BMJ Open · Mahmoud, Mansour Ahmed, Yusuf; King Saud University, Medication Safety Research Chair...

For peer review only

A Prospective Multicenter Study of the Incidence of Adverse Drug Events in Saudi Arabia Hospitals: The (ADESA) Study

Journal: BMJ Open

Manuscript ID bmjopen-2015-010831

Article Type: Research

Date Submitted by the Author: 15-Dec-2015

Complete List of Authors: Aljadhey, Hisham; College of Pharmacy, King Saud University, Medication Safety Research Chair Mahmoud, Mansour Ahmed, Yusuf; King Saud University, Medication Safety Research Chair Sultana, Razia; Specialized Medical Center Hospital Zouein, Salah; Specialized Medical Center Hospital Alshanawani, Sulafa ; King Saud Medical City Mayet, Ahmed; King Khaled University Hospital

Alshaikh, Mashael; King Khaled University Hospital Kalagi, Nora; King Saud University, Medication Safety Research Chair altawil, esra; King Khaled University Hospital El Kinge, Abdul Rahman ; Specialized Medical Center Hospital Arwadi, Abdulmajid; Specialized Medical Center Hospital Alyahya, Maha; King Salman Hospital Murray, Michael; Purdue University and Regenstrief Institute Bates, David; Division of General Medicine

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Pharmacology and therapeutics, General practice / Family practice,

Intensive care, Research methods, Surgery

Keywords: Adverse Drug Events (ADEs), prospective cohort study, Saudi Arabia

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

BMJ Open on D

ecember 29, 2020 by guest. P

rotected by copyright.http://bm

jopen.bmj.com

/B

MJ O

pen: first published as 10.1136/bmjopen-2015-010831 on 12 July 2016. D

ownloaded from

http://bmjopen.bmj.com/


1


Hisham Aljadhey1, Mansour A Mahmoud1, Yusuf Ahmed1, Razia Sultana2, Salah Zouein2, Sulafah Alshanawani3, Ahmed Mayet4, Mashael Alshaikh4, Nora Kalagi1, Esraa Al Tawil4, Abdul Rahman Agha El Kinge2, Abdulmajid Arwadi2, Maha Alyahya5, Michael

D Murray6, David Bates7

1 Medication Safety Research Chair, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia

2Specialized Medical Center, Riyadh, Saudi Arabia

3King Saud Medical City, Riyadh, Saudi Arabia

4King Khaled University Hospital, Riyadh, Saudi Arabia

5King Salman Hospital, Riyadh, Saudi Arabia

6Purdue University and Regenstrief Institute, Indianapolis, United States

7Harvard Medical School and Brigham and Women's Hospital, Boston, United States.

Number of words: 2413

Corresponding author: Hisham Aljadhey, Pharm D, PhD Director of Medication Safety Research Chair Dean, College of Pharmacy, King Saud University P.O.Box 2475, Riyadh 11451, Saudi Arabia Email: [email protected] Phone: +966 530039008

Page 1 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem

ber 29, 2020 by guest. Protected by copyright.

http://bmjopen.bm

j.com/

BM

J Open: first published as 10.1136/bm

jopen-2015-010831 on 12 July 2016. Dow

nloaded from



2

ABSRACT

Background: Few studies have investigated the epidemiology of adverse drug events

(ADEs) in developing countries.

Objective: To determine the incidence of ADEs and assess their severity and

preventability in four Saudi hospitals which represent public, private, teaching, small,

and large hospitals.

Method: We performed a prospective cohort study of patients admitted to medical,

surgical and intensive care units of four hospitals. These hospitals are a 900 beds tertiary

teaching hospital, a 400 beds private hospital, a 1400 beds large government hospital and a

350 beds small government hospital. Incidents were collected by pharmacists and

reviewed by independent clinicians. Reviewers classified the identified incidents into

ADEs, potential ADEs and medication errors and determined their severity and

preventability.

Result: We followed 4041 patients from admission to discharge. Of those 3985

patients had complete data and were analyzed. The mean age of patients in the

analyzed cohort was 43 (±19.5) years. A total of 1676 incidents were identified by

pharmacists during medical chart review. Clinicians reviewers accepted 1531(91.4%) of

the incidents found by pharmacists (245 ADEs, 677 PADEs and 609 medication errors

with low risk to cause harm). The incidence of ADEs was 6.1 (95% CI, 5.4-6.9) per 100

admissions and 7.9 (95% CI, 6.9 – 8.9) per 1000 patient days. The occurrence of ADEs

was most common in the intensive care units 149 (60.8%) followed by medical

67(27.3%) and surgical units 29(11.8%). In terms of severity, 129 (52.7%) of the ADEs

Page 2 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



3

were significance, 91 (37.1%) were serious, 22 (9%) were life-threatening and 3 (1.2%)

were fatal.

Conclusion: We found that ADEs were common in Saudi hospitals, especially in the

ICUs, and they caused significant morbidity and mortality. Future studies should focus

on investigating the root causes of ADEs at the prescribing stage and development and

testing of interventions to minimize harm from medications.

Key words: Adverse Drug Events (ADEs), prospective cohort study, Saudi Arabia

Page 3 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



4

INTRODUCTION

Adverse drug events (ADEs) are major cause of morbidity, mortality, extra

healthcare costs and hospitalization (1-3). An ADE is defined as an injury occurring from

the use of drugs (4). They are largely preventable and occur mostly at the prescribing

stage of medication use process (2, 4, 5). The incidence of ADEs reported in the

literature vary significantly between countries. This is largely because of the differences

in practices, training, study methodology and patient safety initiatives among the

particular countries settings. Early in 1995 Bates et al from the USA reported an

incidence of 6.5 per 100 admissions (2) while using the same methods a study in

Japan reported an incidence of 17 per 100 admissions (4). In Saudi Arabia one single

hospital study reported an incidence of 8.5 per 100 admissions (5) and a cross-sectional

study in morocco reported an incidence of 4.2 per 100 admissions (6). A recent

international study using hospital datasets estimated the prevalence of ADEs to be

3.2% in England, 4.8% in Germany and 5.6% in the USA (7). It is important to mention

that the incidence of preventable ADEs was estimated by a population based study to

be 13.8 per 1000 person-years(8).

Despite the evidence that ADEs are common and threatening patient life, little

attempts had been made in Saudi Arabia to detect and estimate the incidence of ADEs

in hospitalized patients. Such lack of studies will hinder the designing of prevention

strategies and improve patient safety. To date, one prospective chart review study had

been conducted in a single teaching hospital in the Saudi settings (5). Therefore we

thought to study this issue with a larger sample from different hospitals which might

have different practices or strategies of managing patients to come up with a better

Page 4 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



5

estimate of ADEs. The objective of our study was to estimate the incidence of ADEs in

Saudi hospitals and determine their severity and preventability.

Page 5 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



6

METHODS

Study design and patient population

The Adverse Drug Events in Saudi Arabia (ADESA) study was a prospective cohort

study involving four hospitals from Riyadh, Saudi Arabia. These hospitals are a 900 beds

tertiary teaching hospital, a 400 beds private hospital, a 1400 beds large government hospital

and a 350 beds small government hospital. We randomly selected medical, surgical and

intensive care units (ICUs) from these hospitals and excluded obstetrics and pediatric units

because of the minimum use of medications in these units. Further inclusion was patients older

than 12 years of age admitted to these units during the four month study period and patients

admitted for more than 24 hours. None of these hospitals had electronic medical records or

decision support system. All the hospitals utilized paper-based system where physician notes

including prescribed medications and nursing notes including daily administered medications

are handwritten and kept in patient files. Whereas, medication orders are sent to inpatient

pharmacy and dispensed through the unit dose systems.

Definitions

We defined ADE as an injury caused by a medication and may be preventable or not

preventable (2, 9). The non-preventable ADEs are also known as adverse drug reactions

defined by the World Health Organization as “a response to a drug which is noxious and

unintended, and which occurs at doses used in man for prophylaxis, diagnosis, or therapy of

disease, or for the modifications of physiological function”(10). Preventable ADEs are those who

result from medication errors at any stage of medication use process. A potential ADEs is an

error that carries the risk of causing injury related to the use of a medication but harm did not

occur(9).

Page 6 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



7

Data collection and classification of incidents

The method used to collect data was described in details elsewhere (5) In summary, data

was collected daily by trained clinical pharmacists. In addition all nurses working in the particular

units were invited to attend a monthly in-service to increase their awareness about ADEs

reporting. The pharmacists reviewed patients’ medical charts of all admitted patients in each of

the participating units to report demographic characteristics of patients including comorbidity

and number of medications. When incidents found the pharmacists wrote a detailed description

of the incidents and patient history related to the incidents.

Two independent clinicians, who were not involved in the data collection process, were

provided with a study manual that contains study terminology and a guide on the assessment of

the severity and preventability of an incident with example of incidents and their severity

classifications(2). The severity of the incidents was categorized as significant, serious, life

threatening or fatal. The study manual served as a guide for the reviewers to independently

review the incidents and decide on inclusion of incidents and further classify them as ADEs,

potential ADEs or ME and assess their severity and preventability. In case of disagreement

between physicians the final decision was confirmed through discussion between both

reviewers. The primary outcomes of this study were incidence of ADEs, potential ADEs and

medication errors as defined in the earlier section of methodology. The secondary outcomes

were the severity of these events, their preventability, and the associated risk factors.

Data Analysis:

We calculated the overall incidence per 100 admissions and crude rate per 1000 patient

days with 95% Confidence Interval (CI). In addition the incidence was calculated by hospital and

by units. Continuous variables are presented as mean ± standard deviation (SD) and

categorical variables as number and percentages. The Inter-rater reliability was assessed using

Page 7 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



8

kappa statistic for assessment of the presence of an ADE and its preventability and severity. To

evaluate the univariate association of potential risk factors with ADEs, we used univariate

logistic regression. Variables which were found to be significance in the univariate analysis were

included in the multivariate logistic regression final model. Statistical analyses were conducted

using the Statistical Package for Social Science (SPSS) software (SPSS Inc., Chicago, IL),

version 22.0.

