HEALTH CARE EXPENDITURES ASSOCIATED WITH · PDF filehealth care expenditures associated with...
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HEALTH CARE EXPENDITURES
ASSOCIATED WITH PERSISTENT
EMERGENCY DEPARTMENT USE:
A MULTI-STATE ANALYSIS OF
MEDICAID BENEFICIARIES
Presented by –
Parul Agarwal, PhD MPH1,2
Thomas K Bias, PhD3
Usha Sambamoorthi, PhD1
1 West Virginia University School of Pharmacy, Morgantown, WV 2 Institute of Healthcare Delivery Science, Mount Sinai Health Systems, NY 3 West Virginia University School of Public Health, Morgantown, WV
BACKGROUND
• Emergency Medical Treatment and Labor Act
• Changing role of Emergency Department (ED)
• ED use by
- Uninsured
- Insured
• Used for emergent and non-emergent conditions1,2
• ED use results in3
- Fragmented care
- Higher healthcare expenditures
- Reduced quality of care
2
Background
▶ Increased ED visits in past two decades - 32% increase from 1997 to 20074
- More than 130 million ED visits in 20115
▶ Out of 354 million visits for acute care conditions that could have
been managed by primary care providers one-third treated in EDs6
▶ Many individuals visit ED repeatedly7
▶ Provision of treatment in EDs is expensive as compared to other
settings8
3
Date of download: 12/12/2014 Copyright © 2014 American Medical
Association. All rights reserved.
From: Trends and Characteristics of US Emergency Department Visits, 1997-2007
JAMA. 2010;304(6):664-670. doi:10.1001/jama.2010.1112
ED indicates emergency department. Error bars indicate 95% confidence intervals.
Figure Legend:
ED visits increased
from 9.6 million to
17.7 million among
Medicaid enrollees
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Background
▶ Patient- and county-level factors are associated with increased ED
visits9,10
▶ ED use by Medicaid beneficiaries received policy attention11
▶ Post Affordable Care Act more individuals enrolled in the Medicaid
program12
▶ Expanded health insurance coverage without corresponding
increase in the number of primary care providers may impact ED use
▶ Previous expansion of health insurance coverage revealed mixed findings
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Study Rationale
▶ Frequent ED use for non-urgent and preventable conditions1,2 ▶ Frequent ED use may be persistent with some individuals visiting
EDs frequently every year7
▶ Understanding persistent ED use important for Medicaid ▶ Comprehensive research on subgroup differences in persistent ED
users is lacking ▶ No study has examined the association between persistent ED use
and healthcare expenditures excluding costs of ED visits
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Objective
Examine the patient- and county-level factors associated with
persistent ED use and its impact on healthcare expenditures among
adult fee-for-service (FFS) Medicaid beneficiaries.
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Methods
Study Design
▶ Retrospective observational study design
▶ Data from MD, OH, and WV for year 2009 & 2010
▶ Index (calendar year 2009) and follow-up period (calendar year 2010)
▶ Persistent ED use was based on ED visits measured in both years
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Index (2009) Follow-up (2010)
Independent variables Dependent variable: Total
healthcare expenditures
Persistent ED use
Methods
Study Population
▶ 22-64 years old
▶ Alive
▶ Men and non-pregnant women
▶ Not Medicare eligible
▶ FFS continuous enrollees
Data Sources
▶ Medicaid Analytic eXtract files
▶ Area health resource file
▶ County health rankings data
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Methods
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Medicaid
Analytic
eXtract (MAX)
Files
Examples of patient-level information
Personal
Summary File
Demographics, Medicaid eligibility, county federal
information processing standard (FIPS) codes,
Medicaid managed care enrollment, and Medicare
eligibility status
Inpatient
Claims File
Hospital stays, dates of service, Medicaid payment,
and the ICD-9-CM diagnosis and procedure codes
Other Therapy
Claims File
Dates of service, types of service, Medicaid
payment, ICD-9-CM, and CPT codes
Prescription
Drugs Claims
File
Date of prescription filled, days supplied, and
national drug code (NDC), Medicaid payment
Methods
11
Other Data
Sources
Examples of county-level information
Area Health
Resource File
(AHRF)
Percent with college education, health
professional shortage area, federally qualified
health centers per 100,000 population and urgent
care centers per 100,000 population, FIPS codes
County Health
Ranking
Obesity rate
All datasets linked together using Federal Information Processing Standard (FIPS)
codes.
