondents were spread across
the United States, with the exception of Equine respondents, who lacked a presence in Hawaii
and Alaska. Approximately 20 percent of Equine respondents were in the East Coast/Northeast
area of the United States, and approximately 56 percent were east of the Mississippi River
(Figure 134).
Concentration of Equine Respondents in the United States, 2016
Figure 134: Concentration of Equine Respondents in the United States, 2016
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While the Equine respondents are a subset of the overall AAEP membership, the concentration
of AAEP members, while larger, displays a similar pattern to the Equine respondents.
Approximately 18 percent of AAEP members reside on the East Coast/Northeast area of the
United States and approximately 48 percent of members are east of the Mississippi River
(Figure 135).
Concentration of AAEP Members in the United States, 2016
Figure 135: Concentration of AAEP Members in the United States, 2016
Equine respondent geographic concentration was compared to the AVMA respondent
concentration. Approximately 17 percent of AVMA respondents are in the East Coast/Northeast
region of the United States; approximately 48 percent of AVMA respondents are to the east of
the Mississippi River (Figure 136).
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Concentration of AVMA Respondents in the United States, 2016
Figure 136: Concentration of AVMA Respondents in the United States, 2016
All three groups showed a heavy concentration of veterinarians in certain areas of Northern
and Southern California, the Northwest in the coastal area of Oregon and Washington,
central/north Colorado, Texas, the coastal line of Florida, the Great Lakes area leading down to
central Kentucky, and areas in northern Georgia, eastern South Carolina, and North Carolina.
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SECTION 5: MARKET FOR VETERINARY SERVICES
The market for veterinary services is the third vertically-related market (in addition to the
market for education and the market for veterinarians) that functions independently but is
linked to the market for veterinarians through price. Clients are charged a fee for a service
provided by a veterinarian. Veterinary services are a normal good. That is, as income increases,
an individual’s propensity to purchase such goods increases, and as income decreases, that
individual is less likely to purchase such goods. As the demand for veterinary services increases,
the price of veterinary services increases in parallel, other things being equal. Conversely, a
decline in the number of clients, animals per client, or services demanded per animal will
typically reduce the aggregate demand for veterinary services and result in downward pressure
on the price for veterinary services.
While equine owners may demand veterinary services, they might not seek them from a
licensed veterinarian but instead may try to treat their animal themselves, or seek care from a
lay provider or other professional in the equine industry. In response to market forces, few
veterinarians seek to reduce costs through the utilization of veterinary technicians to perform
specific veterinary services. To add to the complexity of this market, not all veterinary services
are the same. Not only are there numerous types of services, but even the same service (e.g.,
castration, dental examination/treatment, physical examination) may differ among practices in
quality and/or price. No information was queried in this survey to determine if consumers are
able to differentiate quality differences in services provided.
In the 2012 AAEP Owner Trainer Survey, 86 percent of respondents said they used their primary
veterinarian for routine care/examinations. While half reported they used their primary
veterinarian for dental care (51 percent), another 26 percent reported that they used the
services of a non-veterinarian. 72 percent reported using their primary veterinarian for
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vaccinations in the past year, but 22 percent said they have used a non-veterinarian for that
service. Half reported that they administered all (23 percent) or some (27 percent) of their
horses’ vaccinations themselves. Among those, 79 percent said they did so in order to save
money. Veterinarians remain a leading supplier of medications for owners/trainers, but they
are not the only source. Nearly all of the respondents in this study reported they purchased
medications from their veterinarian in the past year (93 percent). However, half also said they
purchased medications on the internet (52 percent) and/or from a supply, tack, or western
store (51 percent). While 61 percent said they always go through their veterinarian to get
medications, nearly the same percentage said they seek ways to save money on medications
(53 percent). 35 percent reported that their veterinarian charges a higher price for medications
than other sources charge.
This section provides an overview of the supply of equines in the United States. Data used in
this section are from the U.S. Department of Agriculture Census of Agriculture, the USDA
Equine Health Report of 2015 and estimates made from the AVMA Pet Demographic Surveys.
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5.1 SUPPLY OF EQUIDS IN THE UNITED STATES
The most recent Census of Agriculture (2012) reported 292,590 mules, burros and donkeys
(Figure 137), and 3,621,348 farm horses and ponies (Figure 138) in the United States. Numbers
from the USDA Census of Agriculture refer only to equids that were considered property, and
from which farm proprietors generated at least $1,000 of income, so this database covers only
horses living on certain types of commercial farms.
Figure 137: Total Number of Farm Mules, Burros and Donkeys in the United States 49
49 Source: USDA Census of Agriculture, 1969-2012
66,128
292,590
34,309
98,379
- 50,000
100,000 150,000 200,000 250,000 300,000 350,000
1969 1974 1978 1982 1987 1992 1997 2002 2007 2012
# of
Mul
es, B
urro
s and
Don
keys
Year
Total Number of Farm Mules, Burros and Donkeys in the United States
Mules, burros and donkeys Number of farms
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Figure 138: Total Number of Farm Horses and Ponies in the United States 50
The number of pet horses was obtained from the 1981-2016 AVMA Pet Demographic Surveys
(PDS). “The primary focus of the survey was to collect data about the numbers of pets owned as
of December 31, 2016 by household type to estimate pet populations. Because the data were,
as usual, collected from a sample of households, the results are not a census of pet populations.
Estimates based on a sample are always subject to sampling error” (AVMA, 2017). According to
horse pet population estimates from the most recent of these surveys, the 2016 PDS dataset
estimated 1.9 million U.S. pet horses at the end of December 31, 2016 (Figure 139). There was a
new survey data collection and analysis approach for 2016, which implies that the previous PDS
numbers are no longer directly comparable. “The AVMA is aware of the widely divergent
estimated rates of pet ownership and pet populations in the United States. There are three
main reasons: one, non-representative respondents (‘convenience sampling’), two, no
correction to achieve representativeness (no ‘weighting’), and three, including invalid and
erroneous responses (no ‘screening’)” (AVMA, 2017).
50 Source: USDA Census of Agriculture, 1969-2012
1,595,024 3,621,348
347,797 504,795
-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
1969 1974 1978 1982 1987 1992 1997 2002 2007 2012
# of
Hor
ses
and
Poni
es
Year
Total Number of Farm Horses and Ponies in the United States
Horses and ponies Number of farms
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Figure 139: Total Number of Pet Equids in the United States, 1981-201651
In 2005, the American Horse Council estimated the horse population at 9.2 million, after which
the country experienced an economic recession and the number of horses in the United States
decreased. In 2014, a separate study (the Brakke Equine Mega Study) reported an estimated
U.S. horse population of 6 million. In 2017, the American Horse Council estimated the horse
population at 7.2 million.
5.1.1 Number of Equine-Pet-Owning Households
The 2016 Pet Demographic dataset estimated the number of equine pet-owning households at
the end of 2016 was less than one million (893,152) (Figure 140). These equine pet owners,
who may also be called “backyard” horse owners, are affected by changes in the economy, with
services purchased by horse owners fluctuating in relation to disposable household income. In
51 Source: AVMA Pet Demographic Surveys, 1981-2016
7,000,000
4,000,000
7,300,000
1,914,000 -
1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 8,000,000
1981 1987 1992 1997 2002 2007 2012 2016
# of
Equ
ids
Year
Total Number of Pet Equids in the U.S., 1981-2016
Pet Demographic Survey - pet equids
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other words, the more income these owners have, the more they may be willing to spend on
veterinary services and vice versa.
Figure 140: Percentage and Number of Households That Owned a Horse, Dec. 31, 1991-201652
The USDA Equine Health Report of 2015 reported that throughout the entire country, horses
(excluding miniatures) made up the highest percentage of resident equids present on May 1,
2015 (85.5 percent). Miniature horses and donkeys made up an approximately equal
percentage of resident equids overall (4.6 percent and 4.5 percent, respectively), followed by
ponies and mules (3.4 percent and 2.0 percent, respectively).
5.1.2 Location
As reported in the 2016 Pet Demographic Survey (PDS), 0.7 percent of households in the United
States owned horses at the end of 2016. The percentage of horse-owning households varies by
region. In the PDS, the West South Central area comprising Texas, Oklahoma, Arkansas and
52 Source: AVMA Pet Demographic Surveys, 1991-2016
2.0% 1.5% 1.7% 1.8% 1.5% 0.7% -
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
0%
10%
20%
30%
Num
ber o
f Hou
seho
lds
(in M
illio
ns)
% o
f Hou
seho
lds
Year
Percentage and Number of Households That Owned a Horse (Dec. 31, 1991-2016)
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Louisiana had the largest percentage of households that owned horses, at 1.3 percent. The
Mountain region of Montana, Idaho, Wyoming, Nevada, Utah, Colorado, Arizona, and New
Mexico followed at 1.1 percent, and the East South Central region of Kentucky, Tennessee,
Mississippi and Alabama was next at 0.9 percent. The region with the lowest percentage of
horse-owning households was the Middle Atlantic, comprising New York, Pennsylvania, New
Jersey, Delaware, Maryland, and Washington, D.C. at 0.3 percent, and the New England region,
comprising Maine, Vermont, New Hampshire, Connecticut, Rhode Island, and Massachusetts at
0.3 percent. 53
5.1.3 Veterinary Visits
The 2016 Pet Demographic Survey revealed that 47 percent of non-commercial or “backyard”-
type horse owners viewed their horses as family members, 42 percent as a pet/companion, and
11 percent as property. In addition, 65 percent of the individuals who were identified as the
primary caretaker for a horse were females. These findings may influence demand for
veterinary services.
44 percent of horse-owning households surveyed for the PDS reported that their horse(s) did
not receive any care from a veterinarian in 2016. Of the 56 percent who did receive veterinary
care for their horses, 14 percent reported one visit, 23 percent had two visits, 5 percent had
three visits, and 14 percent had four or more visits.
The USDA Equine Health Report of 2015 was released in December 2016. This study was
conducted in 28 states selected, in part, because they had large or dense equine populations.
As with past studies conducted by USDA’s National Animal Health Monitoring System, the USDA
53 The regions in the 2016 Pet Demographic Survey are different than the 0-9 regions reflected in the Equine report.
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Equine Health Report of 2015 provided valuable information to study participants,
stakeholders, and the equine industry. Data collected represented 71.6 percent of equids in
the U.S. and 70.9 percent of U.S. operations with five or more equids.
The USDA’s National Agricultural Statistics Service has periodically captured data on U.S.
commercial equine operations from their regular Census of Agriculture; the list frame used to
select participants for the USDA Equine Health Report of 2015 study was derived from the 2012
Census of Agriculture. All farms on the 2012 Census list with five or more equids (including
horses, ponies, mules, and donkeys) were eligible to be included. Horses residing at racetracks
were not eligible. In total, 3,997 operations were selected for participation via a stratified
random sample.
Operators/owners of commercial horse operations obtain information on the health care of
their animals from multiple sources. Respondents in the USDA Equine Health Report of 2015
were asked to report all sources of equine health care information used in the previous 12
months. Although equine operations used multiple information sources when making decisions
related to equine health care, the highest percentage (79.8 percent) used a private veterinarian
as a source of information, followed by a farrier (65.2 percent).
Beyond receiving health care information, 78.8 percent of the surveyed commercial operations
in the USDA Equine Health Report of 2015 study had used veterinary services at least once in
the previous 12 months. At least 40 percent of operations had used a veterinarian to provide
one or more of the following services: diagnosis, treatment, or surgery of an individual horse,
vaccination consultation or administration, purchase of drugs or vaccines not administered by a
veterinarian, dentistry (e.g., floating, filing, or removing teeth), or herd diagnostic services.
Over one-fourth of all operations (26.9 percent) used a veterinarian to provide an official health
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certificate, and 6.2 percent of all operations used a veterinarian to perform a biosecurity
assessment.
5.2 DEMAND FOR EQUINE PRIVATE PRACTICE VETERINARY SERVICES
Services provided by equine veterinarians include health maintenance/wellness care,
emergency care, surgery, internal medicine, ophthalmology, radiology, ultrasonography,
imaging modalities such as MRI and CT, laboratory testing, dentistry, sports medicine,
prescription and dispensing of medication, complementary or integrative care (e.g.
acupuncture, chiropractic, massage therapy), and rehabilitation therapy. Additional services
may be provided by veterinary specialists with advanced training in cardiology, dentistry,
dermatology, neurology, oncology, ophthalmology, theriogenology, imaging and internal
medicine.
In the 2016 Pet Demographic Survey, the listing of veterinary services queried to private horse
owners were phrased in layman’s terms. Equine veterinary service options listed in the survey
included part-time or full-time boarding/hospitalization, prescription of vitamins/supplements,
preventative care, treatment for lameness or injury (broken bones, lacerations), dental care or
treatment of mouth problems, treatment to address abdominal pain/colic, eye problems, skin
disorders or worms, treatment of cancer, tumor, or other mass or growth, treatment of heart,
lung, liver or kidney disease, and vaccinations.
When horse owners select a veterinary service provider, their awareness of the business may
have originated through word of mouth, an internet listing or website, print advertisement,
prominent signage (visible from the street), or a Yellow Pages phone book listing. Alternatively,
horse owners may choose a provider because of a recommendation or referral, or a reputation
for high quality care, or the presence of a board-certified specialist at the practice. Other
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considerations include the ability of the practice to provide care quickly or at convenient hours
and the fee structure of the practice.
The AAEP 2012 Owner Trainer Survey revealed that one of the top three reasons that clients
choose a veterinarian is the ability to provide on-the-farm ambulatory emergency care 24 hours
a day, 7 days a week.54 Less than 10 percent of the respondents chose low fees as a top reason
to choose a veterinarian. More than half of the owners reported they had been using their
primary veterinarian for at least six years (55 percent) ; the average was nine years. Owners
reported seeing their veterinarian in person about as often as they talked to them on the
phone, on average about eight times per year. A key component of satisfaction was veterinary
availability. In some ways, offering constant availability appeared to be an “entry requirement”
in that respondents reported that a veterinarian would not be considered as a service provider
if he/she was not readily available. However, owner satisfaction clearly extended beyond
simple availability in that owners reported they wanted to feel that their veterinarian was there
for them, cared about their horses, and was willing to spend time with them. In addition, being
skilled at explaining diagnoses and treatments was also important to owner respondents.
In summary, a number of factors drive the market for equine veterinary services.
54 AAEP “Horse Owner/Trainer Veterinary Services Survey 2012 Report of Findings” was accessed 5/9/14; the PDF can be found by AAEP members who log into http:// touch.aaep.org and do a keyword search for "Owner Trainer Veterinary Services survey."
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SECTION 6: EQUINE PRACTICE
Dataset Observations (n)
AAEP Membership database 7,432
AAEP - secondary sample 975
AVMA - comparative sample 2,545
Equine - main sample (81 Equine respondents from AVMA + 975 AAEP)
1,056
Equine veterinary practices have much in common with other types of veterinary practices in
the delivery of veterinary medical services. Equine practices, however, have several
characteristics that distinguish them from other types of practices, such as varying foci on
individual equine subsectors within the equine industry. Regardless of the subsector served,
each of these practices has the same goal: keeping horses healthy and owners happy.
Respondents that service equines were used in this section of analysis. This section also focuses
on some of the unique characteristics of practice in the following subsectors – or equine sectors
– examined in this analysis:
• Gaited breeds
• Hunter/jumper, eventing, dressage (referred to as English performance in the graphs
and tables)
• Equine companion/pet/pleasure/recreation (referred to as Equine companion in the
graphs and tables)
• Racing - Quarter Horse (referred to as Racing - QH in the graphs and tables)
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• Racing - Standardbred (referred to as Racing - STB in the graphs and tables)
• Racing - Thoroughbred (referred to as Racing - TB in the graphs and tables)
• Reproductive
• Ranch or working
• Western performance barrels, roping, rodeo, cutting, reigning etc. (referred to as
Western performance in the graphs and tables)
• General equine practice – serving multiple sectors (referred to as General equine in the
graphs and tables)
6.1 EQUINE SECTORS
More than 60 percent of AAEP respondents at the time of the survey worked in general equine
practice, serving multiple sectors. These individuals typically work with many different types of
horses in different equine sectors throughout the day. Of the remaining respondents, 15.6
percent worked in English performance, 5.7 percent worked in Thoroughbred racing, 5.7
percent worked in the reproductive sector, 4.7 percent worked primarily with equine
companions, and the remainder (each under 4 percent) in gaited breeds, Quarter Horse and
Standardbred racing, ranch or working, and Western performance (Figure 141).
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Figure 141: Distribution of AAEP Equine Practitioner Respondents and the Type of Equine Sector They Primarily Serve
The many respondents who reported they were involved in general equine practice (across
multiple equine sectors) were spread throughout the country. The respondents active in the
Hunter/jumper, dressage and eventing horse (English performance) sectors were primarily
located along the East Coast and in other pockets of the United States. Working horse
respondents were located primarily in the Midwest and Texas, as were the bulk of the Western
performance horse respondents. Respondents in the Thoroughbred racing discipline were
mostly located in Kentucky, California, Texas, Florida, New York, Pennsylvania and Maryland.
Standardbred racing respondents were found east of the Mississippi River, and toward New
England. Several companion equine respondents were located south of the Great Lakes, and a
number of reproductive specialty respondents reported that they worked in Kentucky, the
Midwest and Texas (Figure 142).
Gaited breeds, 0.2% English performance, 15.6%
Companion, 4.7%
Racing - QH, 1.0%Racing - STB, 1.3%
Racing - TB, 5.7%
Reproductive, 5.7%Ranch or working, 1.7%
Western performance, 3.2%
General equine, 60.9%
Distribution of AAEP Equine Practitioner Respondents and the Type of Equine Sector They Primarily Serve (n=527)
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Concentration of Equine Respondents by Primary Equine Industry Sector, 2016
Figure 142: Concentration of Equine Respondents by Primary Equine Industry Sector, 2016
AAEP respondents were also asked to identify the secondary equine sector they serve, and
were invited to select all that applied to them from a list. Responses showed that 29.2 percent
practiced in general equine (serving multiple sectors), 25.7 percent in equine companion
(including pet, pleasure and recreational use), and 21.1 percent in English performance
(hunter/jumper, eventing, dressage). There was low representation from endurance and polo
sectors, English performance with Arabians, Morgans, and Tennessee Walking Horses, as well
as Standardbred and Quarter Horse racing sectors (Table 130).
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Table 130: Distribution of AAEP Respondent Equine Practitioners and the Secondary Equine Sector They Served
Secondary Equine Sector (n=541) Obs. Yes No
General equine 158 29.2% 70.8% Equine companion 139 25.7% 74.3% English performance - hunter/jumper, eventing, dressage 114 21.1% 78.9% Western performance - barrels, roping, rodeo, cutting, reigning etc. 54 10.0% 90.0% Western show performance - pleasure, trail, reining 31 5.7% 94.3% Racing - TB 30 5.5% 94.5% English performance - Arabians, Morgans, Tennessee Walking Horses 9 1.7% 98.3% Racing - QH 9 1.7% 98.3% Racing - STB 8 1.5% 98.5% Polo 6 1.1% 98.9% Endurance 1 0.2% 99.8%
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Unique Horse Patients Serviced
AAEP respondents reported the total number of unique horse patients that they serviced in
2015. If they saw one horse multiple times, that horse counted as one patient.
Within the equine sectors, respondents in the Thoroughbred racing industry reported having
the highest average total number of unique equine patients that they provided service to
(1,548 unique patients). Those who worked in the ranch or working sector reported the
smallest average number of unique patients at 177 (Table 131).
Table 131: Distribution of AAEP Respondent Equine Practitioners’ Average Number of Unique Horse Patients Serviced in 2015 with Respect to Primary Equine Sector55
Obs. Total Mean Std. Dev. Median Min. Max.
General equine 247 257,123 1,041 1,477 600 2 15,000 English performance 60 52,437 874 1,007 500 15 5,000 Racing - TB 23 35,605 1,548 2,080 1,000 5 10,000 Reproductive 28 21,770 778 826 500 2 3,000 Western performance
14 15,803 1,129 1,289 800 12 5,000
Equine companion 16 10,683 668 632 425 20 2,500 Racing - QH 4 3,100 775 838 500 100 2,000 Racing - STB 6 2,650 442 326 375 100 1,000 Ranch or working 7 1,238 177 104 200 20 343
The total number of unique horse patients that respondents reported that were specifically
mares was more than 150,000. The respondents who worked in the Western sector on average
saw the greatest number of mares (549 unique mare patients), while respondents in the
working or ranch industry saw, on average, the least amount of unique mares (63) (Table 132).
55 Gaited breeds was omitted because the number of observations did not permit estimation.
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Table 132: Distribution of AAEP Respondent Equine Practitioners’ Average Number of Unique Horse Patients Serviced in 2015 That Were Specifically Mares with Respect to Primary Equine Sector56
Obs. Total Mean Std. Dev. Median Min. Max.