Page 8 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



9

RESULTS

Demographic Characteristics of the patients

Medical charts of 4,041 patients were reviewed by clinical pharmacists. Complete

data of 3,985 patients were analyzed (Table 1). The length of hospital stay for these

patients was 30,996 days. The study was conducted in four hospitals in Riyadh, Saudi

Arabia (977 patients from a teaching Hospital, 2033 patients from a private Hospital;

683 patients from large government Hospital; and 292 patients from a small government

hospital). Majority of the patients were male 2102 (52.7%) (Table1). Patients were

admitted to three different services (Medicine; 1352 patients, surgery; 1771 patients and

Intensive Care Units; 862 patients). The mean length of hospital stay was 8.1 ± 10.2

days and the mean age of patient was 43.4 ± 19.0 years (Table 2).

Incidents review and classification

Chart review by pharmacist in the four hospitals identified 1676 cases. The

physician reviewed these cases and finally accepted 1531 (91.3%) of the cases. These

cases were classified as 609 (39.8%) medication errors with low risk of harm, 677

(44.2%) potential adverse drug events (PADEs) and 245 (16%) cases were judged to

be ADEs. Among ADEs 85 (34.7%) were preventable and 160 (65.3%) were judged to

be non-preventable (Table 2). Majority of the preventable ADEs occurred in the

prescribing stage 75 (88.2%) followed by administering 7(8.2%), dispensing 2(2.4% and

monitoring 1(1.2%). One hundred twenty nine (52.7%) of all ADEs were significant, 91

(37.1%) were serious, 22 (9%) were life-threatening and 3 (1.2%) were fatal. Of the 85

preventable ADEs 36 (42.4%) were significant, 38 (44.7%) were serious, 10 (11.9%)

were life-threatening and 1 (1.2%) was fatal. Among potential ADEs 213 (31.9%) were

Page 9 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



10

intercepted by the medical staff. Regarding severity of potential ADEs 383 (56.6%) were

significant, 271 (40%) were serious and 23 (3.4%) were life-threatening.

Overall incidence of ADEs and Medication Errors

The incidence of ADEs per 100 admissions was 6.1(95% CI 5.4 – 6.9), and the

incidence per 1000 patient days was 7.9(95% 6.9 – 8.9) (Table 2). The incidence of

potential ADEs was 16.9 (95% CI 15.7 – 18.3) per 100 admissions and 21.8 (95% CI

20.2 – 23.5) per 1000 patient days. The incidence of medication Errors with low risk to

cause harm was 15.3 (95% CI 14.1 – 16.5) per 100 admissions and 19.6 (95% CI 18.7

– 21.2) per 1000 patient days. The incidence of preventable ADEs was 2.1(95% CI 1.7

– 2.6) per 100 admissions and 2.7 (95% CI 2.2 – 3.3) per 1000 patient days. The

incidence of not preventable ADEs was 4.0 (95% CI 3.4 – 4.6) per 100 admissions and

5.1 (95% CI 4.4 – 6.0) per 1000 patient days. The incidence of intercepted potential

ADEs was 5.3 (95% CI 4.6 – 6.1) per 100 admissions and 6.8 (95% CI 5.9 – 7.8) per

1000 patient days (Table 2). Incidents most commonly occurred in the prescribing stage

1288 (84.1%) followed by dispensing stage 69 (4.5%) and administering 43 (2.8%).

Table 3 shows the distribution of incidents among the four hospitals. The incidence of

ADEs was most common in the small government hospital 96 (6.3%) while the

incidence of PADEs was predominantly higher in private hospital 367 (23.9%).

Medication errors were mostly seen in private hospital 367 (23.9%).

Classification of the 1531 Incidents by service

The incidence of ADEs was higher in the ICUs 13.7(95% CI 11.6-16.1) per 1000

patients days and 17.4(95% CI 14.7-20.3) per 100 admissions followed by the medical

Page 10 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



11

units 6.1(95% CI 4.7-7.7) per 1000 patients days and 4.8(95% CI 3.8-6.1) per 100

admissions (Table 4).

Agreement of physician’s reviewers on the classification of the incidents

The kappa value for the presence of ADEs was 0.71, for the presence of

medication errors it was 0.67 and for the presence of potential ADEs was 0.60. The

kappa value for preventability of ADEs was 0.68 (definitely or probably preventable vs.

definitely or probably not preventable). For the severity of ADEs the kappa score was

0.74 (fatal vs. significant, serious or life-threatening), 0.63 (Life-threatening vs.

significant, serious or fatal), 0.53 (Significant vs. serious, life-threatening or fatal), 0.48

(Serious vs. life-threatening or fatal).

Factors Associated with ADEs

Factors significantly associated with ADEs included older age; (OR, 1.013;

95%CI, 1.004 – 1.021) more number of medications (OR, 1.070; 95%CI, 1.018 – 1.125),

greater length of hospital stay (OR, 1.026; 95%CI, 1.016 – 1.036) and admission to the

ICUs and medicine units respectively (OR, 3.131; 95%CI, 1.937 – 5.063) and (OR,

1.729; 95%CI, 1.086 – 2.755) (Table 6).

Page 11 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



12

DISCUSSION

In this study we evaluated the incidence of ADEs and found that ADEs were

common with one third caused by medication errors and therefore were judged to be

preventable. Errors resulting from preventable ADEs were most common in the

prescribing stage followed by dispensing and administration. Majority of the preventable

ADEs were judged to be serious. The incidence of ADEs reported in our study was

similar to previous studies (2, 5). However, a higher incidence was reported in Japan

(4). The differences between our study result and this study could be the longer length

of hospital stay in Japan and differences in healthcare systems between both countries.

The similarity between our findings and the US study could be because of the similarity

in the healthcare systems between both countries.

We included 3985 patients and found 245 ADEs of which 35% were judged to be

preventable. Gurwitz and colleagues (8) identified 546 ADEs during 2403 nursing home

residence admissions and reported that 51% of the observed ADEs were preventable.

Bates et al (2) identified incidence of ADEs in 4031patients and found 247 ADEs of

which 28% were judged preventable with more serious ADEs to be preventable. In 2009

hug et al(11) assessed the occurrence of ADEs in 1200 patient from six community

hospitals and identified 180 ADEs of which 75% were preventable. Recently a

multicenter cohort study of 3459 patients identified 1010 ADEs and found that 14% of

the identified ADEs were preventable (4).

Page 12 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



13

Regarding potential ADEs we noticed only one third of the events were

intercepted. It is noteworthy to highlight that three of the four hospitals had clinical

pharmacists monitoring patient treatments and most of the intercepted potential ADEs

were in those hospitals.

Our study revealed that ADEs were associated with admission to ICUs and older

age. Consistent with our results other studies also reported that admission to ICUs (4,

12) and older age (4, 8) as major factors associated with ADEs. In support to this

finding perhaps especial care should be given to elderly who are admitted to ICUs

because of the added risk of combining two risk factors.

Several important basic medication safety practices are not adopted in most

Saudi hospitals (13, 14) . Therefore, there are opportunities for improving the safe use

of medications and preventing ADEs in hospitals in Saudi Arabia. On a national level,

the Saudi Food Drug Authority may lead efforts to prevent adverse drug reactions and

the Saudi Medication Safety Center may lead initiatives to prevent medication errors.

For example, the use of pharmacist to ascertain complete medication histories at

admission and provide discharge counseling reduced the incidence of ADEs (15, 16).

Although reporting is a good tool to identify and prevent ADEs, underreporting is a

common challenge in Saudi hospitals(17)

Future research could focus on investigating the causes of ADEs that occur

during the medication use process especially prescribing. Causes of ADEs need to be

identified through both qualitative and quantitative approaches. A systematic approach

need to be used to classify these causes. Using methods similar to the ones used in this

Page 13 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



14

study, the benefits of Interventions can be estimated and compared to baseline. This

study is limited in not including hospitals in small towns and rural areas. However, it is

expected to find higher incidence in these areas and the objective from this study is not

only to get the incidence but to understand the severity, preventability, and seriousness

of these ADEs.

In conclusion, ADEs are common in Saudi hospitals, especially in the ICUs, and

they caused significant morbidity and mortality. Although there are variations in the

incidence of ADEs between countries the possibilities of preventing it are higher;

therefore interventions that were proved to be effective in other countries should be

tested in Saudi Arabia. Such interventions may include but not limited to,

implementations of computerized physician entry (CPOE) with clinical decision support

system(11) involvement of clinical pharmacists as part of the medical team during

physicians rounds(18-20) and changing the currently available paper-based system to

electronic medical records(21).

Contribution: HA, DW and MM designed the study. HA wrote the manuscript, MA and

YA contributed in the data analysis and management. All authors contributed to the data

collection process, the study idea and design and approved the final manuscript.

Conflict of Interest: None declared

Data sharing statement: No additional data are available.

Funding: This study was funded by the National Plan for Science and Technology (09-

BIO708-02)

Page 14 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



15

Acknowledgment: We would like to thank research assistants, Emad Zalloum, Trig

Allam, Maram Abuzaid, Umm Hani Sayeda, Shamailah Osmani, Aishah Nor, Nesreen

al-shabr, Sultan Al-Harbi, for their help during the data collection process.

Page 15 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



16

References

1. Bates DW, Spell N, Cullen DJ, Burdick E, Laird N, Petersen LA, et al. The costs of

adverse drug events in hospitalized patients. Adverse Drug Events Prevention Study Group. JAMA : the journal of the American Medical Association. 1997;277(4):307-11. Epub 1997/01/22.

2. Bates DW, Cullen DJ, Laird N, Petersen LA, Small SD, Servi D, et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA : the journal of the American Medical Association. 1995;274(1):29-34. Epub 1995/07/05.