Methods Dependent Variable 1) Persistent ED users versus Non-users
– No consensus on the number of ED visits that define frequent ED
users
– Commonly used definition (i.e. 4 or more ED visits annually)
2) Total healthcare expenditures
– Payments made by Medicaid for outpatient, inpatient, and
prescription drugs utilization
– ED expenditures were excluded
– Expenditures expressed in 2010 US dollars
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Methods
Independent Variables: Patient-level
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Variables Categories
Age 22-34, 35-44, 45-54, 55-64 years
Gender Female, male
Race/Ethnicity Whites, African Americans, Hispanics, Other Races
Medicaid
Eligibility
Cash eligibility, No cash eligibility, Medical eligibility,
No medical eligibility
Primary care use None, fragmented, continuous
Poly-pharmacy Yes, No
Complex chronic
illness
Presence of physical health conditions, presence of
mental health conditions, presence of both physical
and mental health conditions, none
Tobacco use Yes tobacco use, No tobacco use
Metro Metro, non-metro
Methods
Independent Variables: County-level
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Variables Categories
Education County-level education rate
Unemployment County-level unemployment rate
Obesity County-level obesity rate
Health Professional
Shortage Area
None, partial, complete shortage
Hospitals with EDs Number of hospitals with EDs/100,000 population
Hospitals with
psychiatric emergency
services
Number of hospitals with psychiatric emergency
services/100,000 population
Rural health clinics Number of rural health clinics/100,000 population
Federally qualified
health centers
Number of federally qualified health centers/100,000
population
Community mental
health centers
Number of community mental health centers/100,000
population
Urgent care centers Number of urgent care centers/100,000 population
Methods
Statistical Analyses
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Define Methods
Characteristics of the study
population
Frequencies and percentages
Unadjusted differences between
persistent ED users vs non-users
Chi-square tests of association
Patient- and county-level factors
associated with persistent ED use
Logistic regression
Association between healthcare
expenditures and persistent ED
use
Unadjusted and adjusted
generalized linear models (GLM)
with log link function and gamma
distribution
Characteristics of persistent ED users
and inpatient use (N = 22,252)
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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Persistent EDusers
Non-users
55.60%
2%
Co
lum
n p
erc
en
tage
s
0102030405060708090
100
Prim
ary
Ca
re u
se
Fra
gem
en
ted
Contin
uou
s
Com
ple
x c
hro
nic
illn
ess
PH
C
MH
C
PH
C &
MH
C
None
Poly
-ph
arm
acy
Yes
No
Toba
cco
Use
Yes
No
28.7
13.2 20.1 17.6
41.7
6.7
53.4
17.2
55.1
21.2
Row
pe
rcen
tage
s
Patient-level Factors
Factors associated with persistent ED
use
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1.67
7.65
4.36 3.97
1.08 1.2 0.9
0
1
2
3
4
5
6
7
8
9
10
Ad
juste
d O
dd
s R
ati
os
Patient- and County-level Factors
Mean Expenditures and Ratio of Means
by Type of Healthcare Expenditures
Non-users
(N = 17,107)
Persistent ED users
(N = 5,145)
Type of
Expenditures Mean ($) SE Mean ($) SE
Ratio of
means
Total*** 17,731.1 218.6 42,229.2 758.1 2.4
Outpatient*** 13,205.8 209.0 21,277.9 455.9 1.6
Prescription
Drugs*** 4,314.4 46.6 7,952.6 184.4 1.8
In Users
Prescription
Drugs*** 4,582.8 48.8 7,993.0 185.2 1.7
Inpatient*** 10,368.4 764.5 22,747.9 700.2 2.2
ED expenditures excluded from total and outpatient 18
Note: Asterisks represent significant group differences between persistent ED users and non-users based on IPTW
adjusted t-tests. SE = standard errors
*** p< .001; ** .001 < p < .01; * .01 < p < .05
Generalized Linear Models with Log Link Function
By Type of Expenditures
Type of
Expenditures
Intercept
(SE)
Persistent ED
Use -Beta
(SE) Change ($)
Total
(without ED)
8.68***
(0.62)
0.78***
(0.06) 6,951.84
Outpatient
(without ED)
7.59***
(0.72)
0.77***
(0.06) 2.294.38
Prescription Drugs
7.61***
(0.35)
0.13***
(0.15) 280.19
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Note: SE = standard errors
*** p< .001; ** .001 < p < .01; * .01 < p < .05
Policy Implications
▶ Critical to explore ways to triage patients to other settings such as urgent care centers
▶ Need for policies, programs, and interventions that can meet the healthcare needs of persistent ED users
▶ One can speculate that coordinated care models may reduce persistent ED use and healthcare expenditures
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Limitations & Strengths
Limitations
▶ Administrative claims data are for billing purposes
▶ Could not measure some patient-level factors such as obesity or reasons for using ED
Strengths
▶ Track repeated ED visits by an individual
▶ Differentiate between persistent ED users and non-users
▶ Information available on clinical diagnosis
▶ Availability of payment amount
▶ Use of county-level factors
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Acknowledgements
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THANK YOU !
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