General equine 237 98,258 415 560 250 0 5,000 English performance 53 17,984 339 423 200 2 2,000 Reproductive 27 11,322 419 487 250 2 2,150 Racing - TB 22 8,535 388 505 150 0 1,500 Western performance 15 8,235 549 676 400 0 2,500 Equine companion 14 4,600 329 273 195 5 800 Racing - STB 6 1,245 208 173 163 60 500 Racing - QH 4 1,150 288 320 175 50 750 Ranch or working 7 439 63 41 75 10 104
In the next section, this report observes the respondents in different equine sectors and who
they primarily contacted, how they communicated, and what party was invoiced for services
rendered.
56 Gaited breeds was omitted because the number of observations did not permit estimation.
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Primary Contact
Equine veterinarians communicate with multiple individuals about the diagnosis and treatment
of an individual patient, and do so in a variety of ways. The ranking of AAEP respondents’
primary contact regarding care for their patient is displayed in Figure 143. Position 1 is the most
frequently used primary contact, and the least frequently used primary contact is in position 6.
The order of frequency reported indicated that 69.7 percent of veterinarians most frequently
contacted the owners of the patient; other contacts were the least frequent primary contact,
with trainers, farm employees, corporation/partnership representatives and referring DVMs
falling somewhere in between.
Figure 143: Distribution of AAEP Respondent’s Frequent Primary Contact for Horse Patient
97.5%
56.0%
46.5%
55.0%52.4%
69.7%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Primary Contact
Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient (n=523)
Most (1)
2
3
4
5
Least (6)
Rank
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Respondents practicing in the equine companion sector reported that owners were used the
most as the primary contact (92 percent) when providing care for a patient. Those respondents
in general equine practice (84.9 percent) and ranch or working sectors (77.8 percent) also
communicated primarily with owners. Respondents in the racing industries interfaced with
owners about a patient the least of all sectors: Trainers and farm managers were contacted
primarily the majority of the time by respondents in racing sectors serving Thoroughbreds (80
percent), Standardbreds (71.4 percent), and Quarter Horses (100 percent). While respondents
reported that barn and farm employees were not contacted as often, they were still utilized as
a primary care point-of-contact by some sectors, being used most in reproductive (20 percent)
and ranch or working sectors (22.2 percent). Respondents reported rarely using referring DVMs
as a primary contact, and no respondent reported contacting corporate or partnership
representatives as the primary contact. Respondents in general equine practice, the
Thoroughbred racing industry, reproductive, and English performance sectors, however, ranked
corporations/partnership representatives second as a primary contact. The majority of all
respondents ranked other contacts as least likely to be primary contact (Figure 144).
0% 20% 40% 60% 80% 100%
English performance (n=82)Equine companion (n=25)
Racing-QH (n=5)Racing-STB (n=7)Racing-TB (n=30)
Reproductive (n=30)Ranch or working (n=9)
Western performance (n=17)General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
r
Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient by Primary Equine Sector - Owners/Family Members
Most (1)
2
3
4
5
Least (6)
Rank
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0% 20% 40% 60% 80% 100%
English performance (n=82)Equine companion (n=25)
Racing-QH (n=5)Racing-STB (n=7)Racing-TB (n=30)
Reproductive (n=30)Ranch or working (n=9)
Western performance (n=17)General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
rDistribution of AAEP Respondents' Frequent Primary Contact for
Horse Patient by Primary Equine Sector - Trainers/Farm Managers
Most (1)
2
3
4
5
Least (6)
Rank
0% 20% 40% 60% 80% 100%
English performance (n=82)Equine companion (n=25)
Racing-QH (n=5)Racing-STB (n=7)Racing-TB (n=30)
Reproductive (n=30)Ranch or working (n=9)
Western performance (n=17)General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
r
Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient by Primary Equine Sector - Barn/Farm Employees
Most (1)
2
3
4
5
Least (6)
Rank
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0% 20% 40% 60% 80% 100%
English performance (n=82)Equine companion (n=25)
Racing-QH (n=5)Racing-STB (n=7)Racing-TB (n=30)
Reproductive (n=30)Ranch or working (n=9)
Western performance (n=17)General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
rDistribution of AAEP Respondents' Frequent Primary Contact for
Horse Patient by Primary Equine Sector - Referring DVMs
Most (1)
2
3
4
5
Least (6)
Rank
0% 20% 40% 60% 80% 100%
English performance (n=82)
Racing-QH (n=5)
Racing-TB (n=30)
Ranch or working (n=9)
General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
r
Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient by Primary Equine Sector - Corporation/Partnership
representatives
Most (1)
2
3
4
5
Least (6)
Rank
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Figure 144: Distribution of AAEP Respondents' Frequent Primary Contact for Horse Patient by Primary Equine Sector57
Communication
Effective communication is critical in developing a good relationship with clients and providing
the best care for patients. Some individuals in the client relationship-building process are
communicated with more frequently than others. In this survey, 70.3 percent of AAEP
respondents routinely communicated to owners and family members more than half the time,
followed by 29.3 percent who communicated routinely with trainers and farm managers more
than half the time. The majority of respondents reported that they communicated with barn
and farm employees, referring DVMs, corporation or partnership representatives, and other
contacts (farriers, insurance companies) about clinical findings and care recommendations less
than 25 percent of the time (Table 133).
57 Gaited breeds was omitted because the number of observations did not permit estimation.
0% 20% 40% 60% 80% 100%
English performance (n=82)Equine companion (n=25)
Racing-QH (n=5)Racing-STB (n=7)Racing-TB (n=30)
Reproductive (n=30)Ranch or working (n=9)
Western performance (n=17)General equine (n=317)
% of Respondents
Prim
ary
Equi
ne S
ecto
rDistribution of AAEP Respondents' Frequent Primary Contact for
Horse Patient by Primary Equine Sector - Other
Most (1)
2
3
4
5
Least (6)
Rank
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Table 133: Which of the following people do you routinely communicate with about clinical findings in providing care for your patients?
Percentage Trainers/ farm
managers (n=504)
Owners/ family
members (n=512)
Barn/farm employees
(n=421)
Corporation/ Partnership rep.
(n=250)
Referring DVM
(n=339)
Other (n=66)
0% 0.0% 0.0% 2.1% 49.2% 14.2% 87.9% 1-10% 23.4% 5.8% 56.1% 48.4% 57.2% 4.6% 11-25% 22.6% 7.8% 23.5% 2.0% 11.8% 4.6% 26-50% 24.6% 16.0% 13.8% 0.0% 4.7% 0.0% 51%-75% 10.7% 23.6% 2.4% 0.0% 0.9% 1.5% 76%-99% 8.7% 36.9% 1.7% 0.0% 1.2% 1.5% 100% 9.9% 9.8% 0.4% 0.4% 10.0% 0.0%
The majority of respondents in the different equine sectors reported that they communicate
mostly with owners and trainers. Respondents in the Quarter Horse racing industry
communicated with trainers on average 97 percent of the time, and owners 10.6 percent of the
time. In the Thoroughbred racing industry, veterinarians communicate with referring DVMs an
average of 29.3 percent of the time, with owners 22.9 percent of the time and with trainers 75
percent of the time. Respondents in the English performance sector indicated that they
communicated with owners 58.2 percent of the time and trainers 57.7 percent of the time.
Respondents in the Standardbred racing sector communicated with barn employees 49 percent
of the time. Respondents in general equine practice reported communication with owners 75.1
percent of the time, and with those in companion practice 84.9 percent of the time(Table 134).
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Table 134: Mean Percentage of AAEP Respondents Who Communicate with Type of Client by Primary Equine Sector58
Average Percent Owners
Trainers
Employees Corporate Referring DVM
Other
English performance (n=82)
58.2% 57.7% 23.1% 8.1% 24.8% 10.0%
Equine companion (n=25)
84.9% 17.1% 9.2% 0.4% 10.9% 0.0%
Racing-QH (n=5) 10.6% 97.0% 4.0% 0.0% 0.0% 0.0% Racing-STB (n=7) 41.7% 72.3% 49.0% 6.7% 6.7% 0.0% Racing-TB (n=30) 22.9% 75.0% 24.5% 5.6% 29.3% 10.0% Reproductive (n=30) 42.3% 46.4% 18.8% 2.5% 22.5% 1.3% Ranch or working (n=9) 86.1% 24.4% 18.8% 1.3% 30.3% 0.0% Western performance (n=17)
62.9% 46.4% 10.3% 8.5% 29.9% 0.0%
General equine practice (n=319)
75.1% 33.9% 16.6% 4.0% 16.7% 3.0%
Invoicing
Respondents in every equine sector reported that they invoiced owners and family members
more than 70 percent of the time. In examining the racing industry sectors, survey data
indicated that trainers and farm managers were invoiced 16.4 percent of the time in the
Standardbred industry and 10.7 percent of the time in the Thoroughbred industry, with
corporations invoiced 15.0 percent of the time in the Thoroughbred industry (Table 135).
58 Gaited breeds was omitted because the number of observations did not permit estimation.
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Table 135: Percent of Clients Invoiced by AAEP Respondents for Patient Care 59
Trainers/farm managers
Owners/family members
Barn/farm employees
Corporation/ Partnership rep.
Other
English performance (n=82)
4.6% 89.5% 1.9% 2.6% 1.5%
Equine companion (n=25)
2.6% 95.8% 1.1% 0.6% 0.4%
Racing-QH (n=5) 0.0% 100.0% 0.0% 0.0% 0.0% Racing-STB (n=7) 16.4% 78.6% 2.1% 2.9% 0.0% Racing-TB (n=30) 10.7% 73.8% 6.8% 15.0% 0.0% Reproductive (n=30) 7.5% 76.3% 9.3% 6.8% 0.3% Ranch or working (n=9)
2.8% 93.9% 2.8% 0.6% 0.0%
Western performance (n=17)
7.6% 84.7% 2.7% 5.3% 0.0%
General equine practice (n=319)
3.7% 91.2% 1.3% 2.3% 4.6%
Communication Type
Over time, the equine veterinary industry has adopted new technologies and channels through
which to communicate. As with other industries, methods have evolved from face-to-face
communication, landline phones and fax machines to text messages, email and social media.
AAEP respondents were asked to consider the ways in which they communicate with their
clients, and rank from 1 to 8 the most frequent form of communication used, with 1 indicating
the greatest frequency. While slightly more than half of the respondents ranked in-person
communication first, cell phone communication was a close second (46.9 percent).
Communication through Facebook was ranked the least frequently used, with 39.2 percent of
respondents ranking this method as last (Figure 145).
59 Gaited breeds was omitted because the number of observations did not permit estimation.
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Figure 145: Distribution of AAEP Respondents’ Ranking of Communication Method with Clients
39.2%
34.9%31.2%
31.2%
23.8%44.0%
35.8%
46.9%
50.1%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Type of Client Communication
Distribution of AAEP Respondents' Ranking of Communication Method with Clients (n=525)
Most (1)
2
3
4
5
6
7
Least (8)
Rank
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6.2 STAFF UTILIZATION
Veterinary practices have full-time and part-time employees. AAEP respondents were asked
how many positions were found at their place of employment in 2015, as well as asked to note
the numbers that were full time.
Full-Time Equivalent Veterinarians and Staff Support
A full-time equivalent (FTE) employee in this analysis was defined with the assumption that a
full-time employee was working between 30-40 hours a week and a part-time employee was
working 20-29 hours a week. Given this assumption, a full-time employee was assigned a 1, and
a part-time employee was assigned a 0.5. By adding up the total number of employees, the FTE
was calculated for a practice. For instance, a one-veterinarian practice equaled a 0.5 to 1.5 FTE
veterinarian; a two-veterinarian practice equaled 1.6-2.5 FTE veterinarians; a three-veterinarian
practice equaled 2.6 to 3.5 FTE veterinarians; a four-or-more-veterinarian practice equaled 3.6-
4.5, and so forth.
In the AAEP sample, 38.5 percent of respondents reported a one-veterinarian practice, 14.3
percent a two-veterinarian practice, 12.6 percent a three-veterinarian practice, 7.8 percent a
four-veterinarians practice, 6.1 percent a five-veterinarian practice, and 20.6 percent a six-or-
more-veterinarian practice (Figure 146).
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Figure 146: Distribution of Full-Time Equivalent (FTE) Veterinarians at a Practice
The number of FTE veterinarians in a practice was then divided by the number of employees to
calculate the veterinarian to employee ratio. Employees (support staff) were defined as
receptionists, veterinary assistants, veterinary technicians (credentialed and non-credentialed),
and animal caretakers. On average, there were 1.7 FTE support staff for every FTE veterinarian
employed at the AAEP respondents’ place of practice in 2015.
About 25 percent of respondents reported two to four and five to nine positions in their place
of employment in 2015, and 16 percent reported no support staff positions at their place of
employment (Figure 147).
38.5%
14.3%12.6%
7.8%
6.1%
20.6%
Distribution of Full-Time Equivalent (FTE) Veterinarians at a Practice (n=548)
One
Two
Three
Four
Five
Six or more
FTE Vets
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Figure 147: Distribution of Number of FTE Employees in a Practice
A total of 72 solo practitioners reported no additional veterinarians working at their practice
and no support staff positions. Of the respondents reporting additional owner, associate and
staff positions in their place of employment in 2015, the mean number of FTE associates per
FTE owner veterinarian was 1.89, about two associates for every veterinarian in a practice
(Table 136). Among other positions reported by respondents, there was approximately one
part-time position for each veterinarian in a practice. In the AAEP sample, there were 0.37
interns per veterinarian, 0.14 residents (participating in a residency) per veterinarian, 0.57
credentialed veterinary technicians and 0.80 non-credentialed veterinary technicians per
veterinarian, and 0.80 veterinary assistants. Additionally there were 0.67
receptionist/information clerks, and 0.89 barn/hospital animal caretakers per veterinarian
(Table 137).
16.0%
16.6%
23.5%
22.9%
15.7%
5.3%
Distribution of Number of FTE Employees in a Practice (n=524)
0 employees
1 employee
2-4 employees
5-9 employees
10-19 employees
20 + employees
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Table 136: Mean FTE Associates per Owner Veterinarians at a Practice
Position (per FTE owner veterinarian)
Obs. Mean Ratio Std. Dev. Median Ratio Min. Max.
Associates 337 1.89 1.77 1.33 0.07 12.00
Table 137: Mean FTE Staff Support per FTE Veterinarians (Owners plus Associates)
Position (per FTE veterinarian)
Obs. Mean Ratio Std. Dev. Median Ratio Min. Max.
Intern veterinarians 114 0.37 0.20 0.33 0.10 1.00 Resident veterinarians 14 0.14 0.16 0.11 0.02 0.63 Credentialed veterinary technicians
200 0.57 0.51 0.44 0.08 4.00
Non-credentialed veterinary technicians
238 0.80 0.57 0.67 0.07 3.00
Veterinary assistants 267 0.80 1.08 0.57 0.06 15.00 Receptionists/information clerks
377 0.67 0.43 0.56 0.10 4.00
Barn/hospital animal caretakers
211 0.89 3.49 0.40 0.06 50.00
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Staff Utilization on Ambulatory Calls and After Business Hours
More than one-third (35.2 percent) of AAEP respondents reported that veterinary technicians
and other support staff were used on ambulatory calls routinely, in contrast to 20.4 percent of
respondents who reported that they were not used on ambulatory calls (Figure 148).
Figure 148: Distribution of the Utilization of Veterinary Technicians and Other Support Staff on Ambulatory Calls
Nearly half of the respondents indicated that support staff were not used after business hours,
compared to almost one-quarter of respondents who said support staff were used after
normal business hours on ambulatory calls, but only if needed (Figure 149).
2.5%
20.4%28.0%
35.2%
13.9%
No ambulatorywork is done in
my place ofemployment
Support staffare not used on
ambulatorycalls
Support staffare used onambulatory
calls, but only ifneeded
Support staffare routinely
used onambulatory
calls
Support staffare always
used onambulatory
calls
% o
f Res
pond
ents
Ambulatory Use Type
Distribution of the Utilization of Veterinary Technicians and Other Support Staff on Ambulatory Calls (n=525)
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Figure 149: Distribution of the Utilization of Veterinary Technicians and Other Support Staff after Business Hours
With regard to the number of FTE veterinarians in a practice, the trend among AAEP
respondents appears to be that the larger the veterinary practice in terms of the number of
veterinarians, the more commonly it was reported that support staff were routinely or always
used on ambulatory calls (Figure 150).
7.1%
48.7%
16.6%24.6%
3.1%
No after normalbusiness hourswork is done in
my place ofemployment
Support staff arenot used after
normal businesshours
Support staff areused after normalbusiness hours in
the hospital orclinic
Support staff areused after normalbusiness hours onambulatory calls,
but only if needed
Support staff arealways used afternormal business
hours onambulatory calls
% o
f Res
pond
ents
After Business Hours Use Type
Distribution of the Utilization of Veterinary Technicians and Other Support Staff after Business Hours (n=541)
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Figure 150: Distribution of the Utilization of Veterinary Technicians and Other Support Staff on Ambulatory Calls by Number of FTE Veterinarians at a Practice
3.9% 4.9% 1.5%
36.9%
19.5%
8.8% 8.3% 8.6%2.4%
24.6%
26.8%
39.7%33.3% 31.4%
23.8%
22.2%36.6% 41.2%
39.6% 42.9%
54.8%
12.3% 12.2% 8.8%18.8% 17.1% 19.0%
One Two Three Four Five Six +
% o
f Res
pond
ents
# of FTE Veterinarians
Distribution of the Utilization of Veterinary Technicians and Other Support Staff on Ambulatory Calls by Number of FTE Veterinarians at a
Practice (n=520)
Support staff are always used onambulatory calls
Support staff are routinely usedon ambulatory calls
Support staff are used onambulatory calls, but only ifneeded
Support staff are not used onambulatory calls
No ambulatory work is done inmy place of employment
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The use of veterinary technicians or other support staff at an AAEP respondents’ place of
employment after normal business hours was also investigated. More than half of respondents
who have one to three veterinarians at their place of employment do not use staff in the
hospital or clinic after normal business hours. Of respondents who work in a veterinary practice
of six or more veterinarians, 41.7 percent reported that support staff is used after normal
business hours in the hospital or clinic (Figure 151).
Figure 151: Distribution of the Utilization of Veterinary Technicians and Other Support Staff after Business Hours by Number of FTE Veterinarians at a Practice
Among AAEP respondent practices, there were 15.3 percent (77) of respondents that reported
their practice did not use either a licensed technician or a non-licensed technician/assistant.
38.1 percent (191) reported using both licensed technicians and non-licensed
12.3%4.9% 3.0% 2.1%
8.6%2.4%
59.1%
54.9% 53.7%
39.6% 31.4%
25.0%
5.4%
11.0% 11.9%29.2%
25.7%41.7%
19.7% 29.3% 31.3% 25.0%28.6% 26.2%
3.4% 4.2% 5.7% 4.8%
One Two Three Four Five Six +
% o
f Res
pond
ents
# of FTE Veterinarians
Distribution of the Utilization of Veterinary Technicians and Other Support Staff after Business Hours by Number of FTE Veterinarians at a
Practice (n=519)
Support staff are always usedafter normal business hours onambulatory calls
Support staff are used afternormal business hours onambulatory calls, but only ifneeded
Support staff are used afternormal business hours in thehospital or clinic
Support staff are not used afternormal business hours
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technicians/assistants, 40.4 percent (203) reported the use of non-licensed veterinary
technicians/assistants only, and 6.2 percent (31) reported the use of licensed veterinary
technicians only.
The distribution of duties assigned to each type of technician/assistant is reported in Table 138.
Of the respondents who reported on the distribution of duties assigned to licensed technicians
and/or non-licensed technicians/assistants at their place of work, respondents reported a
higher use of non-licensed veterinary technicians than licensed technicians/veterinary
assistants during the set up of diagnostic imaging equipment (NLT: 91.9 percent; LT: 86.0
percent). The largest difference between the use of the two types of technicians was in the
placing of IV catheters into a patient: 82.9 percent of the 222 respondents with licensed
technicians indicated they were given this responsibility, 38.6 percent of the 394 respondents
with non-licensed technicians/assistantswere given this task. 75.7 percent of those with
licensed technicians utilized them for administering anesthesia, compared to 35.8 percent of
those respondents with non-licensed/assistant staff.
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Table 138: Distribution of Duties Assigned to Licensed Technicians and Non-Licensed Technicians at an AAEP Respondents’ Place of Work (select all that apply)
Licensed Technician
(n=222)
Non-licensed Technicians/Veterinary
Assistants (n=394) Obs. Percent Obs. Percent Administer anesthesia 168 75.7% 141 35.8% Setting up diagnostic imaging equipment (radiography, ultrasonography, endoscopy)
191 86.0% 362 91.9%
Obtaining radiographic studies 163 73.4% 211 53.6% Perform other diagnostic imaging studies (e.g. nuclear scintigraphy, MRI)
54 24.3% 45 11.4%
Administer vaccinations 141 63.5% 163 41.4% Place IV catheters 184 82.9% 152 38.6% Administer treatments or set up fluids through catheter
189 85.1% 258 65.5%
Administer IV injections (no catheter) 172 77.5% 171 43.4% Administer IM injections (other than vaccinations)
190 86.5% 256 65.0%
Perform routine treatments - e.g., apply foot wrap, apply leg wrap, apply topical medications
186 83.8% 284 72.1%
Collect venous blood samples 198 89.2% 260 66.0% Perform laboratory tests in house - e.g., set up bacterial cultures, use CBC/chemistry analysis machines, perform quantitative fecal exams, cytology
196 88.3% 280 71.1%
Perform aseptic preparation for procedures 201 90.5% 333 84.5% Prepare injections for doctor use 191 86.0% 305 77.4% Communicate with clients - e.g. Give care instructions, report laboratory results, make appointments
174 78.4% 260 66.0%
Write invoices for work performed by veterinarian
170 73.9% 264 67.0%
Assist in surgical procedures 162 76.6% 245 62.2%
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6.3 SERVICE CALLS
Among AAEP respondents, 36.5 percent reported being in a strictly ambulatory practice.