3. Al Hamid A, Ghaleb M, Aljadhey H, Aslanpour Z. A systematic review of hospitalisation resulting from medicine related problems in adult patients. British journal of clinical pharmacology. 2013. Epub 2013/11/29.

4. Morimoto T, Sakuma M, Matsui K, Kuramoto N, Toshiro J, Murakami J, et al. Incidence of Adverse Drug Events and Medication Errors in Japan: the JADE Study. J Gen Intern Med. 2011;26(2):148-53.

5. Aljadhey H, Mahmoud MA, Mayet A, Alshaikh M, Ahmed Y, Murray MD, et al. Incidence of adverse drug events in an academic hospital: a prospective cohort study. Int J Qual Health C. 2013;25(6):648-55.

6. Benkirane R, Pariente A, Achour S, Ouammi L, Azzouzi A, Soulaymani R. Prevalence and preventability of adverse drug events in a teaching hospital: a cross-sectional study. Eastern Mediterranean health journal = La revue de sante de la Mediterranee orientale = al-Majallah al-sihhiyah li-sharq al-mutawassit. 2009;15(5):1145-55. Epub 2010/03/11.

7. Stausberg J. International prevalence of adverse drug events in hospitals: an analysis of routine data from England, Germany, and the USA. BMC health services research. 2014;14:125. Epub 2014/03/14.

8. Gurwitz JH, Field TS, Harrold LR, Rothschild J, Debellis K, Seger AC, et al. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. Jama-J Am Med Assoc. 2003;289(9):1107-16.

9. Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care. 2004;13(4):306-14.

10. WHO WHO. Definitions. [cited 2014]; Available from: http://www.who.int/medicines/areas/quality_safety/safety_efficacy/trainingcourses/definitions.pdf

11. Hug BL, Witkowski DJ, Sox CM, Keohane CA, Seger DL, Yoon C, et al. Adverse Drug Event Rates in Six Community Hospitals and the Potential Impact of Computerized Physician Order Entry for Prevention. J Gen Intern Med. 2010;25(1):31-8.

12. Benkirane RR, Abouqal R, Haimeur CC, SS SECEK, Azzouzi AA, Mdaghri Alaoui AA, et al. Incidence of adverse drug events and medication errors in intensive care units: a prospective multicenter study. Journal of patient safety. 2009;5(1):16-22. Epub 2009/11/19.

13. Aljadhey H, Alhusan A, Alburikan K, Adam M, Murray MD, Bates DW. Medication safety practices in hospitals: A national survey in Saudi Arabia. Saudi Pharm J. 2013;21(2):159-64. Epub 2013/08/21.

14. Alkhani S, Ahmed Y, Bin-Sabbar N, Almogirah H, Alturki A, Albanyan H, et al. Current practices for labeling medications in hospitals in Riyadh, Saudi Arabia. Saudi Pharm J. 2013;21(4):345-9. Epub 2013/11/15.

Page 16 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



17

15. AbuYassin BH, Aljadhey H, Al-Sultan M, Al-Rashed S, Adam M, Bates DW. Accuracy of the medication history at admission to hospital in Saudi Arabia. Saudi Pharm J. 2011;19(4):263-7.

16. Al-Ghamdi SA, Mahmoud MA, Alammari MA, Al Bekairy AM, Alwhaibi M, Mayet AY, et al. The outcome of pharmacist counseling at the time of hospital discharge: an observational nonrandomized study. Ann Saudi Med. 2012;32(5):492-7.

17. Alshaikh M, Mayet A, Aljadhey H. Medication error reporting in a university teaching hospital in Saudi Arabia. Journal of patient safety. 2013;9(3):145-9. Epub 2013/02/02.

18. Kucukarslan SN, Peters M, Mlynarek M, Nafziger DA. Pharmacists on rounding teams reduce preventable adverse drug events in hospital general medicine units. Arch Intern Med. 2003;163(17):2014-8.

19. Schnipper JL, Kirwin JL, Cotugno MC, Wahlstrom SA, Brown BA, Tarvin E, et al. Role of pharmacist counseling in preventing adverse drug events after hospitalization. Arch Intern Med. 2006;166(5):565-71. Epub 2006/03/15.

20. Leape LL, Cullen DJ, Clapp MD, Burdick E, Demonaco HJ, Erickson JI, et al. Pharmacist participation on physician rounds and adverse drug events in the intensive care unit. Jama-J Am Med Assoc. 1999;282(3):267-70.

21. Liu M, Hinz ERM, Matheny ME, Denny JC, Schildcrout JS, Miller RA, et al. Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records. J Am Med Inform Assn. 2013;20(3):420-6.

Page 17 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



18

Tables

Table1. Demographic Characteristics of 3985 patients admitted to four Hospitals in Riyadh Frequency (%) Mean (±SD)

Gender

Male 2102 (52.7) -

Female 1883(47.3) -

Hospital type

Hospital 1(Teaching Hospital) 977(24.5) -

Hospital 2 (Private Hospital) 2033(51.1) -

Hospital 3(Large government Hospital) 683(17.1) -

Hospital 4 (Small government Hospital) 292(7.3) -

Service

Medicine 1352(33.9) -

Surgery 1771(44.5) -

Intensive Care Unit (ICU) 862(21.6) -

Age - 43.4 (±19.0)

Length of Hospital Stay - 8.1 (±10.2)

Charlson’s Comorbidity Score - 1.1 (±1.4)

Number of Medications - 2.5 (±2.9)

Table 2. Overall Incidence

Total number

of incidents

=1531

% Incidence per 100 admissions

(95% CI)

Crude rate per 1000 patient days (95%

CI)

Medication Errors with low risk to cause harm 609 39.8 15.3(14.1 – 16.5) 19.6 (18.7 – 21.2)

Potential ADEs 677 44.2 16.9 (15.7 – 18.3) 21.8 (20.2 – 23.5)

Intercepted Potential ADEs (N=213) 5.3 (4.6 – 6.1) 6.8(5.9 – 7.8)

Not intercepted Potential ADEs (N=464) 11.6 (10.6 – 12.7) 14.9 (13.6 – 16.3)

ADEs (Harm) 245 16 6.1 (5.4 – 6.9) 7.9 (6.9 – 8.9)

Preventable ADEs (N=85) 2.1(1.7 – 2.6) 2.7 (2.2 – 3.3)

Non-preventable ADEs (N=160) 4.0 (3.4 – 4.6) 5.1 (4.4 – 6.0)

ADEs, adverse drug events

Table 3. Classification of ADEs by Hospitals Type

Units ADEs Length of hospital

stay

ADEs crude rate per 1000 patient days (95% CI)

Number of admissions

ADEs Incidence per 100 admissions

(95% CI)

Hospital 1

83 9585 8.7 (6.9-10.6) 977 8.5(6.8-10.4)

Hospital 2

53 9032 5.9 (4.4-7.6) 2033 2.6 (2.1-3.3)

Hospital 3

13 6613 2.1(1.1-3.2) 683 2.1(1.1-3.2)

Hospital4

96 5766 16.6(13.5-20.2) 292 32.9(27.7-38.4)

Hospital 1= Teaching hospital, Hospital 2=Private hospital, Hospital 3= small government hospital, Hospital 4=Large government hospital

Table4. Classification of ADEs incidence by Type of Services

Units ADEs Patient days, No

ADEs Crude rate per 1000 patient days (95% CI)



(95% CI)

Medical 66 10767 6.1(4.7-7.7) 1352 4.8(3.8-6.1)

Surgical 29 9310 3.1(2.1-4.4) 1771 1.6(1.1-2.3)

ICU 150 10919 13.7(11.6-16.1) 862 17.4(14.7-20.3)


Page 18 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



19

Table 5. Factors Associated with ADEs

Factor Unadjusted Odds Ratio

95% CI Adjusted Odds Ratio

95% CI

Lower Upper Lower Upper

Age 1.024 1.017 1.032 1.012 1.003 1.021

Number of medications 1.193 1.148 1.240 1.062 1.008 1.119

Charlson’s comorbidity index 1.251 1.158 1.352 1.041 0.937 1.157

Length of hospital stay 1.042 1.034 1.051 1.025 1.015 1.035

Gender (Male)a 0.848 0.642 1.121 - - -

ICUb 7.786 5.259 11.528 3.276 2.005 5.354

Medicineb 2.539 1.664 3.872 1.736 1.078 2.796

CI, Confidence Interval, Reference categories: Femalea, Reference categories: Surgery

b

Page 19 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cohort studies

Section/Topic Item

# Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract Reported on page 1

(b) Provide in the abstract an informative and balanced summary of what was done and what was found Reported on page 1

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported Reported on page 4

Objectives 3 State specific objectives, including any prespecified hypotheses Reported on page 5

Methods

Study design 4 Present key elements of study design early in the paper Reported on page 6

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection

Reported on page 1

Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up Reported on page 7

(b) For matched studies, give matching criteria and number of exposed and unexposed

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group

Bias 9 Describe any efforts to address potential sources of bias

Study size 10 Explain how the study size was arrived at

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and

why

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding Reported on page 7

(b) Describe any methods used to examine subgroups and interactions

(c) Explain how missing data were addressed

(d) If applicable, explain how loss to follow-up was addressed

(e) Describe any sensitivity analyses

Results

Page 20 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on December 29, 2020 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2015-010831 on 12 July 2016. Downloaded from



Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

Reported on page 9

(b) Give reasons for non-participation at each stage

(c) Consider use of a flow diagram

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

Reported on page 9

(b) Indicate number of participants with missing data for each variable of interest

(c) Summarise follow-up time (eg, average and total amount) Reported on page 9

Outcome data 15* Report numbers of outcome events or summary measures over time

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

Reported on page 11

(b) Report category boundaries when continuous variables were categorized

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses

Discussion

Key results 18 Summarise key results with reference to study objectives Reported on page 12

Limitations

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from

similar studies, and other relevant evidence

Reported on page 14

Generalisability 21 Discuss the generalisability (external validity) of the study results Reported on page 14