Ambulatory with a haul-in facility comprised another 35.4 percent of the distribution; 16.1
percent of respondents reported working in a full-service specialty/referral hospital with an
ambulatory division. Respondents who primarily worked in a haul-in facility comprised only 1.3
percent of the group, and 1.7 percent of the respondents reported that they worked in a full-
service specialty/referral hospital with no ambulatory division (Figure 152).
By primary equine sector, there were respondents reporting being in an ambulatory practice in
all sectors except for the ranch or working sector. Over 50 percent of respondents in the equine
companion and Standardbred racing sectors reported being in an ambulatory practice. Over 60
percent of respondents in the ranch or working sectors reported being in an ambulatory with
haul-in facility. 27.6 percent of respondents in the Thoroughbred racing sector, and 23.5
percent respondents in Western performance, reported working in a full-service
specialty/referral hospital with ambulatory division in 2015 (Table 139).
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Figure 152: Distribution of AAEP Respondents’ Primary Practice Business Model In 2015
Table 139: Distribution of AAEP Respondents’ Primary Practice Business Model In 2015 by Primary Equine Sector
Obs. Ambulatory Ambulatory with Haul-in
facility
Haul-in facility only
Specialty/referral - Limited service
English performance 82 40.2% 20.7% 0.0% 2.4% Companion 25 60.0% 36.0% 0.0% 0.0% Racing - QH 5 20.0% 0.0% 0.0% 0.0% Racing - STB 7 71.4% 28.6% 0.0% 0.0% Racing - TB 29 34.5% 10.3% 0.0% 0.0% Reproductive 30 20.0% 30.0% 10.0% 13.3% Ranch or working 9 0.0% 66.7% 0.0% 11.1% Western performance
17 17.6% 35.3% 11.8% 5.9%
General equine 322 37.3% 41.0% 0.6% 1.2%
36.5%
35.4%
1.3%2.3%1.7%2.8%
16.1%
4.0%
Distribution of AAEP Respondents' Primary Practice Business Model In 2015 (n=529)
Ambulatory
Ambulatory with Haul-in facility
Haul-in facility only
Specialty/referral - Limitedservice
Specialty/referral - Full service
Specialty/referral - Limitedservice with ambulatory division
Specialty/referral hospital - Fullservice with ambulatory division
Other
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Obs. Specialty/referral
- Full service Specialty/referral - Limited service with ambulatory
division
Specialty/referral hospital - Full service with ambulatory
division
Other
English performance 82 1.2% 2.4% 28.0% 4.9% Companion 25 0.0% 0.0% 4.0% 0.0% Racing - QH 5 0.0% 0.0% 0.0% 80.0% Racing - STB 7 0.0% 0.0% 0.0% 0.0% Racing - TB 29 0.0% 6.9% 27.6% 20.7% Reproductive 30 0.0% 3.3% 13.3% 10.0% Ranch or working 9 0.0% 11.1% 11.1% 0.0% Western performance 17 5.9% 0.0% 23.5% 0.0% General equine 322 2.2% 2.8% 13.7% 1.2%
More than 90 percent of AAEP respondents said they charged a farm call or trip fee (8.1 percent
do not), and nearly the same amount (89.4 percent) reported that they charged an emergency
fee in addition for emergency calls, while 5.7 percent do not. A modest number of respondents
(4.9 percent) said they did not offer emergency services.
Respondents reported that billing for ambulatory call fees varies among the equine sectors.
Charging ambulatory visits based on zone was reported as the most common method for
ambulatory billing among AAEP respondents in the English performance (76.5 percent), equine
companion (62.5 percent), and general equine practice (68.3 percent) sectors. Within the AAEP
sample, a small percentage charged hourly one-way or round-trip fees for ambulatory calls,
with the exception of respondents in the Standardbred racing sector in which 42.9 percent
charged hourly round-trip fees. Nearly one-third (31.3 percent) of Western performance
respondents and 44.4 percent of ranch/working sector respondents reported that they charged
based on mileage driven (Table 140).
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Table 140: Distribution of AAEP Respondents’ Billing of Ambulatory Farm Calls by Primary Equine Sector60
Obs. By Zone
Hourly One-Way
Hourly Round-
Trip
Mileage Flat Fee
Other61 Total
English performance
81 76.5% 3.7% 2.5% 13.6% 2.5% 1.2% 100.0%
Equine companion
24 62.5% 0.0% 0.0% 29.2% 8.3% 0.0% 100.0%
Racing - QH 5 60.0% 0.0% 0.0% 20.0% 0.0% 20.0% 100.0% Racing - STB 7 42.9% 0.0% 42.9% 14.3% 0.0% 0.0% 100.0% Racing - TB 28 42.9% 3.6% 0.0% 7.1% 14.3% 32.1% 100.0% Reproductive 29 34.5% 3.4% 0.0% 24.1% 0.0% 37.9% 100.0% Ranch or working
9 44.4% 0.0% 11.1% 44.4% 0.0% 0.0% 100.0%
Western performance
16 56.3% 6.3% 0.0% 31.3% 6.3% 0.0% 100.0%
General equine 319 68.3% 2.2% 0.9% 14.4% 11.6% 2.5% 100.0%
At least 50 percent of AAEP respondents in a specialty referral hospital, ambulatory practice or
ambulatory practice with a haul-in facility reported they charged farm calls by zone. Half of the
respondents who worked in a haul-in facility did not charge by zone, but instead charged by
mileage. A small percentage of respondents across business models charged for hourly round-
trip and flat fees, while 14.7 percent of respondents in ambulatory charge a flat fee unrelated
to the distance of the patient from the practice (Table 141).
60 Gaited breeds was omitted because the number of observations did not permit estimation. 61 Other ways of bil l ing ambulatory farm calls were based on procedure/services conducted, location, and number of horses seen. Several respondents stated they do not charge for ambulatory farm calls.
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Table 141: Distribution of AAEP Respondents’ Billing of Ambulatory Farm Calls by Business Model
Obs. By Zone
Hourly One-Way
Hourly Round-
Trip
Mileage Flat Fee
Other62 Total
Ambulatory 191 62.3% 2.1% 2.1% 12.6% 14.7% 6.3% 100.0% Ambulatory with Haul-in facility
186 66.7% 3.2% 1.6% 19.9% 5.9% 2.7% 100.0%
Haul-in facility only 6 0.0% 16.7% 0.0% 50.0% 0.0% 33.3% 100.0% Specialty/referral-Limited service
12 50.0% 0.0% 0.0% 41.7% 0.0% 8.3% 100.0%
Specialty/referral-Full service
9 77.8% 0.0% 0.0% 22.2% 0.0% 0.0% 100.0%
Specialty/referral -Limited service with ambulatory division
15 80.0% 0.0% 6.7% 13.3% 0.0% 0.0% 100.0%
Specialty/referral hospital - Full service with ambulatory division
84 73.8% 2.4% 0.0% 10.7% 7.1% 6.0% 100.0%
Other 18 33.3% 0.0% 5.6% 22.2% 5.6% 33.3% 100.0%
AAEP respondents indicated that their primary practice service area covered anywhere from a
zero-mile radius to a 2,500-mile radius, with 32.8 percent of respondents reporting a service
area between a 21- and 40-mile radius, and 38.6 percent between a 41- and 60-mile radius. The
majority of AAEP respondents reported a service area radius of between 0 and 60 miles, with
the remainder of respondents (22.6 percent) covering more than 61 miles (Figure 153).
62 Other ways of bil l ing ambulatory farm calls was based on procedure/services conducted, location, and number of horses seen. Several respondents stated they do not charge for ambulatory farm calls.
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Figure 153: Distribution of AAEP Respondents’ Primary Practice Service Area Radius (in miles)
The average service area radius of respondents practicing in the Thoroughbred racing sector
encompassed 179 miles, the largest among the equine sectors represented, followed by
respondents in the ranch and working horse industry, with an average radius of 137 miles. The
smallest mean service area radius was reported by equine companion respondents, at 45 miles
(Table 142).
Table 142: Mean of AAEP Respondents’ Primary Practice Service Area Radius (in miles) by Primary Equine Sector63
Obs. Mean Std. Dev. Min. Max.
Racing - TB 27 179 504 1 2,500 Ranch or working 9 137 92 40 300 Racing - STB 7 84 57 30 200 English performance 79 75 75 5 400 Reproductive 29 74 182 0 1,000 Racing - QH 5 72 80 10 200 General equine 317 60 58 15 700 Western performance 17 60 44 10 200 Equine companion 25 45 13 25 90
63 Gaited breeds was omitted because the number of observations did not permit estimation.
6.0%
32.8%38.6%
7.3% 6.6% 8.7%
0-20 21-40 41-60 61-80 81-100 Over 100
% o
f Res
pond
ents
Primary Practice Service Area Radius (in miles)
Distribution of AAEP Respondents' Primary Practice Service Area Radius (in Miles) (n=518)
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Respondents with different business models had widely varying practice radii. At 52 miles,
respondents in a full-service specialty/referral hospital on average had the smallest radius
among the AAEP sample. Respondents who responded that their business model was in the
“Other” category reported the largest service area radius at 177 miles. The majority of
respondents in this “Other” category identified themselves as racetrack veterinarians or
professionals working in integrative therapy (Table 143).
Table 143: Mean of AAEP Respondents’ Primary Practice Service Area Radius (in miles) by Business Model
Obs. Mean Std. Dev. Min. Max.
Ambulatory 193 76 188 1 2,500 Ambulatory with Haul-in facility 184 58 45 10 400 Haul-in facility only 7 66 65 0 180 Specialty/referral hospital - Limited service (e.g., no colic surgery, isolation, neonatology)
10 87 101 5 300
Specialty/referral hospital - Full service 9 52 25 15 100 Specialty/referral hospital - Limited service with ambulatory division
15 99 109 30 400
Specialty/referral hospital - Full service with ambulatory division
82 56 45 20 300
Other 19 177 306 1 1,000
47 percent of AAEP respondents reported that they drove between 25,001 and 50,000 miles a
year while practicing veterinary medicine as an equine practitioner, followed by 29 percent who
traveled between 12,501 and 25,000 miles a year (Figure 154).
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Figure 154: Distribution of AAEP Respondents Miles Traveled for Work Each Year While Practicing Equine Medicine
More than 75 percent of AAEP respondents in any equine sector traveled fewer than 50,000
miles a year, but almost 75 percent of respondents in the Standardbred racing sector reported
traveling 25,001-50,000 miles. Almost one-quarter of respondents in the Thoroughbred racing
sector travelled more than 50,000 miles while performing their work (Table 144).
Table 144: Distribution of AAEP Respondents’ Miles Traveled for Work Each Year While Practicing Equine Medicine by Primary Equine Sector64
Obs. 0-12,500
12,501-25,000
25,001-50,000
50,001-75,000
75,001- 100,000
Over 100,000
English performance 82 6.1% 25.6% 57.3% 9.8% 1.2% 0.0% Equine companion 25 16.0% 32.0% 44.0% 4.0% 4.0% 0.0% Racing - QH 5 60.0% 0.0% 20.0% 20.0% 0.0% 0.0% Racing - STB 7 14.3% 14.3% 71.4% 0.0% 0.0% 0.0% Racing - TB 29 20.7% 17.2% 37.9% 13.8% 10.3% 0.0% Reproductive 29 17.2% 31.0% 34.5% 13.8% 3.4% 0.0% Ranch or working 9 44.4% 44.4% 0.0% 11.1% 0.0% 0.0% Western performance 17 35.3% 23.5% 17.6% 23.5% 0.0% 0.0% General equine 318 10.4% 31.4% 48.7% 6.6% 2.2% 0.6%
64 Gaited breeds was omitted because the number of observations did not permit estimation.
12.8%
29.0%
47.0%
8.4%2.5% 0.4%
0-12,500 12,501-25,000 25,001-50,000 50,001-75,000 75,001-100,000 Over 100,001miles
% o
f Res
pond
ents
# of Miles
Distribution of AAEP Respondents' Miles Traveled for Work Each Year While Practicing Equine Medicine (n=524)
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Respondents’ miles travelled per year by business model show that 63.6 percent of
respondents in a limited-service specialty/referral hospital and 71.4 percent in a haul-in only
facility travel up to 12,500 miles a year. More than 30 percent of AAEP respondents in the
“Other” business model travel in excess of 50,000 miles per year. These respondents included
those that are racetrack veterinarians or offer integrative therapies (Table 145).
Table 145: Distribution of AAEP Respondents’ Miles Traveled for Work Each Year While Practicing Equine Medicine by Business Model
Obs. 0-12,500
12,501-25,000
25,001-50,000
50,001-75,000
75,001- 100,000
Over 100,000
Ambulatory 192 6.8% 28.6% 56.3% 6.8% 1.6% 0.0% Ambulatory with Haul-in facility
187 10.2% 30.5% 50.3% 5.9% 2.1% 1.1%
Haul-in facility only 7 71.4% 28.6% 0.0% 0.0% 0.0% 0.0% Specialty/referral hospital -Limited service (e.g., no colic surgery, isolation, neonatology)
11 63.6% 18.2% 0.0% 9.1% 9.1% 0.0%
Specialty/referral hospital-Full service
9 11.1% 44.4% 33.3% 11.1% 0.0% 0.0%
Specialty/referral hospital -Limited service with ambulatory division
14 7.1% 42.9% 35.7% 7.1% 7.1% 0.0%
Specialty/referral hospital- Full service with ambulatory division
84 16.7% 28.6% 36.9% 14.3% 3.6% 0.0%
Other 20 35.0% 10.0% 25.0% 25.0% 5.0% 0.0%
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6.4 PARALLEL SERVICE PROVIDERS
There are many non-veterinarian providers of equine services, such as dentistry, podiatry,
sports medicine, integrative therapies, reproduction, and pharmaceutical services that were
once deemed solely the market of veterinarians. These non-veterinarian providers of equine
services can be referred to as parallel service providers. Because of the potential effects of
parallel veterinary service providers -- not only on the revenues of practices and incomes of
veterinarians but on the very existence of equine practices in some rural areas -- equine
veterinarians were asked to identify the potential competitors who have adversely affected
their practices. More than 84.7 percent of the AAEP respondents have had parallel service
providers take business away from them. Respondents indicated that nearly one-quarter of
equine practices provided seasonal services in other locations (e.g., states), and 86.4 percent of
this group has had parallel providers move in on their business. 13.6 percent of those who
provide seasonal services had not seen decreased revenue as a result.
AAEP respondents were asked to report the services provided by others to which they
attributed the reductions in their revenue stream, indicating all that applied to them. The top
services that AAEP respondents believed affected their revenue stream were dentistry at 62.5
percent, and internet pharmacy sales at 54.7 percent. Almost half (47.1 percent) of
respondents listed lay practitioners performing chiropractic, acupuncture and massage services.
31.2 percent of respondents felt they lost revenue from transient show veterinarians who
followed a particular sector’s show circuit, and 16.6 percent cited traveling pharmacies with a
physical presence at horse shows. More than 10 percent indicated that revenue was lost due to
services provided by university staff at university hospitals or at satellite locations. Only 15.3
percent of AAEP respondents reported that their revenue stream was not reduced by any of
these factors (Figure 155).
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Figure 155: Do you think your practice’s revenue stream has been reduced by services provided by any of the following types of parallel service providers? (select all that apply)
Pockets of respondents reported having been affected by university hospitals in the Denver,
Colorado area, Northern Virginia/Maryland area, and state of Massachusetts. Respondents felt
the effect of traveling pharmacies – most in Southern California and in states east of the
Mississippi River, especially along the East Coast northward into New England. Many
respondents across the country were affected by traveling show veterinarians, internet
pharmacies, and lay practitioners (Figure 156).
64.7%47.1%
62.5%
31.2%
16.6%
11.1%
15.3%
Internet pharmacies (n=350)
Lay practitioners (n=255)
Dentistry (n=338)
Show veterinarians (n=169)
Traveling pharmacies (n=60)
University staff at university hospitals (n=60)
No affect on revenue stream (n=83)
% of Respondents
Type
of P
aral
lel S
ervi
ce P
rovi
der
Do you think your practice’s revenue stream has been reduced by services provided by any of the following types of parallel service
providers? (select all that apply)
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I do not think my revenue stream has been reduced in any of these ways
University staff at university hospitals or at satellite locations
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Traveling pharmacies with physical presence at horse shows
Show veterinarians that travel with a particular sector’s show circuit
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Lay Practitioners – Dentistry
Lay Practitioners – Chiropractic/Acupuncture/Massage
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Internet Pharmacies
Figure 156: Maps of Parallel Veterinary Service Providers Affecting AAEP Respondents’ Revenue
AAEP respondents face competition not only from parallel service providers but from other
veterinarians within their service area as well: 26.5 percent of AAEP respondents stated that
there were one to five other equine veterinarians in their service area, followed by 24.6 percent
with six to 10 veterinarians, 23.6 percent with 11 to 20 veterinarians and 11.6 percent with 21
to 30 veterinarians (Figure 158).
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Figure 157: Distribution of the Number of Equine Veterinarians Competing in AAEP Respondents’ Service Area
The geographic distribution of competing equine veterinarians in an AAEP respondent’s service
area is presented in Figure 158. Across the continental United States and in parts of Hawaii, the
majority of respondents reported between 1-20 equine veterinarians in their service area.
Areas with more than 50 competing veterinarians were apparent in California, Minnesota,
Kentucky, Texas, Tennessee, Florida, and areas around Maryland (Figure 158).
26.5%24.6% 23.6%
11.6%
5.5%3.4% 4.8%
1-5 6-10 11-20 21-30 31-50 51-100 More than100
% o
f Res
pond
ents
# of Veterinarians
Distribution of the Number of Equine Veterinarians Competing in AAEP Respondents' Service Area (n=525)
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Distribution of Competing Equine Veterinarians in an AAEP Respondent’s Service Area
Figure 158: Distribution of Competing Equine Veterinarians in an AAEP Respondent’s Service Area
Nearly 90 percent of AAEP respondents in the ranch or working sector reported one to five
veterinarians as competitors; the remaining 11.1 percent of respondents reported 11-20
competing veterinarians in their service area. In the English performance sector, 34.6 percent of
respondents reported 11-30 veterinarians in their region. Respondents in the reproductive and
Thoroughbred racing industry had the highest percentage of competition, reporting more than
100 other equine veterinarians in their service area (23.3 percent and 13.3 percent
respectively). Overall, respondents in Standardbred and Quarter Horse racing, and in the ranch
and working sectors had fewer than 30 competing veterinarians in their service area. The
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remaining sectors reported more than 30 competing veterinarians in their service area (Table
146).
Table 146: Distribution of the Number of Competing Veterinarians in a Service Area by Primary Equine Sector65
1-5 6-10 11-20 21-30 31-50 51-100 >100 Total
English performance (n=81)
6.2% 19.8% 34.6% 16.0% 8.6% 8.6% 6.2% 100.0%
Equine companion (n=25)
52.0% 20.0% 20.0% 4.0% 4.0% 0.0% 0.0% 100.0%
Racing-QH (n=4) 50.0% 25.0% 0.0% 25.0% 0.0% 0.0% 0.0% 100.0% Racing-STB (n=7) 28.6% 42.9% 28.6% 0.0% 0.0% 0.0% 0.0% 100.0% Racing-TB (n=30) 10.0% 20.0% 16.7% 10.0% 10.0% 20.0% 13.3% 100.0% Reproductive (n=30) 23.3% 16.7% 20.0% 10.0% 0.0% 6.7% 23.3% 100.0% Ranch or working (n= 9) 88.9% 0.0% 11.1% 0.0% 0.0% 0.0% 0.0% 100.0% Western performance (n=17)
35.3% 29.4% 17.6% 11.8% 5.9% 0.0% 0.0% 100.0%
General equine (n=319) 28.8% 27.3% 23.2% 11.9% 5.0% 0.9% 2.8% 100.0%
65 Gaited breeds was omitted because the number of observations did not permit estimation.
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6.5 PRACTICE OWNERSHIP
Equine practitioners who are practice owners have a much different set of responsibilities than
associates. Not only does a practice owner practice veterinary medicine in most cases, he or
she is also in charge of the business operations associated with running a practice and the end
goal of managing a profitable and successful business. Practice owners, numbering 334,
accounted for 34.3 percent of the AAEP respondents, with 60 percent of owners male and 40
percent female. Of the respondents who were practice owners, 49.7 percent were sole
proprietors, 36.5 percent were a partner/shareholder in an S-Corp or C-Corp, and 13.8 percent
were a partner in a Limited Liability Corporation (LLC) or other type of practice ownership
structure (Figure 159).
Figure 159: Distribution of AAEP Respondent Owners by Practice Ownership Structure
As shown in in Figure 107, nearly one-quarter (23 percent) of practice owner respondents
reported a desire to decrease the number of hours they currently work each week; 16.3
49.7%
36.5%
13.8%
Distribution of AAEP Respondent Owners by Practice Ownership Structure
Sole proprietor (n=166)
Partner/Shareholder S-Corp or C-Corp (n=122)
Partner-LLC or other(n=46)
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percent desired to work more hours; and 60.7 percent reported they would like to work the
same hours amount of hours they currently worked.
An equine veterinarian in an ownership position needs to sell his or her shares in the practice
and transfer ownership of the business either before or at retirement. In other cases, a practice
owner may need to liquidate the business before retirement for a particular reason. Of the 225
AAEP respondents who shared their thoughts on selling equity, four percent indicated that they
would like to sell some or all of their shares before retirement, 28.4 percent would like to sell at
the time of retirement, and 67.6 percent indicated selling some or all of the shares before and
at the time of retirement.
Interest in ownership among associates was also explored. In the AAEP sample, more than half
(50.4 percent) of relief and associate veterinarian respondents were interested in purchasing a
practice. This is more than twice the interest reported by the AVMA sample (21.7 percent).
Only the AAEP respondents was given the choice to answer “Unsure,” and 20.8 percent of these
respondents selected this answer.
Approximately 59 percent of male AAEP respondents indicated interest in buying shares or
becoming a practice owner, while 48.0 percent of female AAEP respondents reported interest
in ownership; 18.7 percent of female and 12.7 percent of male AAEP respondents were unsure
if they would buy shares or obtain ownership. Among the AAEP sample 28.6 percent of male
respondents and 33.3 percent of female respondents were not interested in buying shares or
ownership of a practice (Figure 160). The 2016 Census of Veterinarians asked if respondents
were ”in the market” to buy a practice or become a practice owner instead of whether they are
“interested” (as in the 2016 AVMA-AAEP Survey of Equine Practitoners). Of the AVMA male
respondents, 34 percent were in the market to buy or become a practice owner and 18.7
percent of females were in the market to buy or become a practice owner.
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Figure 160: Distribution of AAEP and AVMA Respondents’ Interest in Buying Shares or Becoming a Practice Owner by Gender
Of the AAEP respondents interested in obtaining ownership in a practice, 34.5 percent were not
at all confident that they would obtain ownership interest in a practice within the next 18
months; 21.6 percent were extremely confident they would. More than 64 percent of AAEP
58.7% 48.0%
28.6%33.3%
12.7% 18.7%
Male (n=63) Female (n=198)
% o
f Res
pond
ents
Share/Ownership Interest Level
Distribution of AAEP Respondents' Interest in Buying Shares or Becoming a Practice Owner by Gender
Interested Not Interested Unsure
34.0%18.7%
66.0%81.3%
Male (n=256) Female (n=972)
% o
f Res
pond
ents
Share/Ownership in the Market Level
Distribution of AVMA Respondents' Interest in Buying Shares or Becoming a Practice Owner by Gender
In the market Not in the market
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respondents were “not very confident” to “not at all confident” to “unsure” about obtaining
practice ownership, while the remaining 36 percent of respondents were “moderately
confident,” “very confident” or “extremely confident” that they would obtain ownership (Figure
161).
Figure 161: Distribution of AAEP Respondents' Confidence Level in Obtaining Practice Ownership Interest in a Practice within the Next 18 Months
While approximately 35 percent of respondents were moderately to extremely confident in
obtaining ownership interest within the next year and a half, nearly one-quarter (23.8) percent
of practice owners were only moderately confident that they would successfully sell their
ownership interest; approximately 20 percent were very to extremely confident that they
would. More than half (56 percent) of AAEP respondent owners stated they were not very
confident, not at all confident, or not sure about being able to successfully sell their ownership
interest (Figure 162).
21.6%
3.5%
10.3%
25.0%
34.5%
5.2%
Distribution of AAEP Respondents' Confidence Level in Obtaining Practice Ownership Interest in a Practice
within the Next 18 Months (n=116)
Extremely confident
Very confident
Moderately confident
Not very confident
Not at all confident
Not sure
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Figure 162: Distribution of AAEP Respondent Owners’ Confidence Level Who Want to Sell Their Ownership Interest
An assessment of the confidence level of owners in selling interest in their practice with respect
to their practice size (including all staff and veterinarians) showed that the more staff members
there were in a practice the more confident owners were in selling their ownership interest
(Figure 163).
9.6%
10.6%
23.8%
21.5%
19.9%
14.6%
Extremely confident
Very confident
Moderately confident
Not very confident
Not at all confident
Not sure
% of Respondents
Conf
iden
ce L
evel
Distribution of AAEP Respondent Owners' Confidence Level Who Want to Sell Their Ownership Interest
(n=302)
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Figure 163: Distribution of AAEP Respondent Owners Who Want to Sell Their Practice Interest: Confidence in Ability to Sell Shares by Practice Size
The average confidence level of AAEP owner respondents in their ability to sell their
shares/practice with respect to the gross revenue generated per year over the past three years
was greater the more revenue a practice generated. When the practice gross revenue was less
than $1 million, less than 50 percent of respondents were extremely to moderately confident
that they would be able to sell their interest (Figure 164).
0%
20%
40%
60%
80%
100%
1 2-4 5-9 10-19 20-49 50+
% o
f Res
pond
ents
Practice Size (# of Staff Members)
Distribution of AAEP Respondent Owners Who Want to Sell Their Practice Interest: Confidence in Ability to Sell
Shares by Practice Size (n=300)
Extremely confident
Very confident
Moderately confident
Not very confident
Not at all confident
Not sure
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Figure 164: Distribution of AAEP Respondent Owners Who Want to Sell Their Practice: Confidence in Ability to Sell by Gross Collected Practice Revenue (per Year in the Last Three Years)
In addition to the majority of AAEP respondents who expressed moderate to low confidence
that they would be able to sell their ownership interest, only 18.4 percent of respondents
reported having a buy-sell agreement in place to provide structure for departure of partners
due to retirement, disability, death, etc. Although more than two-thirds (70.4 percent) of
respondents in a 20-or-more-employee practice had a buy-sell agreement in place, the trend
decreased as respondent practice size decreased. No one in a one- or two-to-four-employee
practice reported having a buy-sell agreement in place (Table 147).
0%20%40%60%80%
100%
% o
f Res
pond
ents
Average Gross Collected Revenue (per Year in the Last Three Years)
Distribution of AAEP Respondent Owners Who Want to Sell Their Practice: Confidence in Ability to Sell by Average Gross Collected
Practice Revenue (per Year in the Last Three Years)
Extremely confident Very confident Moderately confident
Not very confident Not at all confident Not sure
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Table 147: Distribution of AAEP Respondent Owners’ Buy-Sell Agreement by Practice Size
Buy/Sell Agreement
1 staff member
(n=96)
2-4 staff members
(n=84)
5-9 staff members
(n=57)
10-19 staff members
(n=47)
20-49 staff members
(n=20)
50 or more staff members
(n=7) Yes 0.0% 0.0% 22.8% 51.1% 65.0% 85.7% No 100.0% 100.0% 77.2% 48.9% 35.0% 14.3%
In preparing for the future, 26.9 percent of AAEP respondent practice owners indicated that
they were looking to current associates to purchase the practice, followed by nearly the same
number of respondents (26.6 percent) who cited a veterinarian not currently working at their
practice as a future successor. 36.7 percent of respondent owners were not sure who might
succeed them, while 7.9 percent AAEP respondents had some other person in mind, and 2
percent of respondents reported that a corporate entity was most likely to purchase their
ownership interest (Figure 165).
Figure 165: Distribution of AAEP Respondents' Entity That Is Most Likely to Purchase Ownership Interest
26.9%
26.6%2.0%
36.7%
7.9%
Distribution of AAEP Respondents' Entity That Is Most Likely to Purchase Owneship Interest (n=305)
Current associate
Veterinarian not currentlyworking at your practice
Corporate entity
Not sure
Other
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Factors Affecting Ownership Interest
Half of the AAEP respondents who were associates expressed that they were interested in
buying ownership shares at some point during their career. The following binary logit
regression looks at a few factors that affect interest in pursuing practice ownership. A binary
logit measures the relationship between the variable of interest (dependent variable) and the
factors (independent variables) hypothesized to affect the variable of interest that is
mathematically computed. In the binary logistic regression, however, the dependent variable
has only two values (1=yes, 0=no) and the relationship measured is the probability of the
dependent variable occurring when the factor occurs. The dependent variable value of 1 was
assigned to veterinarians who were interested in buying shares of a practice, and a value of 0
was assigned if they were not interested (or they were unsure).
Independent variables that were used to attempt to explain the probability of obtaining
ownership interest were age, year of graduation, gender, children, board certification,
residency and internship participation, work region, equine sector, business model and current
practice size.
As a baseline for comparison with the other variables in the respective groups, the following
factors were omitted from the model: work Region 9, general equine sector, ambulatory
business model, and five to nine staff members in a practice.
In this table the coefficients are used to calculate the probability of an individual respondent
falling into a specific category (interested in practice ownership or not interested in practice
ownership). The main gauge to observe is whether the coefficient is positive or negative. This
will indicate the direction of the relationship (i.e., negative is more likely to lead to not
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interested in practice ownership and positive is more likely to be interested in practice
ownership).
Variables that significantly contribute to the predictive ability of the model have a p-value of .10
or less in the column labeled “Sig.” Variables that are significant at the 10 percent, 5 percent
and 1 percent level are reported in explaining the factors affecting interest in practice
ownership . The “Odds Ratio” column is the odds ratio for each of the independent variables
and is defined as “the change in odds of being in one of the categories of outcome (interested
in practice ownership or not interested in practice ownership) when the value of one of the
independent variables (predictors) increases by one point.”66 To interpret the odds ratio, the
odds ratio value is reduced by 1 to obtain the likelihood of the event occurring.
Results in Table 148 show that for each additional year of experience (based on graduation
year) the odds of being interested in practice ownership versus not interested in practice
ownership was .09 lower, given all the other variables are held constant; in other words, each
additonal year of experience decreases the odds of being interested in practice ownership by
nine percent. For AAEP respondents who are female, the odds of interest in practice ownership
versus not interested in practice ownership was .78 lower than males, given all other variables
are held constant. The odds of a respondent interested in practice ownership versus not
interested in practice ownership was greater for those working in Regions 0, 1, 6 and 8,
compared to respondents who work in Region 9, given all other variables are held constant.
For AAEP respondents in the equine companion sector, the odds of interest in practice
ownership versus not interested in practice ownership was 5.52 times greater than
respondents in the general equine sector, given all other variables are held constant. In
66 Barbara G. Tabachnick and Linda S. Fidell . Using Multivariate Statistics, 6th Edition (New York City, New York: Pearson, 2013), pg.8.
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addition, the odds of interest in practice ownership versus not interested in practice ownership
were greater in the Thoroughbred racing (30.06 greater) and reproductive (16.34 greater)
sectors compared to the general equine sector in the AAEP sample, given all other variables are
held constant.
Table 148: Factors Affecting Interest in Practice Ownership
AAEP Coefficient Std. Error Sig. Odds Ratio
Age -0.047 0.056 0.40 0.95 Graduation Year -0.098 0.060 0.10* 0.91 Gender (Female=1) -1.533 0.577 0.01*** 0.22 Children (Yes=1) 0.794 0.466 0.09* 2.21 Board Certified (Yes=1) 0.621 1.155 0.59 1.86 Internship (Yes=1) -0.843 0.495 0.09* 0.43 Residency (Yes = 1) -0.353 1.103 0.75 0.70 Region 0 3.048 0.920 0.00*** 21.06 Region 1 1.390 0.740 0.06** 4.01 Region 2 0.445 0.748 0.55 1.56 Region 3 0.233 0.819 0.78 1.26 Region 4 -1.266 0.915 0.17 0.28 Region 5 0.250 0.757 0.74 1.28 Region 6 1.581 0.871 0.07* 4.86 Region 7 -0.010 0.775 0.99 0.99 Region 8 1.992 0.843 0.02** 7.33 Region 9 (baseline) Omitted General equine (baseline) Omitted Working 1.166 1.401 0.41 3.21 English performance 0.575 0.554 0.30 1.78 Companion 1.708 0.915 0.06* 5.52 Standardbred racing 0.035 1.538 0.98 1.04 Thoroughbred racing 3.403 1.691 0.04** 30.06 Reproductive 2.794 1.235 0.02** 16.34 Western -0.052 1.049 0.96 0.95 Ambulatory (baseline) Omitted Ambulatory with haul-in facility -0.331 0.513 0.52 0.72 Haul-in only -0.083 1.485 0.96 0.92 Specialty/referral - limited service hospital -1.761 1.545 0.25 0.17
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Specialty/referral - full service hospital 1.194 1.559 0.44 3.30 Specialty/referral - limited service hospital with ambulatory
0.588 1.327 0.66 1.80
Specialty/referral - full service hospital with ambulatory
0.799 0.693 0.25 2.22
One staff member -1.138 1.930 0.56 0.32 2 to 4 staff members -0.584 0.613 0.34 0.56 5 to 9 staff members (baseline) Omitted 10 to 19 staff members -0.073 0.525 0.89 0.93 20 to 49 staff members 0.846 0.760 0.27 2.33 50 or more staff members -1.663 1.743 0.34 0.19 Constant 3.338 1.778 0.06 28.16
Observations 195
Pseudo R-Square 0.3086
Note: Other business model, gaited breed and Quarter Horse racing were omitted from the
model because these variables prevented estimation.
***, **, and * indicate significance at the 1 percent (p < .01), 5 percent (p < .05) and 10 percent (p
< .10) levels, respectively
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6.6 COMPENSATION METHODS
There are multiple ways a veterinarian can be compensated for services performed in a
veterinary practice including hourly wages, salary, production-based compensation, and a blend
of base salary with opportunity for production-based compensation. To better understand
compensation patterns in the workplace, the survey asked AAEP respondents a series of
questions related to how they are paid for their work as a veterinarian.
The survey found that 39.2 percent of respondent owners were compensated with no
differentiation between pay for effort as a veterinarian and pay as an owner, followed by 20.3
percent of owners with differentiation between pay for effort as a veterinarian and pay as an
owner. The remaining 40.5 percent of owner respondents were either compensated hourly or
per diem (1.3 percent), production-based only (11.3 percent), salary only (13.3 percent), salary
with opportunity for production-based pay (8.0 percent), salary with non-production based
incentive (1.3 percent), or some other form of compensation (5.3 percent). For respondent
associates, 49.3 percent were on a salary with opportunity for production-based compensation,
followed by 29.5 percent who were paid salary only. The remaining 21.2 percent of associate
respondents were compensated hourly or per diem (3.4 percent), received purely production-
based pay (16 percent), salary with non-production-based incentive (0.9 percent), or earned
some other form of compensation (0.9 percent) (Table 149).
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Table 149: Distribution of AAEP Respondents’ Method of Compensation for Their Work as a Veterinarian
Compensation Method Owner (n=301)
Associate (n=207)
Hourly or per diem 1.3% 3.4% Production based only 11.3% 16.0% Salary only 13.3% 29.5% Salary with opportunity for production-based compensation 8.0% 49.3% Salary with non-production-based incentive 1.3% 0.9% Owner distribution with no differentiation between pay for effort as a veterinarian and pay as an owner
39.2%
Owner distribution with differentiation between pay for effort as a veterinarian and pay as an owner
20.3%
Other 5.3% 0.9% Total 100.0% 100.0%
Associate Compensation
Among associates, more than 60 percent of respondents in English and Western performance
stated that they had a salary with the opportunity for production-based compensation. More
than 50 percent of respondents in the equine companion, reproductive, and ranch or working
categories were compensated on a strictly salary basis. Of Thoroughbred racing respondents,
46.2 percent reported their compensation was salary only, and 38.5 percent earned a salary
with opportunity for production-based compensation (Table 150).
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Table 150: Distribution of AAEP Respondents’ Compensation Method of Associates by Primary Equine Sector67
Hourly or per diem
Production based only
Salary only
Salary with opportunity
for production-
based compensation
Salary with non-
production-based
incentive
Other Total
English performance (n=33)
0.0% 21.2% 9.1% 69.7% 0.0% 0.0% 100.0%
Equine companion (n=10)
10.0% 10.0% 50.0% 30.0% 0.0% 0.0% 100.0%
Racing - QH (n=3)
0.0% 33.3% 33.3% 33.3% 0.0% 0.0% 100.0%
Racing - TB (n=13)
7.7% 7.7% 46.2% 38.5% 0.0% 0.0% 100.0%
Reproductive (n=14)
0.0% 21.4% 57.1% 7.1% 7.1% 7.1% 100.0%
Ranch or working (n=4)
0.0% 25.0% 75.0% 0.0% 0.0% 0.0% 100.0%
Western performance (n=8)
0.0% 0.0% 37.5% 62.5% 0.0% 0.0% 100.0%
General equine (n=118)
4.2% 16.1% 26.3% 51.7% 0.8% 0.8% 100.0%
Observing compensation by business model, the main methods of compensation were salary
only, and salary with opportunity for production-based compensation. 25 percent of
respondents in a full-service hospital with no ambulatory division reported a salary
compensation method, as did 75 percent of respondents working in a limited service
specialty/referral hospital with no ambulatory division. More than 50 percent of respondents
who worked in an ambulatory practice, full-service specialty/referral hospital without
ambulatory division, limited-service specialty/referral hospital with ambulatory division, and a
full-service specialty/referral hospital with ambulatory division received salary with opportunity
for production-based compensation. 57.1 percent of respondents who reported other form of
business model received salary based compensation. Half of the respondents in the haul-in
67 Gaited breeds and Standardbred racing were omitted because the number of observations did not permit estimation.
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facility only business model reported salary-only compensation, while the other half received
salary with opportunity for production-based compensation (Table 151).
Table 151: Distribution of AAEP Respondents’ Compensation Method of Associates by Business Model
Hourly or per diem
Production based only
Salary only
Salary with opportunity
for production-
based compensation
Salary with non-
production- based
incentive
Other Total
Ambulatory (n=52)
5.8% 7.7% 32.7% 53.8% 0.0% 0.0% 100.0%
Ambulatory with Haul-in facil ity (n=79)
5.1% 20.3% 30.4% 43.0% 0.0% 1.3% 100.0%
Haul-in facility only (n=4)
0.0% 0.0% 50.0% 50.0% 0.0% 0.0% 100.0%
Specialty/referral hospital-Limited service (e.g., no colic surgery, isolation, neonatology) (n=4)
0.0% 0.0% 75.0% 25.0% 0.0% 0.0% 100.0%
Specialty/referral hospital-Full service (n=4)
0.0% 0.0% 25.0% 50.0% 25.0% 0.0% 100.0%
Specialty/referral hospital-Limited service with ambulatory division (n=5)
0.0% 20.0% 0.0% 60.0% 0.0% 20.0% 100.0%
Specialty/referral hospital-Full service with ambulatory division (n=50)
0.0% 22.0% 18.0% 60.0% 0.0% 0.0% 100.0%
Other (n=7) 0.0% 14.3% 57.1% 14.3% 14.3% 0.0% 100.0%
68 percent of associate veterinarian respondents reported they preferred a mix of base salary
with the opportunity for additional production-based compensation, followed by 21.2 percent
who preferred straight salary, 8.1 percent who were partial to production-based only, and 2.7
percent who preferred an hourly or per diem compensation arrangement (Figure 166).
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Figure 166: Distribution of AAEP Respondent Associates’ Preferred Method of Compensation
Owners’ Compensation
No more than one-fifth of practice owner respondents in any sector received compensation for
their efforts as a veterinarian separate from their compensation for being a practice owner,
with the exception of 26.7 percent of owners who practiced in the racing Thoroughbred sector.
Very few owner respondents were compensated based on a salary with a non-production-
based incentive; those who were worked in the English performance and general equine
practice sectors. At least 20 percent of owner respondents in the racing sectors, ranch or
working, and Western performance were compensated on production only (Table 152).