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based

Reported on page 14

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

Page 21 of 21


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960





Journal: BMJ Open

Manuscript ID bmjopen-2015-010831.R1


Date Submitted by the Author: 15-Apr-2016

Complete List of Authors: Aljadhey, Hisham; College of Pharmacy, King Saud University, Medication Safety Research Chair Mahmoud, Mansour Ahmed, Yusuf; King Saud University, Medication Safety Research Chair Sultana, Razia; Specialized Medical Center Hospital Zouein, Salah; Specialized Medical Center Hospital Alshanawani, Sulafa ; King Saud Medical City Mayet, Ahmed; King Khaled University Hospital

Alshaikh, Mashael; King Khaled University Hospital Kalagi, Nora; King Saud University, Medication Safety Research Chair altawil, esra; King Khaled University Hospital El Kinge, Abdul Rahman ; Specialized Medical Center Hospital Arwadi, Abdulmajid; Specialized Medical Center Hospital Alyahya, Maha; King Salman Hospital Murray, Michael; Purdue University and Regenstrief Institute Bates, David; Division of General Medicine


Epidemiology

Secondary Subject Heading: Pharmacology and therapeutics, General practice / Family practice,

Intensive care, Research methods, Surgery



BMJ Open on D



jopen.bmj.com

/B

MJ O


ownloaded from



1

Incidence of Adverse Drug Events in Public and Private Hospitals in Riyadh, Saudi Arabia: The (ADESA) Prospective Cohort Study

Hisham Aljadhey1, Mansour A Mahmoud1, Yusuf Ahmed1, Razia Sultana2, Salah Zouein2, Sulafah Alshanawani3, Ahmed Mayet4, Mashael K Alshaikh4, Nora Kalagi1,

Esraa Al Tawil4, Abdul Rahman El Kinge5, Abdulmajid Arwadi5, Maha Alyahya6, Michael D Murray7, David Bates8


2Specialized Medical Center, Department of Pharmacy, Riyadh, Saudi Arabia

3King Saud Medical City, Department of Pharmacy, Riyadh, Saudi Arabia

4King Khaled University Hospital, Department of Pharmacy, Riyadh, Saudi Arabia

5Specialized Medical Center, Department of Internal Medicine, Riyadh, Saudi Arabia

6King Salman Hospital, Department of Pharmacy, Riyadh, Saudi Arabia

7Purdue University and Regenstrief Institute, College of Pharmacy, Indianapolis, United States

8Harvard Medical School and Brigham and Women's Hospital, Department of Medicine, Boston, United States.

Number of words

Text: 2987

Abstract: 299

Corresponding author: Hisham Aljadhey, Pharm D, PhD Director of Medication Safety Research Chair Dean, College of Pharmacy, King Saud University

Page 1 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



2

Supervisor of Pharmacy Services at King Saud University Medical CityP.O.Box 2475, Riyadh 11451, Saudi Arabia Email: [email protected] Phone: +966 530039008

Page 2 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



3

ABSRACT

Objectives: To determine the incidence of ADEs and assess their severity and

preventability in four Saudi hospitals.

Design: Prospective cohort study

Setting: The study included patients admitted to medical, surgical and intensive care

units of four hospitals in Saudi Arabia. These hospitals include a 900 bed tertiary

teaching hospital, a 400 bed private hospital, a 1400 bed large government hospital and

a 350 bed small government hospital.

Participants: All patients (≥12 years) admitted to the study units during four month.

Primary and secondary outcome measures: Incidents were collected by pharmacists

and reviewed by independent clinicians. Reviewers classified the identified incidents as

ADEs, potential ADEs (PADEs) and medication errors and then determined their

severity and preventability.

Results: We followed 4041 patients from admission to discharge. Of those, 3985

patients had complete data for analysis. The mean age of patients in the analysed

cohort was 43 (±19.5) years. A total of 1676 incidents of ADEs were identified by

pharmacists during the medical chart review. Clinician reviewers accepted 1531(91.4%)

of the incidents identified by the pharmacists (245 ADEs, 677 PADEs and 609

medication errors with low risk to cause harm). The incidence of ADEs was 6.1 (95% CI,

5.4-6.9) per 100 admissions and 7.9 (95% CI, 6.9 – 8.9) per 1000 patient-days. The

occurrence of ADEs was most common in the intensive care units 149 (60.8%) followed

Page 3 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



4

by medical 67(27.3%) and surgical units 29(11.8%). In terms of severity, 129 (52.7%) of

the ADEs were significant, 91 (37.1%) were serious, 22 (9%) were life-threatening and

three (1.2%) were fatal.

Conclusions: We found that ADEs were common in Saudi hospitals, especially in the

ICUs, causing significant morbidity and mortality. Future studies should focus on

investigating the root causes of ADEs at the prescribing stage and development and

testing of interventions to minimise harm from medications.

Key words: adverse drug events (ADEs), prospective cohort study, hospitals, Saudi

Arabia

Strength and limitations

• This study is one of the largest studies investigating the incidence of ADEs in the

Middle East.

• This study is limited by a lack of hospitals from small towns and rural areas and

that these settings have an even higher incidence of ADEs.

• Our study findings are not generalisable to overall Saudi Arabia because the

study was conducted in Riyadh only.

Page 4 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



5

INTRODUCTION

Adverse drug events (ADEs) are major cause of morbidity, mortality, and

increased healthcare costs and hospitalization (1-3). An ADE is defined as an injury

caused by a medication (4). They are largely preventable and occur mostly at the

prescribing stage of the medication use process (2, 4, 5). The incidence of ADEs

reported in the literature varies significantly between countries largely because of the

differences in available drug products, practices, training, study methodology and

patient safety initiatives among countries. Early in 1995 Bates et al from the United

States (U.S) reported an incidence of 6.5 per 100 admissions (2); however, while using

the same methods a study in Japan reported an incidence of 17 per 100 admissions (4)

suggesting real differences between these two countries. In Saudi Arabia, a single


study in Morocco reported an incidence of 4.2 per 100 admissions (6). A recent


3.2% in England, 4.8% in Germany and 5.6% in the U.S (7). It is important to mention

that the incidence of preventable ADEs was estimated by a population-based study to

be 13.8 per 1000 person-years (8).

Despite the evidence that ADEs are common and could be life threatening, little

attempt has been made in Saudi Arabia to detect and estimate the incidence of ADEs in

hospitalised patients. Such a paucity of research hinders the development of prevention

strategies to improve patient safety. To date, one prospective chart review study has

been conducted in a single teaching hospital in the Saudi setting (5). Therefore we

sought to estimate incident ADEs with a larger patient sample from different hospitals

Page 5 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



6

with diverse settings with varying practices and strategies for managing patients.

Therefore, the objective of our study was to estimate the incidence and risk factors

associated with ADEs in Saudi hospitals and determine their severity and preventability.

Page 6 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



7

METHODS

Study design and setting

The Adverse Drug Events in Saudi Arabia (ADESA) project was a four month

prospective cohort study involving four hospitals with diverse settings. These hospitals

included a 900 bed tertiary teaching hospital, a 400 bed private hospital, a 1400 bed

large government hospital and a 350-bed small government hospital. We randomly

selected medical, surgical and intensive care units (ICUs) from these hospitals and

excluded obstetrics and pediatric units because of the lower frequency of use of

medications within these units. We included patients older than 12 years of age

admitted for more than 24 hours during the four-month study period. None of the

hospitals had electronic medical records or decision support systems. Instead, hospitals

utilized paper-based systems where physician notes (including prescribed medications)

and nursing notes (including daily administered medications) were handwritten and kept

in patient charts. Medication orders were sent to the inpatient pharmacies and

dispensed using unit dose systems.

Definitions

Each incident was defined as an ADE (preventable and non-preventable), PADE that

were classified as either intercepted or non-intercepted or a medication errors with low

risk to cause harm. We defined ADE as a preventable injury that was caused by a

medication (2, 9). Non-preventable ADEs, also known as adverse drug reactions

(ADRs), are defined by the World Health Organization as “a response to a drug which is

noxious and unintended, and which occurs at doses used in man for prophylaxis,

Page 7 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



8

diagnosis, or therapy of disease, or for the modification of physiological function”(10).

Preventable ADEs were those that result from medication errors at any stage of the

medication use process (2). A PADE was an error that carries a risk of causing injury

related to the use of a medication but harm did not occur, either because of specific

circumstances or because the error was intercepted (9). Intercepted PADEs were those

that had the potential to cause injury but did not reach the patient because they were

intercepted by someone during the medication use process; Non-intercepted potential

ADEs were those with the potential to cause harm but failed to do so after the

medication reached the patient (9). Medication errors with a low risk to cause harm

included those with minimal risk to cause ADEs or PADEs. Comorbidities were

determined using Charlson's Comorbidity Index, which is a method of classifying

comorbidities of patients according to the International Classification of Disease (ICD).

Each comorbidity class has an associated weight of 1, 2, 3 or 6. The sum of all weights

results in a single comorbidity score for each patient with higher scores predictive of

adverse outcomes such as mortality or high resource use.


Data were collected as described in details elsewhere (5). Briefly, trained clinical

pharmacists collected data each day during the study period. In addition, all nurses

working in the particular units were invited to attend monthly in-service presentations

about the study to increase their awareness about ADEs reporting. The pharmacists

reviewed patients’ medical charts of all admitted patients in each of the participating

units to report demographic characteristics of patients, comorbidity and the number of

Page 8 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



9

medications. When incidents were noted the pharmacists wrote a detailed description of

each incident and captured the relevant patient characteristics and event history.