21.2%
8.1%
2.7%68.0%
Distribution of AAEP Respondent Associates' Preferred Method of Compensation (n=261)
Salary only
Production-based only
Hourly or per diem
Mix of base salary withoppurtunity for production-based compensation
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Table 152: Distribution of AAEP Respondent Compensation Method of Owners by Primary Equine Sector68
Hourly or per diem
Production based only
Salary only
Salary with opportunity for
production-based compensation
Salary with non-
production- based
incentive English performance (n=46)
0.0% 8.7% 17.4% 8.7% 2.2%
Equine companion (n=15)
0.0% 0.0% 6.7% 13.3% 0.0%
Racing - STB (n=4)
25.0% 50.0% 0.0% 0.0% 0.0%
Racing - TB (n=15)
0.0% 20.0% 6.7% 13.3% 0.0%
Reproductive (n=15)
0.0% 13.3% 13.3% 6.7% 0.0%
Ranch or working (n=4)
0.0% 25.0% 0.0% 0.0% 0.0%
Western performance (n=9)
11.1% 22.2% 11.1% 11.1% 0.0%
General equine (n=186)
1.1% 9.7% 14.0% 7.5% 1.6%
68 Gaited breeds and Quarter Horse racing were omitted because the number of observations did not permit estimation.
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Owner distribution with no
differentiation*
Owner distribution with differentiation**
Other Total
English performance (n=46)
39.1% 19.6% 4.3% 100.0%
Equine companion (n=15)
46.7% 20.0% 13.3% 100.0%
Racing-STB (n=4)
25.0% 0.0% 0.0% 100.0%
Racing-TB (n=15)
20.0% 26.7% 13.3% 100.0%
Reproductive (n=15)
53.3% 13.3% 0.0% 100.0%
Ranch or working (n=4)
25.0% 0.0% 50.0% 100.0%
Western performance (n=9)
44.4% 0.0% 0.0% 100.0%
General equine (n=186)
39.2% 22.6% 4.3% 100.0%
*Owner distribution with no differentiation between pay for effort as a veterinarian and pay as
an owner
**Owner distribution with differentiation between pay for effort as a veterinarian and pay as an
owner
40 percent of owner respondents in a full-service specialty/referral hospital and 50 percent in
limited-service specialty/referral hospital were on a salary with opportunity for production-
based compensation. Owner respondents who worked in specialty/referral hospitals that were
full service (40 percent), limited service with ambulatory division (57.1 percent), or full service
with ambulatory division (38.5 percent) reported the highest percentages of owner
compensation with differentiation between effort as a veterinarian and payment for being an
owner (Table 153).
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Table 153: Distribution of AAEP Respondent Compensation Method of Owners by Business Model
Hourly or per diem
Production based only
Salary only
Salary with opportunity
for production-
based compensation
Salary with non-
production- based
incentive
Ambulatory (n=135) 0.7% 14.8% 11.1% 5.2% 0.7% Ambulatory with Haul-in facility (n=103)
2.9% 6.8% 16.5% 5.8% 1.0%
Haul-in facility only (n=3) 0.0% 0.0% 66.7% 0.0% 0.0% Specialty/referral hospital-Limited service (e.g. no colic surgery, isolation, neonatology) (n=6)
0.0% 0.0% 0.0% 50.0% 16.7%
Specialty/referral hospital-Full service (n=5)
0.0% 0.0% 0.0% 40.0% 20.0%
Specialty/referral hospital-Limited service with ambulatory division (n=7)
0.0% 14.3% 0.0% 14.3% 0.0%
Specialty/referral hospital-Full service with ambulatory division (n=26)
0.0% 11.5% 11.5% 15.4% 0.0%
Other (n=13) 0.0% 23.1% 15.4% 7.7% 0.0%
Page 508 of 577
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Owner distribution
with no differentiation*
Owner distribution with differentiation**
Other Total
Ambulatory (n=135) 48.9% 12.6% 5.9% 100.0% Ambulatory with Haul-in facility (n=103)
35.0% 27.2% 4.9% 100.0%
Haul-in facility only (n=3) 33.3% 0.0% 0.0% 100.0% Specialty/referral hospital-Limited service (e.g. no colic surgery, isolation, neonatology) (n=6)
16.7% 0.0% 16.7% 100.0%
Specialty/referral hospital-Full service (n=5)
0.0% 40.0% 0.0% 100.0%
Specialty/referral hospital-Limited service with ambulatory division (n=7)
14.3% 57.1% 0.0% 100.0%
Specialty/referral hospital-Full service with ambulatory division (n=26)
23.1% 38.5% 0.0% 100.0%
Other (n=13) 38.5% 0.0% 15.4% 100.0%
*Owner distribution with no differentiation between pay for effort as a veterinarian and pay as
an owner
**Owner distribution with differentiation between pay for effort as a veterinarian and pay as an
owner
Page 509 of 577
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Owner respondents were asked they received an owner distribution with no differentiation
between pay for effort as a veterinarian and pay as an owner, or received an owner distribution
with differentiation between pay for effort as a veterinarian and pay as an owner. Among
owner respondents who had no differentiation between pay for effort as a veterinarian and pay
as an owner, 54.2 percent were prorated by their percent of ownership, 6.8 percent were
prorated by their percent of revenue production and 39 percent used some other formula.
Among respondents who had differentiation between pay for effort as a veterinarian and pay
as an owner, 61.5 percent indicated that profit is distributed and prorated by their percent of
ownership, 21.5 percent had profit prorated by their percent of revenue production, and 16.9
percent stated some other form of compensation (Figure 167). For those who chose Other, the
majority stated that they were the sole owner of the practice.
54.2%
6.8%
39.0%
No differentiation between pay for effort as aveterinarian and pay as an owner
% o
f Res
pond
ents
Distribution of AAEP Respondents' Owner Compensatation with No Differentiation (n=118)
Other
Owner pay is prorated bytheir percent of production
Owner pay is prorated bytheir percent of ownership
Page 510 of 577
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© Copyright 2018. American Veterinary Medical Association. All rights reserved.
Figure 167: Distribution of AAEP Respondents’ Owner Compensation with Differentiation and with No Differentiation between Pay for Effort as a Veterinarian and Pay as an Owner
61.5%
21.5%
16.9%
With differentiation between pay for effort as aveterinarian and pay as an owner
% o
f Res
pond
ents
Distribution of AAEP Respondents' Owner Compensatation with Differentiation (n=65)
Other
Profit is distributed toowners prorated by theirpercent of production
Profit is distributed toowners prorated by theirpercent of ownership
Page 511 of 577
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Revenue Production
AAEP respondents, both owners and associates, were asked to indicate how their
compensation based on revenue production was calculated: 14.6 percent of owners and 22.9
percent of associates were compensated based on a consistent percentage of gross
production/sales revenue for all services, medical supplies, and pharmaceuticals. Among
associate respondents, 24.3 percent reported that compensation was derived from a higher
percentage of gross production/sales revenue for services, and a lower percentage of sales of
medical supplies and pharmaceuticals. Less than 10 percent of either group of respondents was
paid on net production, or a variable commission rate depending on the nature of the services
performed (Table 154).
Table 154: Distribution of AAEP Respondents’ Revenue Production Compensation
Owner (n=294)
Associate (n=210)
I am not compensated based on revenue production 53.7% 37.6% Consistent percentage of gross production/sales revenue for all services, medical supplies, and pharmaceuticals
14.6% 22.9%
Consistent percentage of net production/sales revenue for all services, medical supplies, and pharmaceuticals
8.8% 3.3%
Other 8.5% 2.9% Higher percentage of gross production/sales revenue for services, with lower percentage for medical supplies, and pharmaceuticals
6.1% 24.3%
Differing percentage of net production/sales depending on net of particular type of service (e.g., dentistry at one rate, vaccinations at a different rate)
5.4% 1.9%
Consistent percentage of gross production/sales revenue for all services, with no compensation for sales of medical supplies, and pharmaceuticals
1.4% 3.8%
Differing percentage of gross production/sales depending on type of service (e.g., dentistry at one rate, vaccinations at a different rate)
1.4% 3.3%
Total 100.0% 100.0%
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Percentage of Household Income
When asked what percentage of household income was contributed by the respondent, 65.4
percent of male Equine respondents reported that they contributed 76 percent to 100 percent
to their total household income, compared to 42.2 percent of female respondents. A smaller
proportion of male respondents (12.8 percent) reported that they contributed 26 percent to 50
percent of their total household income, compared to 32.6 percent of female respondents.
Among AVMA respondents, 58.1 percent of males contributed 76 percent to 100 percent of
their total household income compared to 42.9 percent of females; 13.7 percent of male
respondents contributed 26 percent to 50 percent of their total household income, and 26.2
percent of females contributed a similar level (Figure 168).
Male (n=257) Female (n=344)76-100% 65.4% 42.2%51-75% 18.3% 19.2%26-50% 12.8% 32.6%0-25% 3.5% 6.1%
% o
f Res
pond
ents
Gender
Percentage of Equine Respondents' Household Income Contribution by Gender
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Figure 168: Percentage of Equine and AVMA Respondents’ Household Income Contribution by Gender
By the time they have worked in equine medicine for 30 years or more, more than 50 percent
of Equine respondents were contributing 76 percent to 100 percent of their household’s total
income. AVMA respondents revealed a similar pattern as AAEP respondents but there was a
lower percent of respondents who contributed income to the household in the 76 percent to
100 percent range, except for respondents who graduated prior to 1967 (Figure 169).
Male (n=621) Female (n=1,514)76-100% 58.1% 42.9%51-75% 25.0% 23.9%26-50% 13.7% 26.2%0-25% 3.2% 6.9%
% o
f Res
pond
ents
Gender
Percentage of AVMA Respondents' Household Income Contribution by Gender
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© Copyright 2018. American Veterinary Medical Association. All rights reserved.
Figure 169: Percentage of Equine and AVMA Respondents’ Household Income Contribution by Graduation Year
0%20%40%60%80%
100%
% R
espo
nden
ts
Graduation Year
Percentage of Equine Respondents' Household Income Contribution by Graduation Year (n=601)
0-25% 26-50% 51-75% 76-100%
0%20%40%60%80%
100%
% o
f Res
pond
ents
Graduation Year
Percentage of AVMA Respondents' Household Income Contribution by Graduation Year (n=2,219)
0-25% 26-50% 51-75% 76-100%
Page 515 of 577
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Practice Management Compensation
Among the AAEP respondents, 94 of 528 (17.8 percent) received compensation for the practice
management duties they performed in their practices, while a considerably larger group 340
respondents (64.4 percent) who had practice management duties did not receive
compensation for these services. An additional 94 respondents (17.8 percent) did not perform
practice management duties in their position. Of the respondents who did perform practice
management duties, 55.3 percent were male and 44.7 percent were female.
When examining compensation for practice management duties by gender, 22.7 percent of the
male respondents and 14.0 percent of the female respondents received compensation while
64.6 percent of males and 64.2 percent of females did not; 12.7 percent of males and 21.7
percent of females did not perform practice management duties in their position (Figure 170).
Figure 170: Distribution of AAEP Respondents’ Compensation of Practice Management Duties by Gender
22.7% 14.0%
64.6%64.2%
12.7% 21.7%
Male (n=229) Female (n=299)
% o
f Res
pond
ents
Gender
Distribution of AAEP Respondents' Compensation of Practice Management Duties by Gender
I do not perform practicemanagement duties in myposition
Did not receivecompensation
Received compensation
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A little more than 20 percent of respondents who graduated from veterinary school more than
10 years ago reported that they received compensation for practice management duties in their
position, while well over 50 percent of respondents in all graduation categories did not receive
compensation for performing this work. Of respondents who graduated within the past five
years, 41.8 percent did not perform practice management duties (Figure 171).
Figure 171: Distribution of AAEP Respondents’ Compensation for Practice Management Duties by Graduation Year
52.7%59.3%
66.3%68.1%73.0%69.0%100.0%
0%
20%
40%
60%
80%
100%
2012-20162007-20111997-20061987-19961977-19861967-1976< 1967
% o
f Res
pond
ents
Year of Graduation
Distribution of AAEP Respondents' Compensation for Practice Management Duties by Graduation Year (n=524)
I do not perform practice management duties in my position
Did not receive compensation
Received compensation
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Nearly three-quarters (73.3 percent) of AAEP respondents in a private practice owned by a sole
veterinarian did not receive practice management compensation compared to 49.7 percent in a
private practice owned by partners/multiple shareholders. Almost one-third (29.3 percent) of
respondents in a partner/multiple shareholder private practice did not perform management
duties, although 21 percent of those who did received compensation compared to 15 percent
in a sole-owner private practice. Of respondents in a private corporate practice (one of multiple
practices owned by veterinarian[s]), 50 percent did not receive compensation for performing
this work, 30 percent did receive compensation for it, and 20 percent did not perform practice
management duties (Table 155).
Table 155: Distribution of AAEP Respondents’ Compensation of Practice Management Duties by Practice Type
Private Practice
owned by a single
veterinarian (n=333)
Private Practice owned by
partners/multiple shareholders
(n=181)
Private Corporate Practice)
(n=10)
Receive 15.0% 21.0% 30.0% Do not receive 73.3% 49.7% 50.0% I do not perform practice management duties in my position
11.7% 29.3% 20.0%
Note: Corporate practice was removed because the number of observations did not permit
estimation.
Page 518 of 577
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© Copyright 2018. American Veterinary Medical Association. All rights reserved.
6.7 RETURNS TO EQUINE VETERINARY PRACTICE
Descriptive statistics were calculated for 2015 revenue, expenses and other variables relative to
significant factors used to determine returns to equine veterinary practices of AAEP
respondents (and Equine respondents for the personal gross revenue of production
subsection). Because the mean can be influenced by values at the high end of the distributions,
the median the value that divides the distribution in half may be a more meaningful
estimate of the central tendency of the population, and so was included in the summary
statistic tables. In certain analyses, the median is reported where appropriate.
6.7.1 Personal Gross Revenue of Production for 2015
Respondents who reported income as 15 percent to 30 percent of their total gross revenue
from production in 2015 were included in this portion of the analysis. Outliers who were
removed from the summary statistic tables are Equine respondents and AVMA respondents
who reported more than $1 million in personal gross revenue of production for 2015 (eight out
of 439 respondents in the Equine sample and 13 in the AVMA sample). All respondents
reporting income as 15 percent to 30 percent of their production were included in the graphs in
this subsection.
Owner and Associate
The median personal gross revenue from production for practice owner Equine respondents
was $385,832, and the median personal gross revenue from production for associates was
$356,500. For AVMA respondents, the median personal gross revenue from production was
$500,000 for owners and $450,000 for associates (Table 156).
Page 519 of 577
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Table 156: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by Owner and Associate
Equine Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
Owner 80 $416,863 $218,731 $262,000 $385,832 $520,000 $70,000 $1,000,000 Associate 88 $386,281 $162,033 $280,000 $356,500 $450,000 $120,000 $1,000,000
AVMA Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
Owner 118 $511,062 $216,301 $380,000 $500,000 $600,000 $42,000 $1,000,000 Associate 232 $462,905 $171,098 $350,000 $450,000 $553,000 $100,000 $1,000,000
The distribution of the Equine and AVMA samples is presented in Figure 172. The largest
percent of owner and associate Equine respondents reported their personal gross revenue of
production in the $300,000-$400,000 range, compared to AVMA owner and associate
respondents who reported personal revenue of production in the $500,000-$600,000 range.
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%
% o
f Res
pond
ents
Personal Gross Revenue of Production ($)
Distribution of Equine Respondents' 2015 Total Personal Gross Revenue of Production by Employment Status
Owner (n=87) Associate (n=89)
Page 520 of 577
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© Copyright 2018. American Veterinary Medical Association. All rights reserved.
Figure 172: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue of Production by Employment Status
Veterinary Experience (measure by graduation year)
The mean personal gross revenue of production among Equine respondents by graduation year
showed a gradual increase in revenue production until after 20 years of practicing veterinary
medicine was reached. Respondents less than five years from graduation reported mean gross
revenue production of $306,019, while respondents who had been practicing for more than 30
years produced a mean of $411,528. AVMA respondents showed similar means with respect to
respondents who recently graduated, similarly bringing in less revenue than those with more
experience (Table 157).
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%
% o
f Res
pond
ents
Personal Gross Revenue of Production ($)
Distribution of AVMA Respondents' 2015 Total Personal Gross Revenue of Production by Employment Status
Owner (n=128) Associate (n=234)
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Table 157: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by Graduation Year
Equine Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
31 years +
24 $411,528 $226,359 $265,000 $398,332 $481,500 $70,000 $1,000,000
21-30 years
36 $431,590 $210,278 $287,500 $355,000 $595,000 $125,000 $1,000,000
11-20 years
29 $441,980 $183,027 $337,168 $442,227 $575,000 $75,000 $825,000
6-10 years
47 $400,613 $188,133 $280,000 $360,000 $430,000 $96,056 $1,000,000
1-5 years
31 $306,019 $98,464 $220,000 $300,000 $374,000 $102,520 $475,000
AVMA Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
31 years +
32 $459,491 $194,974 $365,000 $438,790 $572,500 $80,000 $1,000,000
21-30 years
51 $473,444 $219,529 $300,000 $424,162 $600,000 $155,000 $1,000,000
11-20 years
113 $504,236 $202,619 $400,000 $500,000 $600,000 $42,000 $1,000,000
6-10 years
90 $484,490 $165,121 $374,000 $500,000 $574,000 $140,000 $1,000,000
1-5 years
65 $408,080 $119,724 $330,000 $410,000 $452,000 $150,000 $823,000
Page 522 of 577
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Similar to the data recorded in the Age Earnings Profile of veterinarians from Section 4, Equine
and AVMA respondents in the first five years after graduation reported producing less revenue
than more seasoned practitioners, with earnings and personal gross revenue production
gradually increasing as they gained more experience in the veterinary field. The majority of all
equine respondents who graduated within the last five years reported personal gross revenue
production of under $500,000, while AVMA respondents within five years of graduation
reported gross revenues in a range spanning from $100,000 to $900,000 (Figure 173).
Less$100k
$100k-$200k
$200k-$300k
$300k-$400k
$400k-$500k
$500k-$600k
$600k-$700k
$700k-$800k
$800k-$900k
$900k-$1m
Over$1m
31 years + (n=27) 3.7% 7.4% 14.8% 18.5% 22.2% 11.1% 0.0% 3.7% 0.0% 3.7% 14.8%21-30 years (n=40) 0.0% 7.5% 15.0% 27.5% 12.5% 5.0% 12.5% 2.5% 2.5% 2.5% 12.5%11-20 years (n=30) 3.3% 6.7% 10.0% 16.7% 30.0% 10.0% 10.0% 6.7% 3.3% 0.0% 3.3%6-10 years (n=47) 2.1% 4.3% 21.3% 31.9% 19.1% 6.4% 6.4% 2.1% 4.3% 0.0% 2.1%5 years (n=31) 0.0% 9.7% 32.3% 38.7% 19.4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
% o
f Res
pond
ents
Graduation Year
Distribution of Equine Respondents 2015 Total Personal Gross Revenue of Production by Graduation Year
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Figure 173: Distribution of Equine and AVMA Respondents' 2015 Total Personal Gross Revenue of Production by Graduation Year
Gender
The mean personal gross revenue from production among Equine respondents by gender was
$477,929 for males and $346,638 for females. Among AVMA respondents, the mean personal
gross revenue was $515,159 for males and $451,108 for females (Table 158). The distribution of
personal gross revenue from production by gender is presented in Figure 174. It is important to
note, when interpreting this data, that the mean experience (years since graduation) of male
respondents in this study was more than twice that of females.
Less$100k
$100k-$200k
$200k-$300k
$300k-$400k
$400k-$500k
$500k-$600k
$600k-$700k
$700k-$800k
$800k-$900k
$900k-$1m
Over$1m
31 years + (n=37) 5.4% 2.7% 5.4% 16.2% 24.3% 13.5% 10.8% 2.7% 2.7% 0.0% 16.2%21-30 years (n=56) 0.0% 3.6% 14.3% 23.2% 14.3% 10.7% 10.7% 3.6% 5.4% 0.0% 14.3%11-20 years (n=115) 0.9% 4.3% 10.4% 7.0% 25.2% 16.5% 14.8% 7.8% 8.7% 1.7% 2.6%6-10 years (n=91) 0.0% 1.1% 9.9% 18.7% 14.3% 34.1% 14.3% 1.1% 1.1% 3.3% 2.2%5 years (n=65) 0.0% 4.6% 4.6% 32.3% 40.0% 10.8% 6.2% 0.0% 1.5% 0.0% 0.0%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Res
pond
ents
Graduation Year
Distribution of AVMA Respondents 2015 Total Personal Gross Revenue of Production by Graduation Year
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Table 158: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by Gender
Equine Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
Male 67 $477,929 $215,933 $320,000 $450,000 $605,000 $70,000 $1,000,000 Female 98 $346,638 $138,938 $264,000 $334,234 $400,000 $75,000 $1,000,000
AVMA Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
Male 136 $515,159 $201,726 $385,000 $487,500 $600,000 $80,000 $1,000,000 Female 211 $451,108 $173,344 $330,000 $435,000 $550,000 $42,000 $1,000,000
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%
% o
f Res
pond
ents
by
Gend
er
Total Personal Gross Revenue of Production ($)
Distribution of Equine Respondents' 2015 Total Personal Gross Revenue of Production by Gender
Male (n=74) Female (n=99)
Page 525 of 577
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Figure 174: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue of Production by Gender
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
% o
f Res
pond
ents
Total Personal Gross Revenue of Production ($)
Distribution of AVMA Respondents' 2015 Total Personal Gross Revenue of Production by Gender
Male (n=145) Female (n=213)
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Revenue Production Effect on Income
The higher the median personal gross revenue of production reported by Equine and AVMA
respondents, the higher the income bracket a respondent reported (Table 159). Overall, Equine
or AVMA respondents who brought more revenue into the practice reported higher trends in
personal take-home income (Figure 175).
Table 159: Mean Personal Gross Revenue of Production of Equine and AVMA Respondents by Income
Equine Income
Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
$20,000 to $29,999
5 $112,211 $33,147 $96,056 $115,000 $120,000 $70,000 $160,000
$30,000 to $39,999
6 $168,147 $52,999 $125,000 $162,500 $216,114 $102,520 $240,250
$40,000 to $49,999
11 $201,000 $39,666 $155,000 $206,000 $230,000 $150,000 $264,000
$50,000 to $59,999
8 $268,875 $49,273 $241,000 $289,500 $305,000 $175,000 $305,000
$60,000 to $69,999
26 $299,712 $63,872 $250,000 $285,000 $349,000 $200,000 $400,000
$70,000 to $79,999
28 $334,422 $50,185 $300,000 $333,584 $356,500 $250,000 $463,000
$80,000 to $89,999
18 $383,350 $63,864 $331,300 $367,000 $430,000 $274,000 $500,000
$90,000 to $99,999
8 $419,377 $88,729 $375,000 $395,500 $457,500 $300,000 $599,015
$100,000 to $124,999
28 $494,005 $112,423 $400,000 $450,000 $578,996 $350,000 $770,000
$125,000 to $149,999
10 $550,000 $114,770 $450,000 $497,500 $600,000 $450,000 $775,000
$150,000 to $174,999
8 $687,625 $147,467 $570,000 $677,500 $790,000 $500,000 $926,000
$175,000 to $199,999
6 $760,833 $151,011 $650,000 $732,500 $850,000 $600,000 $1,000,000
$200,000 or greater
5 $905,000 $94,207 $825,000 $900,000 $1,000,000 $800,000 $1,000,000
Page 527 of 577
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AVMA Income
Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
$20,000 to $29,999
5 $121,400 $23,554 $97,000 $150,000 $1,000,000 $784,700 $1,000,000
$30,000 to $39,999
2 $162,500 $53,033 $125,000 $162,500 $200,000 $125,000 $200,000
$40,000 to $49,999
13 $210,077 $53,021 $170,000 $200,000 $250,000 $150,000 $300,000
$50,000 to $59,999
12 $258,974 $42,602 $227,500 $258,948 $302,500 $170,000 $310,000
$60,000 to $69,999
29 $311,640 $66,751 $250,000 $300,000 $374,000 $200,000 $420,000
$70,000 to $79,999
48 $358,317 $74,445 $300,000 $352,657 $416,000 $243,000 $500,000
$80,000 to $89,999
43 $396,618 $67,443 $350,000 $400,000 $450,000 $285,354 $525,000
$90,000 to $99,999
31 $470,341 $73,974 $420,000 $452,000 $500,000 $325,000 $650,000
$100,000 to $124,999
82 $511,922 $78,735 $450,000 $500,000 $570,000 $350,000 $700,000
$125,000 to $149,999
39 $597,400 $107,567 $500,000 $600,000 $670,000 $424,162 $823,000
$150,000 to $174,999
24 $693,649 $147,027 $600,000 $637,287 $797,500 $500,000 $1,000,000
$175,000 to $199,999
11 $735,841 $138,377 $646,000 $700,000 $850,000 $575,000 $1,000,000
$200,000 or greater
19 $889,037 $86,009 $800,000 $850,000 $1,000,000 $784,700 $1,000,000
Page 528 of 577
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Less than$50,000 (n
= 23)
$50,000-$99,999 (n
= 88)
$100,000-$149,999
(n=38)
$150,000-$199,999
(n=14)
$200,000or more(n=13)
Over $1,000,000 0.0% 0.0% 0.0% 7.1% 76.9%$900,000-$1,000,000 0.0% 0.0% 0.0% 7.1% 7.7%$800,000-$900,000 0.0% 0.0% 0.0% 14.3% 15.4%$700,000-$800,000 0.0% 0.0% 7.9% 21.4% 0.0%$600,000-$700,000 0.0% 0.0% 18.4% 28.6% 0.0%$500,000-$600,000 0.0% 2.3% 15.8% 21.4% 0.0%$400,000-$500,000 0.0% 18.2% 50.0% 0.0% 0.0%$300,000-$400,000 0.0% 51.1% 7.9% 0.0% 0.0%$200,000-$300,000 39.1% 27.3% 0.0% 0.0% 0.0%$100,000-$200,000 47.8% 1.1% 0.0% 0.0% 0.0%Less $100,000 13.0% 0.0% 0.0% 0.0% 0.0%
47.8%
51.1%
50.0% 28.6%
76.9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% o
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ents
Income
Distribution of Equine Respondents' 2015 Total Personal Gross Revenue of Production by Income
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Figure 175: Distribution of Equine and AVMA Respondents’ 2015 Total Personal Gross Revenue of Production by Income
Less than$50,000 (n
= 23)
$50,000-$99,999(n=88)
$100,000-$149,999
(n=38)
$150,000-$199,999
(n=14)
$200,000 ormore
(n=13)Over $1,000,000 0.0% 0.0% 0.0% 8.6% 56.3%$900,000-$1,000,000 0.0% 0.0% 0.0% 8.6% 6.3%$800,000-$900,000 0.0% 0.0% 2.5% 8.6% 34.4%$700,000-$800,000 0.0% 0.0% 5.8% 17.1% 3.1%$600,000-$700,000 0.0% 1.8% 22.3% 40.0% 0.0%$500,000-$600,000 0.0% 9.2% 38.8% 17.1% 0.0%$400,000-$500,000 0.0% 34.4% 27.3% 0.0% 0.0%$300,000-$400,000 9.1% 36.8% 3.3% 0.0% 0.0%$200,000-$300,000 27.3% 17.2% 0.0% 0.0% 0.0%$100,000-$200,000 50.0% 0.6% 0.0% 0.0% 0.0%Less $100,000 13.6% 0.0% 0.0% 0.0% 0.0%
50.0% 36.8%
38.8%
40.0%
56.3%
0%10%20%30%40%50%60%70%80%90%
100%
% o
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Income
Distribution of AVMA Respondents' 2015 Total Personal Gross Revenue of Production by Income
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Practice Size
Respondents’ median personal gross revenue from production, in general, consistently
increased as the number of veterinarians in a practice increased to a three-FTE veterinarian
practice. An AAEP respondent in a one-veterinarian practice with no support staff produced a
median of $205,000 in gross revenue; a one-veterinarian practice with support staff earned
$330,000 as a median personal gross revenue from production; and a veterinary practice of two
FTE veterinarians, $400,000 (Table 160).
Table 160: Mean Personal Gross Revenue of Production of AAEP Respondents by Number of FTE Veterinarians in a Practice
Number of FTE Veterinarians
Obs. Mean Std. Dev. 1st Quartile
Median 3rd Quartile
Min. Max.
Solo practitioner (no support staff)
10 $207,452 $121,427 $102,520 $205,000 $275,000 $70,000 $427,000
One FTE veterinarian
22 $371,369 $174,163 $250,000 $330,000 $450,000 $150,000 $785,000
Two FTE veterinarians
16 $438,614 $194,592 $312,500 $400,000 $516,496 $200,000 $926,000
Three FTE veterinarians
16 $339,159 $81,833 $275,000 $347,480 $385,500 $151,000 $450,000
Four FTE veterinarians
9 $385,222 $162,897 $300,000 $382,000 $430,000 $175,000 $750,000
Five FTE veterinarians
6 $463,705 $189,965 $360,000 $446,114 $500,000 $230,000 $800,000
Six or more FTE veterinarians
9 $404,222 $233,820 $295,000 $350,000 $400,000 $220,000 $1,000,000
The general trend among AAEP respondents was that the larger the practice size, the higher the
number of respondents who produced revenue of more than $300,000 (Figure 176). A greater
percent of respondents from five- and six-doctor practices earned revenue of more than
$500,000 than did those from four-doctor and smaller practices.
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Figure 176: Distribution of AAEP Respondents’ 2015 Total Personal Gross Revenue of Production by FTE Veterinarians in a Practice
0%10%20%30%40%50%60%70%80%90%
100%
% o
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FTE Veterinarians
Distribution of AAEP Respondents' 2015 Total Personal Gross Revenue of Production by Number of FTE Veterinarians in a Practice
Over $1,000,000
$900,000-$1,000,000
$800,000-$900,000
$700,000-$800,000
$600,000-$700,000
$500,000-$600,000
$400,000-$500,000
$300,000-$400,000
$200,000-$300,000
$100,000-$200,000
Less $100,000
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6.7.2 Total Practice Gross Revenue of Production
AAEP respondents who are practice owners in the United States were specifically asked about
the gross revenue of production of their practice. Respondents were asked to record the
practice’s gross revenue of production that was listed on their tax forms Sole Proprietorships:
Tax Form 1040/Schedule C, Line 7; Partnerships: Tax Form 1065, Line 1C; Corporations: Tax
Form 1120, Line 1C. Owners who reported between $0 and $6 million of total practice gross
revenue of production in 2015 were used (213 out of 221 respondents) to account for the
outliers in the data. With these parameters , the overall mean of AAEP respondent owners’
total practice gross production revenue was $903,487. The median was $450,000.
Practice Type
Among AAEP respondents, the median total practice gross revenue from production for owners
who are solo practitioners was $125,000; that figure for owners in a private practice owned by
a sole veterinarian with support staff was $431,416. For respondents in private practice owned
by multiple partners/shareholders, the median was $1,887,500 (not shown in Table 161). For
respondents in a private practice owned by multiple partners/shareholders, the median was
then broken out by the number of FTEs at the practice, and the general trend of the reported
median increased for each additional FTE veterinarian (owners, associates, interns, and
resident (residency participants) in a practice (Table 161).
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Table 161: Mean Practice Gross Revenue of Production of AAEP Respondents by Practice Type 69
Type of Practice Obs. Mean Std. Dev. 1st Quartile Median
Solo Practitioner 42 $170,940 $139,599 $77,000 $125,000 Private Practice Owned by one veterinarian
114 $610,566 $513,851 $250,000 $431,416
Private Practice Owned by partners/multiple shareholders: One FTE veterinarian 8 $648,120 $655,788 $248,000 $327,527 Two FTE veterinarians 9 $974,047 $716,942 $560,000 $702,809 Three FTE veterinarians 7 $1,132,635 $620,182 $517,576 $1,264,895 Four FTE veterinarians 6 $2,413,017 $1,094,687 $1,632,000 $2,062,500 Five FTE veterinarians 3 $1,775,773 $456,109 $1,469,790 $1,557,528 Six FTE veterinarians 23 $3,152,502 $1,319,781 $2,394,050 $3,300,000
Type of Practice Obs. 3rd Quartile Min. Max.
Solo Practitioner 42 $230,000 $80 $565,000 Private Practice Owned by one veterinarian
114 $835,239 $250 2,500,000
Private Practice Owned by partners/multiple shareholders: One FTE veterinarian 8 $1,007,802 $18,305 $2,000,000 Two FTE veterinarians 9 $940,899 $288,113 $2,195,000 Three FTE veterinarians 7 $1,705,971 $140,000 $1,800,000 Four FTE veterinarians 6 $3,400,000 $1,242,103 $4,079,000 Five FTE veterinarians 3 $2,300,000 $1,469,790 $2,300,000 Six FTE veterinarians 23 $4,043,000 $453,000 $5,300,000
69 Corporate practice was omitted because the number of observations did not permit estimation.
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Primary Equine Sector
Although a statistical test measuring the significance of equine sectors to practice revenue was
not significant, Table 162 is presented for potential interest to the reader. On average,
respondents who are owners of a practice in the Thoroughbred racing sector had the highest
median revenue at $1.2 million, followed by the reproductive sector at $653,806. The lowest
median practice gross revenue of production was reported by respondents in the Western
performance sector, with $240,000.
Table 162: Practice Gross Revenue of Production of AAEP Respondents by Primary Equine Sector70
Equine Sectors Obs. Mean Std. Dev. 1st Quartile Median
English performance 37 $820,983 $1,180,595 $216,114 $325,000 Equine companion 8 $576,055 $630,955 $164,367 $270,000 Racing - STB 5 $397,000 $487,465 $58,000 $212,000 Racing - TB 9 $1,479,025 $1,466,767 $375,000 $1,200,000 Reproductive 10 $1,371,835 $1,504,747 $380,000 $653,806 Western performance 7 $346,143 $348,804 $150,000 $240,000 General equine 132 $911,251 $1,051,406 $247,500 $503,000
Equine Sectors Obs. 3rd Quartile Min. Max.
English performance 37 $916,000 $197 $5,200,000 Equine companion 8 $858,153 $95,976 $1,927,424 Racing - STB 5 $500,000 $15,000 $1,200,000 Racing - TB 9 $1,800,000 $250 $4,730,000 Reproductive 10 $2,000,000 $127,989 $4,043,000 Western performance 7 $360,000 $35,000 $1,100,000 General equine 132 $1,100,000 $80 $5,300,000
70 Ranch or working and gaited breeds were omitted because the number of observations did not permit estimation. There were no Quarter Horse racing observations.
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Business Model
The average practice gross revenue of production for the respondents working in the three
types of specialty/referral hospital business models were more than $1 million. Both
specialty/referral hospitals (limited and full-service) with ambulatory divisions had a median
greater than than $1 million. Of AAEP respondents who owned an ambulatory practice, the
median gross production revenue was $288,113. Respondent owners of an ambulatory with
haul-in facility reported a median of $549,000, and those with haul-in only facility reported a
median of $240,000 (Table 163).
Table 163: Practice Gross Revenue of Production of AAEP Respondents by Business Model 71
Business Model Obs. Mean Std. Dev. 1st Quartile Median
Ambulatory 95 $475,820 $539,349 $127,989 $288,113 Ambulatory with Haul-in facility 74 $874,298 $778,015 $310,779 $549,000 Haul-in facility only 3 $548,250 $613,499 $150,000 $240,000 Specialty/referral hospital-Limited service (e.g., no colic surgery, isolation, neonatology)
6 $1,272,992 $1,520,442 $100,000 $765,000
Specialty/referral hospital-Limited service with ambulatory division
7 $2,259,942 $1,669,125 $1,025,603 $1,800,000
Specialty/referral hospital-Full service with ambulatory division
18 $2,535,743 $1,496,352 1000000 $2,507,864
Other 8 $302,150 $ 189,884 $155,351 $337,500
71 Specialty/referral hospital-full service was omitted because the number of observations did not permit estimation.
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Business Model Obs. 3rd Quartile Min. Max.
Ambulatory 95 $560,000 $197 $2,585,000 Ambulatory with Haul-in facility 74 $1,425,000 $80 $4,043,000 Haul-in facility only 3 $1,254,749 $150,000 $1,254,749 Specialty/referral hospital-Limited service (e.g., no colic surgery, isolation, neonatology)
6 $2,000,000 $7,949 $4,000,000
Specialty/referral hospital-Limited service with ambulatory division
7 $3,600,000 $140,250 $4,730,000
Specialty/referral hospital-Full service with ambulatory division
18 $3,954,000 $453,000 $5,200,000
Other 8 $362,500 $56,500 $650,000
6.7.3 Average Gross Collected Revenue
Owner AAEP respondents were surveyed concerning average gross collected revenue per year
over the past three years (2013-2015). This question featured a categorical variable that was
presented by revenue ranges from ”less than $250,000” to “over $10,000,000.” Due to the low
responses with observations exceeding $4 million in average gross collected revenue, the last
category included in this analysis is “over $4,000,000.” Included in this subsection of the
analysis are graphs that display the distributions of different significant variables.
Practice Type
Respondents indicated the average gross collected revenue per year of their practice over a
three-year period. Nearly 80 percent of respondents in the group of private practices owned by
a sole veterinarian with no support staff indicated that they collected gross revenue of less than
$250,000 while 40 percent of respondents in a private practice owned by a sole veterinarian
with support staff reported between $250,001 and $500,000. Of respondents in private
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practice owned by partners/multiple shareholders (which includes four respondents in a private
corporate practice), more than one-quarter (26.6 percent) reported collected practice revenue
between $1 million to $2 million (Figure 177).
Figure 177: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by Practice Ownership Type
Practice Size (FTE Veterinarians)
Nearly 50 percent of AAEP respondents in a one-veterinarian practice reported average gross
collected practice revenue per year of less than $250,000. As practice size increased, a higher
percentage of respondents reported increased collected revenues. Of AAEP respondents in a
practice of six or more veterinarians, 31.6 percent reported more than $4 million in average
collected practice revenue over the past three years (Figure 178).
0.0%20.0%40.0%60.0%80.0%
100.0%
% o
f Res
pond
ents
Average Gross Collected Revenue per Year (from 2013-2015)
Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years)
by Practice Ownership TypePrivate Practice owned by asingle veterinarian, no staff(n=69)
Private Practice owned by asingle veterinarian (n=147)
Private Practice (or PrivateCorporate Practice) owned bypartners/multiple shareholders(n=79)
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Figure 178: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by Number of FTE Veterinarians in a Practice
One(n=173)
Two(n=31)
Three(n=24)
Four(n = 16)
Five(n=13)
Six ormore
(n=38)Over $4,000,000 0.0% 0.0% 0.0% 0.0% 0.0% 31.6%$3,000,001-$4,000,000 0.0% 0.0% 0.0% 18.8% 0.0% 13.2%$2,000,001-$3,000,000 0.0% 0.0% 4.2% 6.3% 53.8% 26.3%$1,000,001-$2,000,000 4.8% 9.7% 33.3% 50.0% 30.8% 18.4%750,001-$1,000,000 4.2% 19.4% 29.2% 0.0% 0.0% 7.9%$500,001-$750,000 8.3% 22.6% 16.7% 12.5% 0.0% 2.6%$250,001-$500,000 35.1% 35.5% 12.5% 12.5% 0.0% 0.0%Less than $250,000 47.6% 12.9% 4.2% 0.0% 15.4% 0.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% o
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# of FTE Veterinarians at Practice
Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years), by
Number of FTE Veterinarians
Over $4,000,000
$3,000,001-$4,000,000
$2,000,001-$3,000,000
$1,000,001-$2,000,000
750,001-$1,000,000
$500,001-$750,000
$250,001-$500,000
Less than $250,000
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Equine Sector
Analyzing the average three-year gross collected revenue of a practice per year by equine
sector shows more than 50 percent of AAEP respondents reported average practice revenue of
under $1 million. 6.7 percent of the respondents in the Thoroughbred racing sector, 8.7 percent
in the English performance sector, 13.3 percent in the reproductive sector, and 2.7 percent in
general equine, reported more than $4 million in practice revenue (Figure 179).
Figure 179: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by Equine Sector72
72 Gaited breeds and Quarter Horse racing were omitted because the number of observations did not permit estimation.
% o
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in E
quin
e Se
ctor
Average Gross Collected Revenue per Year (2013-2015)
Distribution of AAEP Respondent Owners' Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by
Equine Sector
Over $4,000,000
$3,000,001-$4,000,000
$2,000,001-$3,000,000
$1,000,001- $2,000,000
750,001-$1,000,000
$500,001- $750,000
$250,001-$500,000
Less than $250,000
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Business Model
A review of responses relative to business model finds 90.8 percent of the AAEP respondents in
an ambulatory practice, 71.6 percent of respondents in an ambulatory with haul-in facility, and
92.3 percent of respondents in the “Other” category of practice with reported practice revenue
of less than $1 million. Two out of the three respondents practicing in a solely haul-in facility
reported practice revenue of less than $250,000. Respondents whose practices collected more
than $4 million in revenue were in a full-service specialty/referral hospital (40 percent), or a
full-service specialty/referral hospital with an ambulatory division (38.5 percent) (Figure 180).
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Figure 180: Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by Business Model
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% o
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Primary Business Model
Distribution of AAEP Respondent Owners’ Average Gross Collected Revenue Earned per Year for Their Practice (over the last three years) by
Business Model
Over $4,000,000
$3,000,001-$4,000,000
$2,000,001-$3,000,000
$1,000,001-$2,000,000
750,001-$1,000,000
$500,001-$750,000
$250,001-$500,000
Less than $250,000
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6.7.4 Revenue and Income Contraction and Expansion of Equine Practices
AAEP respondents who were practice owners were asked specifically about whether their
practices’ gross revenue production expanded (increased) or contracted (decreased) in 2015
compared to 2014. This was also examined by the type of equine sector in which the
respondents worked.
Practice Gross Revenue
Overall, 64.1 percent of owner respondents reported an expansion in practice gross revenue
from 2015 compared to 2014; 13.1 percent reported a contraction, 16.6 percent of
respondents stayed the same, and 6.3 percent were unsure.
Observing contraction and expansion among equine sectors from 2014 to 2015 finds that 80
percent of Standardbred racing respondents saw no change in their practice gross revenue for
2015 compared to 2014. More than 50 percent of respondents in the English performance,
equine companion, Thoroughbred racing, reproductive, ranch or working, Western
performance, and general equine sectors reported an increase in gross revenue. AAEP
respondents who reported a decrease in revenue represented English performance (16.3
percent percent), equine companion (13.3 percent), Thoroughbred racing (5.9 percent),
reproductive (12.5 percent), ranch or working (20.0 percent), Western performance (11.1
percent), and general equine sectors (13.7 percent) (Figure 181). The majority of AAEP
respondents reported that their practices’ gross revenue expanded or stayed the same when
comparing 2015 to 2014.