Two independent clinicians who were not involved in the data collection process

were provided with a study manual that contained study terminology and a guide on the

assessment of the severity and preventability of an incident. The manual included

examples of incidents and their severity classifications. The severity of the incidents

was categorized as significant, serious, life threatening or fatal using a methodology

developed by the Brigham and Women’s Hospital’s Center for Patient Safety Research

and Practice (2). The study manual served as a guide for the reviewers to

independently review the incidents and decide on inclusion of incidents and further

classify them as ADEs, PADEs or medication errors with low risk to cause harm. They

were then able to assess severity and preventability. Preventability categories were

defined as follows: definitely preventable, probably preventable, definitely not

preventable or probably not preventable (2). In the event that there was disagreement

on the classification of the incidents, the clinicians called for a meeting to decide

whether to include or exclude the incidents. The primary outcomes of this study were

incidence of ADEs, PADEs and medication errors with low risk to cause harm, as

defined previously. The secondary outcomes were the severity of events, their

preventability, and associated risk factors. The research and ethics committees of the

four hospitals approved this study.

Data Analysis:

Page 9 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



10

We calculated the overall incidence per 100 admissions and crude rate per 1000

patient- days with 95% confidence intervals (CI). In addition the incidence was

calculated by hospital and by unit type. Continuous variables are presented as mean ±

standard deviation (SD) and categorical variables as number and percentage. Inter-

rater reliability was assessed using the kappa statistic for assessment of the presence

of an ADE and its preventability and severity. To evaluate the univariate association of

potential risk factors with ADEs, we used univariate logistic regression. The variables

included in the univariate analysis were age, gender, Charlson’s comorbidity index

weight, length of hospital stay, number of medications, and service type. Variables

found to be statistically significant (P < 0.05) in the univariate analysis were included in

the multivariate logistic regression final model. Statistical analyses were conducted

using the Statistical Package for Social Science (SPSS) software IBM SPSS Statistics

for Windows, Version 22.0. Armonk, NY: IBM Corp

Page 10 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



11

RESULTS


Clinical pharmacists reviewed the medical charts of 4,041 patients. Complete

data of 3,985 patients were analysed (Table 1). The total length of hospital stay for


Arabia (977 patients from a teaching hospital; 2033 patients from a private hospital, 683

patients from large government hospital, and 292 patients from a small government

hospital). Male patients were a slight majority (52.7%). The patients were admitted to

one of the three services (Medicine, 1352 patients; surgery, 1771 patients; and

Intensive Care Units, 862 patients). The mean length of the hospital stay was 8.1 ± 10.2

days and the mean age of the patients was 43.4 ± 19.0 years (Table 2).


The pharmacists’ chart review s in the four hospitals identified 1676 cases of

ADEs, PADEs and medication errors. Physician reviewed and accepted 1531 (91.3%)

of the cases, which were classified as 609 (39.8%) medication errors with low risk of

harm, 677 (44.2%) PADEs, and 245 (16%) cases of ADEs. Among the ADEs 85

(34.7%) were deemed preventable and 160 (65.3%) were judged to be non-preventable

(Table 2). The majority of the preventable ADEs occurred in the prescribing stage (75 ;

88.2%) followed by administering stage (7 ;8.2%), dispensing stage (2 ;2.4% and

monitoring stage (1; ;1.2%). One hundred twenty nine (52.7%) of the ADEs were

significant, 91 (37.1%) were serious, 22 (9%) were life-threatening, and three (1.2%)

were fatal. Of the 85 preventable ADEs, 36 (42.4%) were significant, 38 (44.7%) were

serious, 10 (11.9%) were life-threatening and one (1.2%) was fatal. Among PADEs, 213

Page 11 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



12

(31.9%) were intercepted by the medical staff. Regarding severity of PADEs, 383

(56.6%) were significant, 271 (40%) were serious and 23 (3.4%) were life-threatening.

Overall incidence of ADEs and medication errors with low risk to cause harm

The incidence of ADEs per 100 admissions was 6.1(95% CI 5.4 – 6.9) and the

incidence of potential ADEs was 16.9 (95% CI 15.7 – 18.3) per 100 admissions (Table

2). The incidence of medication errors with low risk to cause harm was 15.3 (95% CI

14.1 – 16.5) per 100 admissions and the incidence of preventable ADEs was 2.1(95%

CI 1.7 – 2.6) per 100 admissions. The incidence of non-preventable ADEs was 4.0

(95% CI 3.4 – 4.6) per 100 admissions and the incidence of intercepted potential ADEs

was 5.3 (95% CI 4.6 – 6.1) per 100 admissions (Table 2). Incidents of preventable

ADEs, PADEs and medication errors with low risk to cause harm most commonly

occurred in the prescribing stage 1288 (84.1%) followed by dispensing stage 69 (4.5%)

and the administering stage (43; 2.8%). Table 3 shows the distribution of incidents

among the four hospitals. Examples of PADEs at different stages of the medication use

process are listed in Appendix A. The incidence of ADEs was higher in the large

government hospital 16.6 (95% CI 13.5-20.2) per 1000 patient-days and 32.9(95% CI

27.7-38.4) per 100 admissions followed by the teaching hospital 8.7 (95% CI 6.9-10.6)

per 1000 patient-days and 8.5(95% CI 6.8-10.4) per 100 admissions (Table 3).

The incidence of PADEs was predominantly higher in the private hospital (367;

23.9%). Medication errors were mostly seen in the private hospital (367; 23.9%).

Classification of ADEs Incidents by service type

Page 12 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



13

The incidence of ADEs was higher in the ICUs at 13.7 (95% CI 11.6-16.1) per

1000 patients-days and 17.4 (95% CI 14.7-20.3) per 100 admissions, followed by the

medical units 6.1 (95% CI 4.7-7.7) per 1000 patients-days and 4.8, (95% CI 3.8-6.1) per

100 admissions (Table 4).

Medication classes involved in ADEs, PADEs and medication errors with low risk to cause harm

Anticoagulants (21.6%) and antibiotics (20.8%) were the most common medication

classes associated with ADEs. Medication classes most commonly associated with

PADEs were antibiotics (31.3%) followed by anticoagulants (17.3%) and

antihypertensives (9.3%) (Table 5).


The kappa value for the presence of ADEs was 0.71; for the presence of

medication errors it was 0.67, and for the presence of potential ADEs it was 0.60. The


definitely or probably not preventable). For the severity of ADEs, the kappa value was

0.74 (fatal vs. significant, serious or life-threatening), 0.63 (life-threatening vs.

significant, serious or fatal), 0.53 (significant vs. serious, life-threatening or fatal), 0.48

(serious vs. life-threatening or fatal) (Table 6).

Factors associated with ADEs

Factors significantly associated with ADEs included age; (OR, 1.012; 95%CI,

1.003 – 1.021) number of medications (OR, 1.062; 95%CI, 1.008 – 1.119), length of

hospital stay (OR, 1.025; 95%CI, 1.015 – 1.035) and admission to the ICUs and

medicine units (OR, 3.276; 95%CI, 2.005 – 5.354) and (OR, 1.736; 95%CI, 1.078 –

Page 13 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



14

2.796), respectively (Table 7). Gender was not significantly associated with ADEs (p =

0.248); therefore, it was not included in the multivariate analysis.

Page 14 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



15

DISCUSSION


common with one third caused by medication errors judged to be preventable. Errors

resulting from preventable ADEs were most common in the prescribing stage followed

by the dispensing and administration stages. The majority of the preventable ADEs

were judged to be serious. The incidence of ADEs reported in our study was similar to

that found in previous studies (2, 5). However, a higher incidence was reported in Japan

(4). The differences between our study results and the results from the Japanese study

could be the longer length of hospital stay in Japan and differences in healthcare

systems between countries. The similarity between our findings and the US study could

be because of our use of the same methods for data collection, ADE detection, and

event classification and the similarities in the healthcare systems. The incidence in the

prescribing stage in the current study was higher than those reported in Malaysia

(25.15%) (11), Indonesia (20.4%) (12) and Thailand (1%)(13).

The kappa values reported in our study range from substantial to moderate

according to the measure of the strength of agreement suggested by Landis & Koch

(1977)(14). The lowest level of agreement in the current study was reported for

judgment regarding the severity of the incidents (0.48 and 0.52). However a similar

study reported kappa values lower than those found in our study (0.32 and 0.37) (2).

We included 3985 patients and found 245 ADEs, of which 35% were judged to

be preventable. Gurwitz and colleagues (8) identified 546 ADEs during 2403 nursing

home residence admissions and reported that 51% of the observed ADEs were

Page 15 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



16

preventable. Bates et al (2) determined the incidence of ADEs in 4,031 patients and

found 247 ADEs, of which 28% were deemed preventable. In 2009, Hug et al. (15)

assessed the occurrence of ADEs in 1200 patients from six community hospitals and

identified 180 ADEs, of which 75% were preventable. Recently a multicentre cohort

study of 3,459 patients identified 1010 ADEs and found that 14% of the identified ADEs

were preventable (4).

Regarding PADEs we noticed that only one third of the events were intercepted.

It is noteworthy to highlight that three of the four hospitals had clinical pharmacists

monitoring patient treatments and most of the intercepted PADEs were in those

hospitals.


age. Consistent with our results, other studies also reported that admission to ICUs (4,

16) and older age (4, 8) were major factors associated with ADEs. In support of this

finding, perhaps especial care should be given to elderly who are admitted to ICUs


Several important basic medication safety practices are not widely adopted in

most Saudi hospitals (17, 18) . Therefore, there are opportunities for improving the safe

use of medications and preventing ADEs in hospitals in Saudi Arabia. On a national

level, the Saudi Food Drug Authority may lead efforts to prevent ADRs and the Saudi

Medication Safety Centre may lead initiatives to prevent medication errors. For

example, the use of pharmacists to ascertain complete medication histories at


Page 16 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



17


common challenge in Saudi hospitals (21).

There is lack of literature about incident medication errors in Southeast Asian

(22) and the Middle Eastern countries (23). Future research could focus on investigating

the causes of ADEs that occur during the medication use process, especially at the

prescribing stage. More research is needed on the causes of ADEs using both

qualitative and quantitative methodologies using standard definitions of events and

severity classification. Using methods similar to the ones used in this study, the benefits

of interventions to prevent ADEs can be estimated and compared to a rigorously

determined baseline.

This study is one of the largest studies investigating the incidence of ADEs in the

Middle East. This study is limited by a lack of hospitals from small towns and rural areas

and that these settings have an even higher incidence of ADEs. Finally, our study

findings are not generalisable to overall Saudi Arabia because the study was conducted

in Riyadh only.

In conclusion, ADEs are common in Saudi hospitals, especially in the ICUs,

causing significant morbidity and mortality. While there are variations in the incidence of

ADEs among countries, there are prospects for preventing them. Interventions that are

effective in other countries should be tested in Saudi Arabia. Such interventions may

include but are not limited to implementations of computerised physician entry (CPOE)

with a clinical decision support system (15), involvement of clinical pharmacists as part

of the medical team during physicians rounds (24-26), medication reconciliation to

Page 17 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



18

obtain accurate medication histories at hospital admission, unit transfers during

hospitalization, and discharge from the hospital (27) and changing the currently

available paper-based system to electronic medical records system (28).

Contribution: HA, DB and MM designed the study. HA wrote the manuscript, MA and

YA contributed in the data analysis and management. All authors contributed to the data

collection process, the study idea and design and approved the final manuscript.



Funding: This study was funded by the National Plan for Science and Technology (09-

BIO708-02).




Page 18 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



19

References

1. Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug events in hospitalized patients.

Adverse Drug Events Prevention Study Group. JAMA. 1997;277(4):307-11.

2. Bates DW, Cullen DJ, Laird N, et al. Incidence of adverse drug events and potential adverse drug

events. Implications for prevention. ADE Prevention Study Group. JAMA. 1995;274(1):29-34.

3. Al Hamid A, Ghaleb M, Aljadhey H, et al. A systematic review of hospitalisation resulting from

medicine related problems in adult patients. Br J Clin Pharmacol . 2013.

4. Morimoto T, Sakuma M, Matsui K, et al. Incidence of Adverse Drug Events and Medication Errors

in Japan: the JADE Study.J Gen Intern Med. 2011;26(2):148-53.

5. Aljadhey H, Mahmoud MA, Mayet A, et al. Incidence of adverse drug events in an academic

hospital: a prospective cohort study. Int J Qual Health Care. 2013;25(6):648-55.

6. Benkirane R, Pariente A, Achour S, et al. Prevalence and preventability of adverse drug events in

a teaching hospital: a cross-sectional study. East Mediterr Health J.. 2009;15(5):1145-55.

7. Stausberg J. International prevalence of adverse drug events in hospitals: an analysis of routine

data from England, Germany, and the USA. BMC health serv res. 2014;14:125.

8. Gurwitz JH, Field TS, Harrold LR, et al. Incidence and preventability of adverse drug events

among older persons in the ambulatory setting. JAMA. 2003;289(9):1107-16.

9. Morimoto T, Gandhi TK, Seger AC,et al. Adverse drug events and medication errors: detection

and classification methods. BMJ Qual Saf . 2004;13(4):306-14.

10. WHO WHO. Definitions [cited 2014]. Available from:

http://www.who.int/medicines/areas/quality_safety/safety_efficacy/trainingcourses/definitions.pdf

11. Abdullah DC, Ibrahim NS, Ibrahim MI. Medication errors among geriatrics at the outpatient

pharmacy in a teaching hospital in Kelantan. Malays J Med Sci. 2004;11:52-8.

12. Ernawati DK, Lee YP, Hughes JD. Nature and frequency of medication errors in a geriatric ward:

an Indonesian experience. The Clin Risk Manag. 2014;10:413-21.

13. Sangtawesin V, Kanjanapattanakul W, Srisan P, et al. Ingchareonsunthorn P. Medication errors

at Queen Sirikit National Institute of Child Health. J Med Assoc Thai. 2003;3:S570–5.

14. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics.

1977;33(1):159-74.

15. Hug BL, Witkowski DJ, Sox CM, et al. Adverse Drug Event Rates in Six Community Hospitals and

the Potential Impact of Computerized Physician Order Entry for Prevention. J Gen Intern Med.

2010;25(1):31-8.

16. Benkirane RR, Abouqal R, Haimeur CC, et al. Incidence of adverse drug events and medication

errors in intensive care units: a prospective multicenter study. J Patient Saf. 2009;5(1):16-22.

17. Aljadhey H, Alhusan A, Alburikan K, et al. Medication safety practices in hospitals: A national

survey in Saudi Arabia. Saudi Pharmaceutical Journal. 2013;21(2):159-64.

18. Alkhani S, Ahmed Y, Bin-Sabbar N, et al. Current practices for labeling medications in hospitals in

Riyadh, Saudi Arabia. Saudi Pharm J . 2013;21(4):345-9.

19. AbuYassin BH, Aljadhey H, Al-Sultan M, et al. Accuracy of the medication history at admission to

hospital in Saudi Arabia. Saudi Pharm J . 2011;19(4):263-7.

20. Al-Ghamdi SA, Mahmoud MA, Alammari MA, et al. The outcome of pharmacist counseling at the

time of hospital discharge: an observational nonrandomized study. Ann Saudi Med. 2012;32(5):492-7.

21. Alshaikh M, Mayet A, Aljadhey H. Medication error reporting in a university teaching hospital in

Saudi Arabia. J Patient Saf. 2013;9(3):145-9.

22. Salmasi S, Khan TM, Hong YH, et al. Medication Errors in the Southeast Asian Countries: A

Systematic Review. PloS one. 2015;10(9):e0136545.

Page 19 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



20

23. Alsulami Z, Conroy S, Choonara I. Medication errors in the Middle East countries: a systematic

review of the literature. Eur JClin Pharmacol. 2013;69(4):995-1008.

24. Kucukarslan SN, Peters M, Mlynarek M, et al. Pharmacists on rounding teams reduce

preventable adverse drug events in hospital general medicine units. Arch Intern Med.

2003;163(17):2014-8.

25. Schnipper JL, Kirwin JL, Cotugno MC, Wahlstrom SA, Brown BA, Tarvin E, et al. Role of

pharmacist counseling in preventing adverse drug events after hospitalization. Arch Intern Med.

2006;166(5):565-71.

26. Leape LL, Cullen DJ, Clapp MD, et al. Pharmacist participation on physician rounds and adverse

drug events in the intensive care unit. JAMA. 1999;282(3):267-70.

27. Tam VC, Knowles SR, Cornish PL, Fine N, Marchesano R, Etchells EE. Frequency, type and clinical

importance of medication history errors at admission to hospital: a systematic review. Can Med Assoc J.

2005;173(5):510515.

28. Liu M, Hinz ERM, Matheny ME, Denny JC, Schildcrout JS, Miller RA, et al. Comparative analysis of

pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records.

J Am Med Inform Assoc. 2013;20(3):420-6.

Page 20 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



21

Tables


Gender

Male 2102 (52.7) -

Female 1883(47.3) -

Hospital type





Service

Medicine 1352(33.9) -

Surgery 1771(44.5) -


Age, years - 43.4 (±19.0)

Length of Hospital Stay, days - 8.1 (±10.2)

Comorbidities (Charlson’s index weight) - 1.1 (±1.4)


Table 2. Overall Incidence of ADEs, potential ADEs and medication errors with low risk t cause harm

Total number

of incidents

=1531


(95% CI)

Crude rate per 1000 patient-days (95%

CI)


Potential ADEs (PADEs) 677 44.2 16.9 (15.7 – 18.3) 21.8 (20.2 – 23.5)



ADEs (Harm) 245 16 6.1 (5.4 – 6.9) 7.9 (6.9 – 8.9)



Medication errors with low risk to cause harm include those medication errors with low risk to cause ADEs or PADEs. ADEs, adverse drug events

Table 3. Classification of ADEs by Hospital Type


stay

ADEs crude rate per 1000 patient- days (95% CI)



(95% CI)

Hospital 1

83 9585 8.7 (6.9-10.6) 977 8.5(6.8-10.4)

Hospital 2

53 9032 5.9 (4.4-7.6) 2033 2.6 (2.1-3.3)

Hospital 3

13 6613 2.1(1.1-3.2) 683 2.1(1.1-3.2)

Hospital4

96 5766 16.6(13.5-20.2) 292 32.9(27.7-38.4)

Hospital 1= Teaching hospital, Hospital 2=Private hospital, Hospital 3= small government hospital, Hospital 4=Large government

hospital


Units ADEs Patient-days, No

ADEs Crude rate per 1000 patient-days (95% CI)



(95% CI)

Medical 66 10767 6.1(4.7-7.7) 1352 4.8(3.8-6.1)

Surgical 29 9310 3.1(2.1-4.4) 1771 1.6(1.1-2.3)

ICU 150 10919 13.7(11.6-16.1) 862 17.4(14.7-20.3)


Page 21 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



22

Table 5. Medication classes involved in ADEs, PADEs and medication errors with low risk to cause harm

Medication classes ADEs, n (%)

(n= 245)

PADEs n (%)

(n= 677)

Medication errors with low risk to cause harm n (%)

(n= 609)

Antibiotics 51(20.8) 212(31.3) 193(31.7)

Anticoagulants 53(21.6) 117(17.3) 92(15.1)

Antihypertensives 49(20) 63(9.3) 61(10)

NSAIDs 11(4.5) 41(6.1) 55(9)

GI-medicines 4(1.6) 43(6.4) 39(6.4)

Antidiabetics 5(2) 32(4.7) 26(4.3)

Steroids 14(5.7) 12(1.8) 17(2.8)

Electrolytes 7(2.9) 19(2.8) 6(1)

Cardiovasculars 4(1.6) 15(2.2) 11(1.8)

Dyslipidemic agents 7(2.9) 16(2.4) 6(1)

Analgesics 4(1.6) 9(1.3) 15(2.5)

Antiasthmatics 5(2) 14(2.1) 6(1)

Antituberculosis 3(1.2) 11(1.6) 7(1.1)