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Figure 181: Distribution of AAEP Respondents’ Practice Gross Revenue Change in 2015 Compared to 201473
The reported average decrease and increase in practice revenues ranged from 7 percent to 10
percent. The percent of contraction and expansion of practice gross revenue by equine sector is
presented in Figure 182 and Figure 183.
Contraction: The decrease in practice revenue varied among respondents in the English
performance and general equine sectors, with 37.5 percent of English performance and 29.6
percent of general equine respondents reporting a 7 percent to 10 percent contraction. There
were not enough observations among the other equine sectors to permit estimation (Figure
182).
73 Quarter Horse racing and gaited breeds were omitted because the number of observations did not permit estimation.
0%10%20%30%40%50%60%70%80%90%
100%
% o
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pond
ents
Primary Equine Sector
Distribution of AAEP Respondents' Practice Gross Revenue Change in 2015 Compared to 2014
Increased Decreased Stayed the same Not sure
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Expansion: The percent of expansion among equine sectors varied. Half of the respondents in
the Western performance sector reported more than a 15 percent increase in practice revenue.
More than 40 percent of owner respondents in English performance, equine companion,
Thoroughbred racing, reproductive, and Western performance reported a more than 11
percent increase in gross practice revenue (Figure 183).
Figure 182: Distribution of AAEP Respondents’ Practice Gross Revenue Contraction from 2014-201574
74 Gaited breeds, Quarter Horse racing, Thoroughbred racing, equine companion, reproductive, ranch or working, gaited breeds, and Western performance were omitted because the number of observations did not permit estimation.
12.5% 7.4%
25.0% 25.9%
37.5%29.6%
12.5%14.8%
12.5% 22.2%
English performance(n=8)
General equine (n=27)
% o
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Primary Equine Sector
Distribution of AAEP Respondents' Practice Gross Revenue Contraction from 2014-2015
More than 15%
11-15%
7-10%
4-6%
1-3%
% Contraction
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Figure 183: Distribution AAEP Respondents’ Practice Gross Revenue Expansion from 2014-201575
75 Quarter Horse racing, Standardbred racing and gaited breeds were omitted because the number of observations did not permit estimation.
0%10%20%30%40%50%60%70%80%90%
100%
% o
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pond
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Primary Equine Sector
Distribution of AAEP Respondents' Practice Gross Revenue Expansion from 2014-2015
More than 15%
11-15%
7-10%
4-6%
1-3%
% Expansion
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Net Income (the “Bottom Line”)
Net income is a practice’s total revenue minus all the expenses of the business, including both
fixed and variable costs. The majority of Standardbred racing respondents saw no change in
their net income for 2015 compared to 2014 (60 percent). More than 50 percent of
respondents in the English performance, equine companion, Thoroughbred racing,
reproductive, Western performance, and general equine sectors reported an increase in their
net income. While 40 percent of respondents in the ranch or working sector were not sure of
their net income change, another 40 percent reported an increase in net income. Those
respondents that reported a decrease of net income included 18.4 percent of English
performance respondents, 13.3 percent of equine companion respondents, 5.9 percent of
Thoroughbred racing, 18.8 percent of reproductive, 11.1 percent of Western performance, and
16.8 percent of the general equine practice sector (Figure 184).
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Figure 184: Distribution of AAEP Respondents’ Net Income Change in 2015 Compared to 201476
The average decrease and increase in practice net income reported by respondents ranged
from 7 percent to 10 percent.
The percent contraction and expansion of net income by equine sector is presented in the
following two figures. The few respondents in the equine companion sector reported a
decrease in net income of 4 percent to 6 percent from 2014 to 2015. Greater variation was
seen in the percent decrease in net income by respondents who owned a practice in the English
performance and general equine sectors because of the high representation of these groups
among the responses (Figure 185).
76 Gaited breeds and Quarter Horse racing was omitted because the number of observations did not permit estimation.
0%10%20%30%40%50%60%70%80%90%
100%
% o
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ents
Primary Equine Sector
Distribution of AAEP Respondents' Net Income Change in 2015 Compared to 2014
Increased Decreased Stayed the same Not sure
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More than one-third (33.3 percent) of respondents with a practice in the English performance
sector, 20 percent of those in the equine companion sector, 22.2 percent of those involved in
Thoroughbred racing, 18.2 percent of those in the reproductive sector, 66.7 percent of those
practicing in the Western performance sector, and 16 percent of respondents in the general
equine practice sector reported more than 15 percent expansion in net income (Figure 186).
Figure 185: Distribution of AAEP Respondents’ Practice Net Income Contraction from 2014-201577
77 Quarter Horse racing, Thoroughbred racing, Standardbred racing, equine companion, gaited breeds, and Western performance were omitted because the number of observations did not permit estimation
0%
20%
40%
60%
80%
100%
English performance(n=9)
Reproductive(n=3)
General equine(n=33)
% o
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Primary Equine Sector
Distribution of AAEP Respondents' Practice Net Income Contraction from 2014-2015
1-3% 4-6% 7-10% 11-15% More than 15%
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Figure 186: Distribution AAEP Respondents’ Practice Net Income Expansion from 2014-201578
6.7.5 Total Practice Expenses/Deductions for 2015
Practice expenses are the fixed and variable costs incurred in operating a veterinary practice.
Expenses include the cost of pharmaceuticals/supplies, labor expense, administrative costs, and
expenses involving equipment/facilities. Practice expenses range from vehicle maintenance to
shipping materials to insurance, to utility, phone and internet costs. Expenses also include
78 Quarter Horse racing, Standardbred racing, gaited breeds, and ranch or working were omitted because the number of observation did not permit estimation.
0%10%20%30%40%50%60%70%80%90%
100%
Englishperformance
(n=24)
Equinecompanion
(n=10)
Racing-TB(n=9)
Reproductive(n=11)
Westernperformance
(n=6)
Generalequine(n=100)
% o
f Res
pond
ents
Primary Equine Sector
Distribution of AAEP Respondents' Practice Net Income Expansion from 2014-2015
1-3% 4-6% 7-10% 11-15% More than 15%
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compensation for support staff and associate veterinarians as well as costs of various benefit
and perquisite programs.
Equine practice owners who responded to the survey were asked what their total practice
expenses/deductions were for 2015 as listed on: Tax Form 1040/Schedule C, Line 28 for sole
proprietorship; Partnerships: Tax Form 1065, Line 21; and Corporations: Tax Form 1120, Line
27. Respondents reported expenses between $19,025 and $28.8 million. Outliers removed
were those respondents reporting practice expenses greater than $4 million, with the median
reported in this subsection. The average expense was $572,771.20.
Practice Type
The highest median practice expenses and deductions reported for 2015 among practice types
came from respondents who owned a private practice with partners/multiple shareholders;
their median expenses were $982,245 compared to $344,401 reported by respondents in a
private practice owned by a single veterinarian, and $61,850 for respondents in a private
practice owned by a sole veterinarian with no support staff (Table 164).
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Table 164: Median 2015 Practice Expenses/Deductions of AAEP Respondents by Practice Type 79
Type of Practice Obs. Mean Std. Dev. 1st Quartile Median
Solo Practitioner 38 $92,547 $81,006 $40,000 $61,850 Private Practice Owned by a single veterinarian
84 $491,563 $454,693 $185,512 $344,401
Private Practice (or Private Corporation80) Owned by partners/multiple shareholders: One FTE veterinarians 5 $587,041 $638,617 $194,835 $300,000 Two FTE veterinarians 9 $663,179 $532,937 $280,000 $551,212 Three FTE veterinarians 3 $920,500 $685,389 $214,220 $964,390 Four FTE veterinarians 4 $1,621,788 $940,195 $918,575 $1,374,000 Five FTE veterinarians 12 $2,125,305 $1,184,946 $1,291,904 $1,849,000
Type of Practice Obs. 3rd Quartile Min. Max.
Solo Practitioner 38 $122,711 $21,000 $427,000 Private Practice Owned by a single veterinarian 84 $701,728 $19,025 $2,250,000 Private Practice (or Private Corporation) Owned by partners/multiple shareholders: One FTE veterinarians 5 $816,000 $24,368 $1,600,000 Two FTE veterinarians 9 $690,344 $100,000 $1,598,000 Three FTE veterinarians 3 $1,582,889 $214,220 $1,582,889 Four FTE veterinarians 4 $2,325,000 $839,150 $2,900,000 Five FTE veterinarians 12 $3,020,603 $272,696 $4,000,000
79 Five FTE veterinarians was omitted because the number of observations did not permit estimation.
80The few respondents who reported being in a private corporate practice with multiple veterinarians were reported with the respondents in a private practice with multiple partners/shareholders.
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Practice Size (per Veterinarian)
The survey responses indicated that, in general, the more veterinarians in a practice, the lower
the practice expenses and deductions per veterinarian (at the median). Sole practitioners
reported a median of $79,445 in practice expenses and deductions; a veterinarian in a practice
of one FTE veterinarian with support staff reported a median of $250,000 in expenses and
deductions. The median expenses/deductions decreased per veterinarian the more
veterinarians in a practice until reaching that of a five FTE veterinarian practice, which reflected
a median of $257,136. However, median expenses/deductions reported by the 16 respondents
working in veterinarian practices with six or more FTE decreased to that seen in a three FTE
veterinarian practice (Table 165).
Table 165: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Number of FTE Veterinarians in a Practice
Number of FTE Veterinarians Obs. Mean Std. Dev. 1st Quartile Median
Sole Practitioner 39 $109,645 $86,155 $52,000 $79,445 One FTE veterinarian 47 $333,661 $250,547 $159,297 $250,000 Two FTE veterinarians 24 $265,608 $166,051 $157,227 $237,694 Three FTE veterinarians 13 $224,688 $120,923 $133,333 $233,333 Four FTE veterinarians 10 $283,503 $210,466 $146,375 $217,989 Five FTE veterinarians 5 $297,724 $130,286 $200,000 $257,136 Six or more FTE veterinarians 16 $224,999 $115,846 $163,615 $233,880
Number of FTE Veterinarians Obs. 3rd Quartile Min. Max.
Sole Practitioner 39 $150,000 $21,000 $427,000 One FTE veterinarian 47 $500,222 $19,025 $1,066,667 Two FTE veterinarians 24 $325,086 $34,327 $735,496 Three FTE veterinarians 13 $275,948 $71,407 $527,630 Four FTE veterinarians 10 $437,500 $56,250 $725,000 Five FTE veterinarians 5 $420,000 $161,485 $450,000 Six or more FTE veterinarians 16 $291,673 $30,300 $500,000
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Primary Equine Sector
Although the differences in expenses reported by respondents across equine sectors were not
significant, the numbers are reported here for general information. Respondents who owned a
practice in the reproductive sector had the greatest median expenses and deductions
($339,895). At the low end of the spectrum, the few respondents in the Standardbred racing
sector had the smallest median expense for their practice at $77,000. Western performance
had a median of $80,000. The English performance sector had a median that exceeded
$200,000, and a median of more than $300,000 was observed in the equine companion and
general equine medicine subsectors (Table 166).
Table 166: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Primary Equine Sector81
Equine Sectors Obs. Mean Std. Dev. 1st Quartile Median
English performance 23 $389,099 $494,683 $122,000 $215,000 Equine companion 6 $568,481 $719,269 $57,638 $309,520 Racing - STB 3 $138,333 $141,359 $38,000 $77,000 Racing - TB 7 $711,841 $824,471 $100,000 $200,000 Reproductive 9 $1,264,867 $1,616,582 $251,623 $339,895 Western performance 3 $110,000 $70,000 $60,000 $80,000 General equine 101 $550,641 $644,848 $100,000 $330,000
Equine Sectors Obs. 3rd Quartile Min. Max.
English performance 23 $586,000 $21,000 $2,250,000 Equine companion 6 $775,000 $57,390 $1,901,821 Racing - STB 3 $300,000 $38,000 $300,000 Racing - TB 7 $1,582,889 $100,000 $2,100,000 Reproductive 9 $1,600,000 $27,000 $4,000,000 Western performance 3 $190,000 $60,000 $190,000 General equine 101 $724,742 $19,025 $3,441,878
81 Ranch/or working, Quarter Horse racing, and gaited breeds were omitted because the number of observations did not permit estimation.
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Business Model
Observation of practice expenses by business model revealed that respondents in
specialty/referral hospitals with limited services and full service hospitals with ambulatory
divisions had median expenses and deductions of $837,698 and $2,000,000, respectively.
Respondents owning some other type of practice carried the smallest median expenses of
$112,500. Median expenses among respondents from the ambulatory business model were
$181,898, and median expenses from respondents in an ambulatory with haul-in facility wereas
$427,000 (Table 167).
Table 167: Mean 2015 Practice Expenses/Deductions of AAEP Respondents by Business Model 82
Business Models Obs. Mean Std. Dev. 1st Quartile Median
Ambulatory 73 $327,436 $428,621 $68,654 $181,898 Ambulatory with Haul-in facility 57 $654,587 $671,493 $225,000 $427,000 Specialty/referral hospital-Limited service with ambulatory division
4 $1,152,035 $1,225,663 $424,372 $837,698
Specialty/referral hospital-Full service with ambulatory division
10 $2,034,252 $1,091,136 $989,489 $2,000,000
Other 8 $148,849 $100,620 $ 78,647 $112,500
Business Models Obs. 3rd Quartile Min. Max.
Ambulatory 73 $404,571 $21,000 $2,250,000 Ambulatory with Haul-in facility 57 $888,167 $36,000 $3,961,153 Specialty/referral hospital-Limited service with ambulatory division
4 $1,879,698 $32,744 $2,900,000
Specialty/referral hospital-Full service with ambulatory division
10 $2,599,328 $700,000 $4,000,000
Other 8 $ 240,000 $28,500 $300,000
82 Haul-in facility only, l imited service specialty/referral hospital, and full-service specialty/referral hospital were omitted because the number of observations did not permit estimation.
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6.7.6 Current Ratio
Equine practice owners who responded to the survey were asked what their total assets and
liabilities were as recorded on their 2015 balance sheet. If respondents had multiple owners at
their practice, the respondents indicated their share of total assets and total liabilities.
Respondents reported their total assets as low as $50 and as high as $31 million. Respondents
reported their total liabilities as low as $50 and as high as $9.5 million. Those who reported
total assets greater than $4.5 million and total liabilities greater than $1.3 million were
considered outliers and removed from the sample.
The overall mean total assets of respondents were $522,388. The average total liabilities of a
respondent in a practice was $139,964.20
The current ratio (current assets to current liabilities) is a measure of the practice’s ability to
meet short-term obligations. The median current ratio of owner respondent’s equine practices
is 5.74, with a range of less than .01 to 61.6. This means that the median veterinary practice
has $5.67 of current assets for each $1 of current liabilities. Acceptable minimal current
ratios vary from industry to industry and are generally between 1.5 and 3
for healthy businesses.83
Practice Type
Calculations of the current ratio for owner respondents could only be calculated for those
respondents in private practice. Respondents in a private corporate practice reported not
having access to the asset and liability information. Respondents who were solo practitioners
reported a median current ratio of 2.02, respondents in a single owner private practice with
83 https://www.adelaide.edu.au/vetsci/vibe/student-resources/learning-guides/key-performance-indicators/kpis-uoa-olt-9apr2014.pdf
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support staff reported a median current ratio of 3.41, and those in a private practice owned by
partners/multiple shareholders reported a median of 1.42. That is, for every $1 of liabilities,
solo practitioners had $2.02 of assets and single owner veterinarians with support staff had
$3.41 of assets. For every $1 of liabilities, owners in a multiple owner practice had $1.42 of
assets (Table 168).
Table 168: Mean Current Ratio of AAEP Respondents by Practice Type
Variable Obs. Mean Std. Dev.
1st Quartile
Median 3rd Quartile
Min. Max.
Solo Practitioner 11 3.60 4.26 1.05 2.02 5.15 0.35 15.00 Private Practice Owned by a single veterinarian
39 8.18 12.84 1.09 3.41 9.83 0.80 61.57
Private Practice Owned by partners/multiple shareholders84
23 2.60 3.08 1.00 1.42 3.16 0.01 15.00
Number of Full-Time Equivalent (FTE) Veterinarians in a Practice
Among respondents in the survey, the current ratio with respect to number of FTE veterinarians
in a practice showed a fluctuation in the medians depending on the number of veterinarians in
the practice. Respondents who reported being solo practitioners reported a median of $1.71 of
assets for every $1 in liabilities, slightly higher than respondents at practices with six or more
FTE veterinarians, who reported their median current ratio in a practice as having $1.17 in
assets for $1 in liabilities, on average. Respondents in a one-FTE veterinarian practice with
support staff reported a median current ratio of 3.41, followed by 2.53 in a practice with two
84 The few respondents who reported being in a private corporate practice with multiple veterinarians were reported with the respondents in a private practice with multiple partners/shareholders.
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FTE veterinarians, 2.36 in a three-FTE veterinarian practice, 18.9 in a four-FTE veterinarian
practice, and 3.33 in a five-FTE veterinarian practice (Table 169).
Table 169: Mean Current Ratio of AAEP Respondents by Number of FTE Veterinarians in a Practice
FTE Veterinarian Obs. Mean Std. Dev.
1st Quartile
Median 3rd Quartile
Min. Max.
Solo Practitioner 12 3.39 4.13 1.03 1.71 4.41 0.35 15.00 One veterinarian 17 4.45 4.74 1.00 3.41 5.00 0.80 19.81 Two veterinarians 15 9.76 18.97 1.00 2.53 4.71 0.01 61.57 Three veterinarians 7 6.46 6.63 1.09 2.36 15.00 0.70 15.02 Four veterinarians 5 13.23 10.46 3.04 18.90 19.23 1.00 24.00 Five veterinarians 7 4.16 3.40 1.00 3.33 6.13 1.00 10.00 Six or more veterinarians
11 1.95 1.36 1.00 1.17 3.16 0.76 4.40
Primary Equine Sector
Although current ratios across equine sectors were not significant, the mean current ratios of
the practices in different equine sectors are presented for general interest in Table 170. AAEP
respondents in the Thoroughbred racing industry reported the highest median current ratio of
12.50, with the lowest reported in the General equine sector with 1.56, although the lowest
current ratio average (mean) was in the English performance sector (3.9). The median current
ratio of respondents in the English performance, reproductive, and Western sectors range from
$3.16 to $5 in assets for every $1 of liabilities.
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Table 170: Mean Current Ratio of AAEP Respondents by Primary Equine Sector85
Equine Sector Obs. Mean Std. Dev.
1st Quartile
Median 3rd Quartile
Min. Max.
English performance
13 3.90 4.99 1.05 3.16 3.67 0.80 19.81
Racing - TB 4 18.93 21.55 5.35 12.50 32.50 0.70 50.00 Reproductive 3 6.91 7.27 1.00 4.71 15.02 1.00 15.02 Western performance
3 5.32 1.22 4.29 5.00 6.67 4.29 6.67
General equine 47 4.72 9.53 1.00 1.56 4.40 0.01 61.57
Business Model
AAEP respondents owning a limited-service specialty/referral hospital with ambulatory division
had the highest median current ratio of 3.71; in other words, for every $1 of liabilities, they had
$3.71 of assets. The lowest median current ratio among respondents occurred in the full-
service specialty/referral hospital with ambulatory division with a mean current ratio of 1.17
(Table 171).
85 Gaited breeds, equine companion, Quarter Horse racing, Standardbred racing, and ranch or working were omitted because the number of observations did not permit estimation.
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Table 171: Mean Current Ratio of AAEP Respondents by Business Model 86
Business Model Obs. Mean Std. Dev.
1st Quartile
Median 3rd Quartile
Min. Max.
Ambulatory 32 3.91 5.16 0.76 1.53 3.88 0.01 19.81 Ambulatory with Haul-in facility
28 6.71 12.04 1.00 3.04 5.72 0.35 61.57
Specialty/referral hospital -Limited service with ambulatory division
3 6.57 7.43 1.00 3.71 15.00 1.00 15
Specialty/referral hospital -Full service with ambulatory division
7 2.69 3.31 1.00 1.17 3.16 1.00 10
6.7.7 Profit Centers/Activity Centers
Multiple different activities in equine practice are revenue generators for veterinarians, and
include, but are not limited to, dentistry, reproduction, lameness exams, pharmacy, preventive
medicine, integrative therapy, imaging, laboratory tests, surgery, internal medicine, physical
exams, farm calls, and pre-purchase exams. This subsection explores the revenues generated by
AAEP respondents in certain revenue categories.
AAEP respondents were asked what percent of revenue they received from several types of
services that may be offered by their practice. The largest revenue source for AAEP
respondents (14.8 percent) was reported to be preventative medicine, and the smallest (2.9
percent) was pre-purchase exams (Figure 187).
86 Haul-in facility only, l imited service specialty/referral hospital, and full-service specialty/referral hospital and other type of business model were omitted because the number of observations did not permit estimation.
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Figure 187: Equine Practice Profit Centers (Largest to Smallest)
AAEP respondents indicated the percent of revenue received from each of the multiple activity
centers in their practice. The highest mean percent of revenue produced by respondents was
14.8 percent for preventative medicine services, followed by 11.2 percent for pharmacy
services. The smallest sources of revenue reported were surgery (4.2 percent) and pre-purchase
exams (2.9 percent) (Table 172).
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Table 172: Mean Percent Revenue Received from Services Performed by AAEP Respondents
Obs. Mean Std. Dev.
1st Quartile
Median 3rd Quartile
Min. Max.
Preventative Medicine 83 14.8% 9.9% 8% 14% 20% 0% 40% Pharmacy 83 11.2% 8.5% 5% 10% 15% 0% 42% Lameness examinations 83 10.5% 7.3% 5% 10% 15% 0% 35% Imaging 83 9.9% 12.6% 5% 9% 10% 0% 100% Physical examinations 83 9.0% 5.5% 5% 8% 10% 0% 30% Dentistry 83 8.4% 8.6% 3% 7% 10% 0% 60% Laboratory testing 83 7.0% 3.6% 5% 5% 10% 0% 20% Farm Call 83 6.8% 4.3% 3% 5% 10% 0% 19% Internal Medicine 83 5.9% 5.2% 2% 5% 9% 0% 31% Reproductive examinations
83 5.1% 9.4% 0% 2% 5% 0% 50%
Integrative therapies (e.g. acupuncture, chiropractic)
83 4.4% 13.8% 0% 0% 2% 0% 95%
Surgery 83 4.2% 4.7% 1% 3% 5% 0% 25% Pre-purchase exams 83 2.9% 2.3% 1% 3% 4% 0% 10%
When considering the primary equine subsectors in which AAEP respondents practice,
respondents in English performance had the highest mean across sectors in percent revenue in
pharmacy (14.8 percent), imaging (12.2 percent), and pre-purchase exams (3.7 percent).
Respondents in the Thoroughbred racing sectors reported the highest mean percent of revenue
compared to other sectors from internal medicine (12.7 percent), surgery (6.5 percent) and
integrative therapies (17 percent).
The ranch or working respondents’ highest mean percent of revenue was generated by services
in preventative medicine (17.5 percent), dentistry (11.3 percent), lameness examinations (18.8
percent), and physical examinations (10 percent). General equine respondents had the highest
mean in laboratory testing (7.4 percent), reproductive examinations (5.1 percent), and farm
calls (7.3 percent) (Table 173).
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Table 173: Mean Percent Revenue Received from Services Performed by AAEP Respondents by Primary Equine Sector87
Preventative Medicine Dentistry Pharmacy
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
English performance (n=15)
12.4 7.4 1/25 7.9 7.4 0/25 14.8 6.9 5/31
Racing-TB (n=6) 7.3 4.3 0/10 0.0 - - 11.5 8.0 2/22 Ranch or working (n=4) 17.5 10.4 5/30 11.3 2.5 10/15 7.5 5.0 5/15 General equine (n=52) 16.2 10.5 0/40 9.4 9.5 0/60 10.7 9.4 0/42
Laboratory testing
Lameness examinations Physical examinations
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
English performance (n=15)
7.0 2.7 4/12 12.8 8.4 1/25 7.0 4.2 2/20
Racing-TB (n=6) 4.8 4.3 0/10 14.5 11.9 0/35 9.0 8.6 0/25 Ranch or working (n=4)
3.8 1.5 2/5 18.8 10.3 10/30 10.0 4.1 5/15
General equine (n=52) 7.4 3.6 0/20 9.5 5.5 0/25 9.1 5.1 0/25
87 There were no respondents in Quarter Horse racing sector, gaited breeds, reproductive, equine companion, Western performance, and Standardbred racing.
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Imaging Reproductive examinations
Surgery
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
English performance (n=15)
12.2 6.9 2/22 1.8 2.0 0/5 2.3 1.8 0/5
Racing - TB (n=6) 11.0 10.1 0/30 2.5 6.1 0/15 6.5 6.9 0/20 Ranch or working (n=4)
6.5 2.4 5/10 2.8 2.1 0/5 6.3 2.5 5/10
General equine (n=52) 10.3 14.8 0/100 5.1 8.2 0/47 4.3 5.2 0/25
Internal Medicine Pre-purchase exams
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
English performance (n=15) 4.3 3.4 0/13 3.7 2.4 0/8 Racing - TB (n=6) 12.7 11.6 0/31 2.2 2.5 0/5 Ranch or working (n=4) 7.5 2.9 5/10 1.6 1.4 0/3 General equine (n=52) 5.4 4.3 0/15 2.9 2.3 0/10
Farm Call Integrative therapies88
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
English performance (n=15) 7.1 4.1 2/15 6.8 16.0 0/60 Racing - TB (n=6) 1.0 1.3 0/3 17.0 38.3 0/95 Ranch or working (n=4) 3.6 1.6 2/5 3.0 4.8 0/10 General equine (n=52) 7.3 3.9 0/17 2.3 7.3 0/50
Only three types of business models had enough respondents to estimate the mean percentage
of revenue collected from equine services. Respondents in an ambulatory with haul-in facility
reported higher mean percentages compared to the other business models in preventative
medicine (17.3 percent), dentistry (11 percent), lameness (10.5 percent) and physical
examinations (9.7 percent). Respondents in ambulatory practice had higher mean percentages
88 Integrative therapies refers to acupuncture, chiropractic, etc.
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in pharmacy (12.7 percent), laboratory testing (7.4 percent), farm calls (7.9 percent), and
integrative therapies (8.8 percent). Respondents in a full-service specialty/referral hospital with
ambulatory division had a higher mean percent of revenue from services in imaging (14.9
percent), reproductive examinations (8.2 percent), surgery (6.5 percent), internal medicine (7.5
percent), and pre-purchase exams (3.2 percent) compared to the other two business models
(Table 174)
Table 174: Mean Percent Revenue Received from Services Performed by AAEP Respondents by Business Model 89
Preventative Medicine Dentistry Pharmacy
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Ambulatory (n=31) 15.5 10.5 0/40 6.8 6.4 0/23 12.7 8.8 2/42 Ambulatory with Haul-in facility (n=32)
17.3 9.9 1/40 11.0 11.0 0/60 9.5 7.3 2/34
Specialty/referral hospital Full service with ambulatory division (n=17)
9.8 7.3 0/25 6.6 6.6 0/25 12.0 10.5 0/40
Laboratory testing Lameness examinations Physical examinations
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Ambulatory (n=31) 7.4 3.8 0/20 10.3 8.1 0/35 8.5 6.1 0/25 Ambulatory with Haul-in facil ity (n=32)
7.0 3.1 2.5/18 10.5 6.3 1/25 9.7 5.4 5/30
Specialty/referral hospital Full service with ambulatory division (n=17)
6.4 4.3 0/15 9.5 6.9 0/20 8.6 5.4 0/25
89 There were no respondents in l imited service specialty/referral hospital with ambulatory division, full-service specialty/referral hospital with ambulatory division, or other type of business model. Respondents in full- and l imited-service specialty/referral hospital were removed due to only one observation in each group.
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Imaging Reproductive examinations
Surgery
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Mean Std. Dev.
Min/ Max
Ambulatory (n=31) 8.9 9.4 0/50 3.3 8.7 0/47 2.1 1.8 0/5 Ambulatory with Haul-in facil ity (n=32)
8.5 6.8 0/30 5.4 8.4 0/40 4.4 4.4 0/22
Specialty/referral hospital Full service with ambulatory division (n=17)
14.9 22.8 0/100 8.2 12.3 0/50 6.5 6.3 0/25
Farm Call Integrative therapies
Mean Std. Dev.
Min./ Max.
Mean Std. Dev.
Min/ Max
Ambulatory (n=31)
7.9 4.4 0/19 8.8 21.5 0/95
Ambulatory with Haul-in facility (n=32)
6.5 4.1 0/15 2.1 5.1 0/25
Specialty/referral hospital Full service with ambulatory division (n=17)
5.7 3.9 0/15 1.1 1.4 0/5
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SECTION 7: ECONOMY-WIDE IMPACTS OF EQUINE PRACTICES
7.1 IMPLAN SOFTWARE AND INPUT/OUTPUT ANALYSIS
IMPLAN software is an economic tool developed by the Minnesota IMPLAN Group in 1993, and
has since become the most widely used tools for economic analysis. The IMPLAN system
combines data from different sources including the U.S. Department of Commerce, the U.S.
Bureau of Labor Statistics, and other Federal and state government agencies to compute
multipliers that are used to estimate the impacts of exogenous factors on the local economy.
Data in IMPLAN are collected for every geographic region in the United States, from small cities
to the entire nation. The IMPLAN application also facilitates regional analyses where multiple
counties or states are grouped into one entity. The economic impact analysis captures the
economic implications of a new or existing activity, policy or project. The entry of a new
veterinary practice in a community, for example, sparks change in the local economy:
Construction of a veterinary facility requires the participation of a variety of skilled construction
workers, and the staff needed to operate the facility will spend part of their income in local
markets.
The IMPLAN system estimates the multiplier effects of changes in final demand for one sector
on all other industries within a local area and provides the results in terms of total changes in
employment, income, output and value added.
In an economic impact analysis, three different results are presented: direct effects, indirect
effects and induced effects. Putting the results in the context of an equine veterinary practice,
the direct effect refers to the impacts created directly by the practice’s activity. For example,
consider a new equine veterinary practice that opens in Upperville, Va., employs six workers
and records sales of $700,000. The direct impact of this practice on Upperville’s economy is
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$700,000, indicating that the total gross output of all businesses in the community has
increased by $700,000. In terms of impact on employment, the direct effect of the equine
veterinary facility on local employment will be the creation of six new jobs.
The indirect effect refers to those effects generated by the producers of intermediate goods
and services purchased by the practice. Suppose that Upperville already has one equine
veterinary practice that purchases medical supplies from a local medical supplies manufacturer.
The entry of the new practice increases the demand for medical supplies and requires the local
manufacturer to increase its production in order to meet the new demand of the new
veterinary practice. An increase in the number of employees at the medical supplies
manufacturer due to the increased demand is recorded as an indirect effect of the new equine
veterinary practice. In the same way, the increase in the total gross output will be recorded as
the indirect effect of the new equine veterinary practice on gross output. Other industries
affected by the new veterinary practice and part of the indirect effect may include utilities,
construction, landscaping, delivery services and other businesses that provide services to the
new practice.
Induced effect refers to the subsequent spending in the local economy made by the employees
of the new equine veterinary practice and those of the intermediate input suppliers.
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7.2 RESULTS AND DISCUSSION
An economic impact analysis was performed for each of the 10 regions in the United States.
Using the national average number of veterinarians from the AVMA membership database and
the percentage of equine veterinarians in the United States reported in the 2017 AVMA Report
on The Market for Veterinarians, an approximate number of equine veterinarians and
employees 90 was established. By taking the mean practice revenue of each region91 and
multiplying it by the number of practices in each region92, the total regional and national
industry output was calculated. Due to an inadequate amount of purchasing or expenditure
data for each of these regions, the expenditure pattern was considered to be the same for
each. That is, it was assumed that the production of a veterinary service by any of these regions
required the same set of inputs. The average output per region and the mean number of
employees was used to determine the economic impact of the entry of one additional practice
in the study area. Once the impact per practice was determined, the impact for the entire
industry was aggregated by multiplying the impact of an individual practice by the total number
of establishments in the area.
7.2.1 Economic Effect of Equine Veterinary Medicine on Employment
The employment effects indicated that at the national level the equine veterinary industry
generates an estimated 18,658 direct jobs, supports 5,497 indirect jobs, and induces 8,925
other jobs for an estimated total of 33,080 jobs for the entire economy (Table 175).
90 Using the IMPLAN 2013 (sector 459) data, a 4:1 ratio was established (four employees for every one veterinarian) 91 Source: 2016 AVMA-AAEP Survey of Equine Practitioners 92 Number derived from IMPLAN 2013 (sector 459) data and 2016 AVMA-AAEP Survey of Equine Practitioners data.
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Table 175: Economic Impacts of Equine Veterinary Practice on Employment
U.S. Region Direct Effect Indirect Effect Induced Effect Total Effect
Region 0 1,462.8 394.0 748.4 2,605.2 Region 1 1,570.0 460.3 788.7 2,819.0 Region 2 1,977.2 179.4 478.2 2,634.8 Region 3 2,701.0 1,158.4 1,063.8 4,923.2 Region 4 1,915.2 1,120.6 1,567.6 4,603.4 Region 5 1,179.0 282.0 597.7 2,058.7 Region 6 1,354.2 14.8 292.8 1,661.8 Region 7 2,127.5 1,033.5 1,367.4 4,528.4 Region 8 1,416.1 555.6 853.7 2,825.4 Region 9 2,954.9 298.2 1,167.0 4,420.1
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7.2.2 Economic Effect of Equine Veterinary Medicine on Labor Income
The total direct economic impact on employee compensation and proprietor income at a
national level was estimated at $1,142,584,231. This value corresponds to the total dollar
amount invested by equine veterinary practice owners into the national economy as payroll
expenditures and owner’s share. The total indirect effects were estimated at $300,947,279 and
represent the total additional investment in labor income of all other necessary industries that
have had to vary their production as a result of the existence of the veterinary industry. The
induced effects at the national level were equivalent to $431,782,923. The aggregated effects
were estimated at $1,875,314,433 for the U.S. economy (Table 176).
Table 176: Economic Impacts of Equine Veterinary Practice on Labor Income
U.S. Region Direct Effect Indirect Effect Induced Effect Total Effect
Region 0 $107,135,531 $26,873,590 $42,275,111 $176,284,232 Region 1 $121,572,871 $32,043,109 $44,563,256 $198,179,235 Region 2 $69,478,706 $9,782,085 $22,174,001 $101,434,792 Region 3 $93,032,841 $56,721,817 $47,939,615 $197,694,273 Region 4 $172,980,432 $57,842,377 $69,183,989 $300,006,797 Region 5 $78,533,853 $14,659,019 $26,645,570 $119,838,442 Region 6 $45,267,474 $882,528 $14,172,059 $60,322,061 Region 7 $167,835,924 $55,330,748 $63,981,063 $287,147,734 Region 8 $103,976,992 $27,749,094 $38,505,949 $170,232,034 Region 9 $182,769,608 $19,062,913 $62,342,311 $264,174,832
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7.2.3 Economic Effect of Equine Veterinary Medicine on Value Added
The value added represents the increase in the gross revenue of production generated by an
industry. The direct contributions of equine practice to the gross revenue of production by
region varied from $145,781,473 to $512,941,638. At the national level, the direct effects were
estimated at $2,673,924,754. The total indirect effects were estimated at $538,244,792. The
induced effects at the national level were equivalent to $760,616,080. The aggregated effects
were estimated at $3,972,785,626 for the U.S. economy (Table 177).
Table 177: Economic Impacts of Equine Veterinary Practice on Total Value Added
U.S. Region Direct Effect Indirect Effect Induced Effect Total Effect
Region 0 $192,107,833 $47,496,412 $71,400,763 $311,005,008 Region 1 $218,988,387 $57,272,131 $78,029,932 $354,290,450 Region 2 $269,439,598 $18,197,764 $39,663,267 $327,300,629 Region 3 $512,941,638 $99,027,701 $83,755,460 $695,724,799 Region 4 $335,823,352 $106,939,381 $124,701,161 $567,463,894 Region 5 $145,781,473 $25,416,201 $46,749,008 $217,946,683 Region 6 $163,644,681 $1,505,387 $24,807,336 $189,957,404 Region 7 $322,028,635 $96,578,535 $112,568,302 $531,175,472 Region 8 $195,251,345 $49,737,127 $69,348,292 $314,336,764 Region 9 $317,917,811 $36,074,152 $109,592,560 $463,584,523
7.2.4 Economic Effect of Equine Veterinary Medicine Output
The direct effect represents the gross sales of the equine veterinary industry. In other words,
the direct effect represents the total dollar value of the equine veterinary services sold to
consumers. In total, the direct effect of equine veterinary practices was estimated at
$3,553,116,133. The veterinary industry uses inputs from other industries, and the total value
of the products of these suppliers is captured in the indirect effect. The total indirect and
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induced effects at the national level were $943,888,813 and $1,315,166,676, respectively. The
aggregated effect for the entire economy was estimated at nearly $5,812,171,621 (Table 178).
Table 178: Economic Impacts of Equine Veterinary Practice on Output
U.S. Region Direct Effect Indirect Effect Induced Effect Total Effect
Region 0 $262,008,543 $78,434,418 $116,062,838 $456,505,799 Region 1 $308,804,240 $94,086,615 $125,394,356 $528,285,211 Region 2 $290,568,202 $31,168,536 $68,032,449 $389,769,187 Region 3 $678,145,171 $176,666,976 $148,425,036 $1,003,237,183 Region 4 $536,168,363 $191,252,305 $222,323,986 $949,744,655 Region 5 $195,381,806 $45,964,320 $83,609,278 $324,955,404 Region 6 $158,838,853 $2,657,214 $42,964,502 $204,460,569 Region 7 $487,289,168 $172,133,495 $199,723,282 $859,145,946 Region 8 $280,534,671 $89,747,156 $121,733,224 $492,015,051 Region 9 $355,377,115 $61,777,778 $186,897,725 $604,052,618
7.2.5 Economic Effect of Equine Veterinary Medicine on Tax
Veterinary practices pay tax to the local, state and Federal government through different
channels: tax on employee and proprietor compensation, tax on production and imports,
service tax, and corporate tax. Calculations estimated the total value of the tax money received
from equine veterinary practices in each district. In total, states and local governments received
$2,486,913 in payroll tax, $160,410,269 in production and imports tax, $47,915,109 in service
tax paid by consumers, and $19,327,666 in corporate tax (Table 179). The Federal government
received $143,692,453, $20,377,063, $142,707,217, and $136,678,453 from taxes on employee
compensation, production and imports, household service expenditures and corporate
earnings, respectively. In addition, the Federal government received an estimated $26,491,736
as tax on proprietor income. Thus, the equine veterinary industry paid an estimated
$700,086,878 to the local, state and Federal governments (Table 179 and Table 180).
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Table 179: Economic Impacts of Equine Veterinary Practice on State and Local Tax Revenues
Employee Compensation
Tax on Production and Imports
Households Corporations
Region 0 $159,425 $10,558,946 $5,099,312 $1,843,288 Region 1 $175,828 $12,848,247 $7,822,215 $3,465,811 Region 2 $139,402 $15,111,932 $2,952,035 $1,739,269 Region 3 $273,273 $37,856,359 $2,585,282 $4,509,770 Region 4 $549,576 $20,774,416 $8,358,319 $1,616,159 Region 5 $139,395 $7,352,952 $3,530,271 $1,112,637 Region 6 $115,373 $8,971,839 $1,656,771 $1,578,503 Region 7 $281,505 $20,087,594 $3,416,893 $543,597 Region 8 $258,242 $11,898,546 $3,561,643 $888,895 Region 9 $394,894 $14,949,438 $8,932,367 $2,029,738
Table 180: Economic Impacts of Equine Veterinary Practice on Federal Tax Revenues
Employee Compensation
Proprietor Income
Tax on Production and Imports
Households Corporations
Region 0 $12,164,868 $2,875,071 $1,119,936 $16,351,185 $8,775,469 Region 1 $13,031,710 $3,309,520 $1,442,104 $16,659,202 $10,115,165 Region 2 $10,412,993 $600,869 $2,184,336 $6,808,909 $14,872,715 Region 3 $19,502,708 $1,496,052 $4,850,202 $13,915,673 $32,458,454 Region 4 $27,912,884 $2,809,188 $2,704,637 $19,382,412 $17,398,409 Region 5 $8,097,176 $2,203,582 $791,642 $8,640,967 $6,416,030 Region 6 $5,885,178 $367,570 $1,062,320 $4,449,491 $8,529,286 Region 7 $17,653,846 $5,360,433 $2,636,990 $22,710,023 $15,783,413 Region 8 $11,351,145 $3,062,334 $1,650,084 $12,255,397 $9,310,667 Region 9 $17,679,944 $4,407,118 $1,934,812 $21,533,958 $13,018,845
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RECOGNITION OF AUTHORS
Charlotte R. Hansen M.S. AVMA Veterinary Economics Division Statistical Analyst Matthew Salois Ph.D. AVMA Director of Veterinary Economics Bridgette Bain Ph.D. AVMA Veterinary Economics Division, Assistant Director of Analytics Frederic Ouedraogo Ph.D. AVMA Veterinary Economics Division Assistant Director of Economics Barbara Dutton Marketing & Communications Senior Content Writer Special thanks to the AVMA AAEP Task Force Team for their insight and assistance in preparation of this report. Amy L. Grice VMD, MBA Chair of AVMA AAEP Economic Impact Survey Task Force Ann Dwyer DVM AVMA AAEP Economic Impact Survey Task Force Member Kathy Anderson, DVM AVMA AAEP Economic Impact Survey Task Force Member Reynolds Cowles DVM AVMA AAEP Economic Impact Survey Task Force Member
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