Vitamins 0 8(1.2) 5(0.8)

Antifungals 1(0.5) 4(0.6) 6(1)

Antiseizures 5(2) 3(0.4) 2(0.3)

Antipsychotics 1(0.5) 3(0.4) 6(1)

Thyroid agents 0 5(0.7) 3(0.5)

Antivirals 4(1.6) 2(0.3) 1(0.2)

Antihistamines 1(0.5) 3(0.4) 1(0.2)

Sedatives 4(1.6) 1(0.1) 0

Anticancers 0 3(0.4) 2(0.3)

Others 12(4.9) 41(6.1) 49(8)

Page 22 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



23

Table 6. Interrator reliability of the incident type and their severity and preventability

Severity Agreement % Kappa value

Exclude vs ADEs, PADE or medication error 56.4 0.63

ADEs vs PADE, medication error or exclude 93.6 0.71

PADEs vs ADE, medication error or exclude 70.9 0.62

Medication error vs ADEs, PADE or exclude 93.7 0.67

Preventable vs non-preventable ADEs 92.2 0.68

Fatal vs Life-threatening, serious or significant 100 0.74

Life-threatening vs fatal serious or significant 100 0.63

Serious vs fatal, life-threatening or significant 60.5 0.48

Significant vs fatal, life-threatening or serious 84.2 0.52



95% CI P value Adjusted Odds Ratio

95% CI P value


Age 1.024 1.017 1.032 <0.001 1.012 1.003 1.021 0.009

Number of medications 1.193 1.148 1.240 <0.001 1.062 1.008 1.119 0.023

Charlson’s comorbidity index weight

1.251 1.158 1.352 <0.001 1.041 0.937 1.157 0.452

Length of hospital stay 1.042 1.034 1.051 <0.001 1.025 1.015 1.035 <0.001

Gender (Male)a 0.848 0.642 1.121 0.248 - - - -

ICUb 7.786 5.259 11.528 <0.001 3.276 2.005 5.354 <0.001

Medicineb 2.539 1.664 3.872 <0.001 1.736 1.078 2.796 0.023


b

Page 23 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



24

Appendix A.

Examples of PADEs

Prescribing

The physician ordered lisinopril, 5 mg tablet, once daily even though the patient was not

hypertensive and had no indication for the drug. The order was intended for another patient and

the nurse intercepted the error.

Transcribing

A 74-year old man with diabetes mellitus, hypertension and recurrent urinary tract infections

was admitted to the medical ward. Meropenem, 500 mg intravenously, every eight hours was

ordered. In the morning round, the infectious disease consultant verbally asked the intern to

change meropenem to imipenem 500 mg intravenously every six hours. However, the intern

mistakenly transcribed it as meropenem. This error was caught, corrected, and noted as an

error in the patient’s medical record.

Dispensing

An order of metoclopramide 10 mg was sent to the pharmacy. The nurse obtained the drug from

the pharmacy, but from the appearance of the solution, she suspected that the preparation was

not metoclopramide. The nurse contacted the pharmacy and the pharmacist found that it was

the wrong medication, although the label was stated that it was metoclopramide.

Administering

A nurse handled two capsules for two different patients in Room #8 and Room #9. She almost

accidentally gave the wrong medication (switched) to each patient. However, the patient in

Page 24 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



25

Room # 9 knew her medication and she said, “This is not my medicine,” and the error was

intercepted by the patient.

Page 25 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



26

Figure 1. Study flow chart

Study included 3,985 patients admitted to four

hospitals over four months

Incidents identified by pharmacists

1676

Incidents rejected by reviewers

145

Incidents accepted by reviewers

1531

Medication errors 1286

Adverse drug events (ADEs)

245

Non-preventable ADEs 160

Preventable ADEs

85

Risk to cause harm (Potential ADEs)

677

Low risk to cause harm

609

Non-intercepted 464

Intercepted 213

Page 26 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from




Section/Topic Item


Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 6

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 5

Objectives 3 State specific objectives, including any prespecified hypotheses 5

Methods

Study design 4 Present key elements of study design early in the paper 6


collection

6

Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up 6



applicable

6

Data sources/

measurement



7


Study size 10 Explain how the study size was arrived at 6


why

8

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 8

(b) Describe any methods used to examine subgroups and interactions 8




Results

Page 27 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960






10

(b) Give reasons for non-participation at each stage 10

(c) Consider use of a flow diagram 24


confounders

10


(c) Summarise follow-up time (eg, average and total amount) 6

Outcome data 15* Report numbers of outcome events or summary measures over time 10



12




Discussion

Key results 18 Summarise key results with reference to study objectives 14

Limitations



15 -16

Generalisability 21 Discuss the generalisability (external validity) of the study results 16

Other information



17





Page 28 of 28


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960




Incidence of Adverse Drug Events in Public and Private Hospitals in Riyadh, Saudi Arabia: The (ADESA) Prospective

Cohort Study

Journal: BMJ Open

Manuscript ID bmjopen-2015-010831.R2


Date Submitted by the Author: 01-Jun-2016

Complete List of Authors: Aljadhey, Hisham; College of Pharmacy, King Saud University, Medication Safety Research Chair Mahmoud, Mansour

Ahmed, Yusuf; King Saud University, Medication Safety Research Chair Sultana, Razia; Specialized Medical Center Hospital Zouein, Salah; Specialized Medical Center Hospital Alshanawani, Sulafa ; King Saud Medical City Mayet, Ahmed; King Khaled University Hospital Alshaikh, Mashael; King Khaled University Hospital Kalagi, Nora; King Saud University, Medication Safety Research Chair altawil, esra; King Khaled University Hospital El Kinge, Abdul Rahman ; Specialized Medical Center Hospital Arwadi, Abdulmajid; Specialized Medical Center Hospital Alyahya, Maha; King Salman Hospital Murray, Michael; Purdue University and Regenstrief Institute

Bates, David; Division of General Medicine


Epidemiology

Secondary Subject Heading: Pharmacology and therapeutics, General practice / Family practice, Intensive care, Research methods, Surgery



BMJ Open on D



jopen.bmj.com

/B

MJ O


ownloaded from



1

Incidence of Adverse Drug Events in Public and Private Hospitals in Riyadh, Saudi Arabia: The (ADESA) Prospective Cohort Study

Hisham Aljadhey1, Mansour A Mahmoud1, Yusuf Ahmed1, Razia Sultana2, Salah Zouein2, Sulafah Alshanawani3, Ahmed Mayet4, Mashael K Alshaikh4, Nora Kalagi1,

Esraa Al Tawil4, Abdul Rahman El Kinge2, Abdulmajid Arwadi2, Maha Alyahya5, Michael D Murray6, David Bates7


2Specialized Medical Center, Riyadh, Saudi Arabia

3King Saud Medical City, Riyadh, Saudi Arabia

4King Khaled University Hospital, Riyadh, Saudi Arabia

5King Salman Hospital, Riyadh, Saudi Arabia

6Purdue University and Regenstrief Institute, Indianapolis, United States

7 Harvard Medical School and Brigham and Women's Hospital, Boston, United States.

Number of words

Text: 3059

Abstract: 299

Corresponding author: Hisham Aljadhey, Pharm D, PhD Director of Medication Safety Research Chair Dean, College of Pharmacy, King Saud University Supervisor of Pharmacy Services at King Saud University Medical CityP.O.Box 2475, Riyadh 11451, Saudi Arabia Email: [email protected] Phone: +966 530039008

Page 1 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



2

ABSRACT

Objectives: To determine the incidence of ADEs and assess their severity and

preventability in four Saudi hospitals.

Design: Prospective cohort study

Setting: The study included patients admitted to medical, surgical and intensive care

units of four hospitals in Saudi Arabia. These hospitals include a 900 bed tertiary

teaching hospital, a 400 bed private hospital, a 1400 bed large government hospital and

a 350 bed small government hospital.

Participants: All patients (≥12 years) admitted to the study units during four month.

Primary and secondary outcome measures: Incidents were collected by pharmacists

and reviewed by independent clinicians. Reviewers classified the identified incidents as

ADEs, potential ADEs (PADEs) and medication errors and then determined their

severity and preventability.

Results: We followed 4041 patients from admission to discharge. Of those, 3985

patients had complete data for analysis. The mean age of patients in the analysed

cohort was 43 (±19.5) years. A total of 1676 incidents of ADEs were identified by

pharmacists during the medical chart review. Clinician reviewers accepted 1531(91.4%)

of the incidents identified by the pharmacists (245 ADEs, 677 PADEs and 609

medication errors with low risk to cause harm). The incidence of ADEs was 6.1 (95% CI,

5.4-6.9) per 100 admissions and 7.9 (95% CI, 6.9 – 8.9) per 1000 patient-days. The

occurrence of ADEs was most common in the intensive care units 149 (60.8%) followed

Page 2 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



3

by medical 67(27.3%) and surgical units 29(11.8%). In terms of severity, 129 (52.7%) of

the ADEs were significant, 91 (37.1%) were serious, 22 (9%) were life-threatening and

three (1.2%) were fatal.

Conclusions: We found that ADEs were common in Saudi hospitals, especially in the

ICUs, causing significant morbidity and mortality. Future studies should focus on

investigating the root causes of ADEs at the prescribing stage and development and

testing of interventions to minimise harm from medications.

Key words: adverse drug events (ADEs), prospective cohort study, hospitals, Saudi

Arabia

Page 3 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



4

Strength and limitations

• This study is one of the largest studies investigating the incidence of ADEs in the

Middle East.

• This study is limited by a lack of hospitals from small towns and rural areas and

that these settings have an even higher incidence of ADEs.

• Our study findings are not generalisable to overall Saudi Arabia because the

study was conducted in Riyadh only.

Page 4 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



5

INTRODUCTION

Adverse drug events (ADEs) are major cause of morbidity, mortality, and

increased healthcare costs and hospitalization (1-3). An ADE is defined as an injury

caused by a medication (4). They are largely preventable and occur mostly at the

prescribing stage of the medication use process (2, 4, 5). The incidence of ADEs

reported in the literature varies significantly between countries largely because of the

differences in available drug products, practices, training, study methodology and

patient safety initiatives among countries. Early in 1995 Bates et al from the United

States (U.S) reported an incidence of 6.5 per 100 admissions (2); however, while using

the same methods a study in Japan reported an incidence of 17 per 100 admissions (4)

suggesting real differences between these two countries. In Saudi Arabia, a single


study in Morocco reported an incidence of 4.2 per 100 admissions (6). A recent


3.2% in England, 4.8% in Germany and 5.6% in the U.S (7). It is important to mention

that the incidence of preventable ADEs was estimated by a population-based study to

be 13.8 per 1000 person-years (8).

Despite the evidence that ADEs are common and could be life threatening, little

attempt has been made in Saudi Arabia to detect and estimate the incidence of ADEs in

hospitalised patients. Such a paucity of research hinders the development of prevention

strategies to improve patient safety. To date, one prospective chart review study has

been conducted in a single teaching hospital in the Saudi setting (5). Therefore we

sought to estimate incident ADEs with a larger patient sample from different hospitals

Page 5 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



6

with diverse settings with varying practices and strategies for managing patients.

Therefore, the objective of our study was to estimate the incidence and risk factors

associated with ADEs in Saudi hospitals and determine their severity and preventability.

Page 6 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



7

METHODS

Study design and setting

The Adverse Drug Events in Saudi Arabia (ADESA) project was a four month

prospective cohort study involving four hospitals with diverse settings. These hospitals

included a 900 bed tertiary teaching hospital, a 400 bed private hospital, a 1400 bed

large government hospital and a 350-bed small government hospital. We randomly

selected medical, surgical and intensive care units (ICUs) from these hospitals and

excluded obstetrics and pediatric units because of the lower frequency of use of

medications within these units. We included patients older than 12 years of age

admitted for more than 24 hours during the four-month study period. None of the

hospitals had electronic medical records or decision support systems. Instead, hospitals

utilized paper-based systems where physician notes (including prescribed medications)

and nursing notes (including daily administered medications) were handwritten and kept

in patient charts. Medication orders were sent to the inpatient pharmacies and

dispensed using unit dose systems.

Definitions

Each incident was defined as an ADE (preventable and non-preventable), PADE that

were classified as either intercepted or non-intercepted or a medication errors with low

risk to cause harm. We defined ADE as any injury resulting from medical interventions

related to a drug and includes both ADR in which no error occurred and complications

resulting from medication errors (2, 9, 10). Non-preventable ADEs, also known as

adverse drug reactions (ADRs), are defined by the World Health Organization as “a

Page 7 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



8

response to a drug which is noxious and unintended, and which occurs at doses used in

man for prophylaxis, diagnosis, or therapy of disease, or for the modification of

physiological function”(11). A non-preventable ADE is an injury with no error in the

medication process. An example of this would be an allergic reaction in a patient not

previously known to be allergic to that particular medication. Preventable ADEs were

those that result from medication errors at any stage of the medication use process (2).

An example of this would be an anaphylactic reaction to an antibiotic that the patient is

known to be allergic to. Preventability was further classified into definitely

preventable/non-preventable and probably preventable/non-preventable. A PADE was

an error that carries a risk of causing injury related to the use of a medication but harm

did not occur, either because of specific circumstances or because the error was

intercepted (9). Intercepted PADEs were those that had the potential to cause injury but

did not reach the patient because they were intercepted by someone during the

medication use process; Non-intercepted potential ADEs were those with the potential

to cause harm but failed to do so after the medication reached the patient (9).

Medication errors with a low risk to cause harm included those with minimal risk to

cause ADEs or PADEs. Comorbidities were determined using Charlson's Comorbidity

Index, which is a method of classifying comorbidities of patients according to the

International Classification of Disease (ICD). Each comorbidity class has an associated

weight of 1, 2, 3 or 6. The sum of all weights results in a single comorbidity score for

each patient with higher scores predictive of adverse outcomes such as mortality or

high resource use.


Page 8 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



9

Data were collected as described in details elsewhere (5). Briefly, trained clinical

pharmacists collected data each day during the study period. In addition, all nurses working in

the particular units were invited to attend monthly in-service presentations about the study to

increase their awareness about ADEs reporting. The pharmacists reviewed patients’ medical

charts of all admitted patients in each of the participating units to report demographic

characteristics of patients, comorbidity and the number of medications. When incidents were

noted the pharmacists wrote a detailed description of each incident and captured the relevant

patient characteristics and event history.

Two independent clinicians who were not involved in the data collection process, were

provided with a study manual that contained study terminology and a guide on the assessment

of the severity and preventability of an incident. The manual included examples of incidents and

their severity classifications. The severity of the incidents was categorized as significant,

serious, life threatening or fatal using a methodology developed by the Brigham and Women’s

Hospital’s Center for Patient Safety Research and Practice (2). The study manual served as a

guide for the reviewers to independently review the incidents and decide on inclusion of

incidents and further classify them as ADEs, PADEs or medication errors with low risk to cause

harm. They were then able to assess severity and preventability. Preventability categories were

defined as follows: definitely preventable, probably preventable, definitely not preventable or

probably not preventable (2). In the event that there was disagreement on the classification of

the incidents, the clinicians called for a meeting to decide whether to include or exclude the

incidents. The primary outcomes of this study were incidence of ADEs, PADEs and medication

errors with low risk to cause harm, as defined previously. The secondary outcomes were the

severity of events, their preventability, and associated risk factors. The research and ethics

committees of the four hospitals approved this study.

Data Analysis:

Page 9 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



10

We calculated the overall incidence per 100 admissions and crude rate per 1000 patient-

days with 95% confidence intervals (CI). In addition the incidence was calculated by hospital

and by unit type. Continuous variables are presented as mean ± standard deviation (SD) and

categorical variables as number and percentage. Inter-rater reliability was assessed using the

kappa statistic for assessment of the presence of an ADE and its preventability and severity. To

evaluate the univariate association of potential risk factors with ADEs, we used univariate

logistic regression. The variables included in the univariate analysis were age, gender,

Charlson’s comorbidity index weight, length of hospital stay, number of medications, and service

type. Variables found to be statistically significant (P < 0.05) in the univariate analysis were

included in the multivariate logistic regression final model. Statistical analyses were conducted

using the Statistical Package for Social Science (SPSS) software IBM SPSS Statistics for

Windows, Version 22.0. Armonk, NY: IBM Corp.

Page 10 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



11

RESULTS


Clinical pharmacists reviewed the medical charts of 4,041 patients. Complete

data of 3,985 patients were analysed (Table 1). The total length of hospital stay for


Arabia (977 patients from a teaching hospital; 2033 patients from a private hospital, 683

patients from large government hospital, and 292 patients from a small government

hospital). Male patients were a slight majority (52.7%) (Table1). The patients were

admitted to one of the three services (Medicine, 1352 patients; surgery, 1771 patients;

and Intensive Care Units, 862 patients). The mean length of the hospital stay was 8.1 ±

10.2 days and the mean age of the patients was 43.4 ± 19.0 years (Table 1).


The pharmacists’ chart review s in the four hospitals identified 1676 cases of

ADEs, PADEs and medication errors. Physician reviewed and accepted 1531 (91.3%)

of the cases, which were classified as 609 (39.8%) medication errors with low risk of

harm, 677 (44.2%) PADEs, and 245 (16%) cases of ADEs (Figure 1). Among the ADEs

85 (34.7%) were deemed preventable and 160 (65.3%) were judged to be non-

preventable (Table 2). The majority of the preventable ADEs occurred in the prescribing

stage (75 ; 88.2%) followed by administering stage (7 ;8.2%), dispensing stage (2 ;2.4%

and monitoring stage (1; ;1.2%). One hundred twenty nine (52.7%) of the ADEs were

significant, 91 (37.1%) were serious, 22 (9%) were life-threatening, and three (1.2%)

were fatal. Of the 85 preventable ADEs, 36 (42.4%) were significant, 38 (44.7%) were

serious, 10 (11.9%) were life-threatening and one (1.2%) was fatal. Among PADEs, 213

Page 11 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



12

(31.9%) were intercepted by the medical staff. Regarding severity of PADEs, 383

(56.6%) were significant, 271 (40%) were serious and 23 (3.4%) were life-threatening.

Overall incidence of ADEs and medication errors with low risk to cause harm

The incidence of ADEs per 100 admissions was 6.1(95% CI 5.4 – 6.9) and the

incidence of potential ADEs was 16.9 (95% CI 15.7 – 18.3) per 100 admissions (Table

2). The incidence of medication errors with low risk to cause harm was 15.3 (95% CI

14.1 – 16.5) per 100 admissions and the incidence of preventable ADEs was 2.1(95%

CI 1.7 – 2.6) per 100 admissions. The incidence of non-preventable ADEs was 4.0

(95% CI 3.4 – 4.6) per 100 admissions and the incidence of intercepted potential ADEs

was 5.3 (95% CI 4.6 – 6.1) per 100 admissions (Table 2). Incidents of preventable

ADEs, PADEs and medication errors with low risk to cause harm most commonly

occurred in the prescribing stage 1288 (84.1%) followed by dispensing stage 69 (4.5%)

and the administering stage (43; 2.8%). Table 3 shows the distribution of incidents

among the four hospitals. Examples of PADEs at different stages of the medication use

process are listed in Appendix A. The incidence of ADEs was higher in the large

government hospital 16.6 (95% CI 13.5-20.2) per 1000 patient-days and 32.9(95% CI

27.7-38.4) per 100 admissions followed by the teaching hospital 8.7 (95% CI 6.9-10.6)

per 1000 patient-days and 8.5(95% CI 6.8-10.4) per 100 admissions (Table 3).

The incidence of PADEs was predominantly higher in the private hospital (367;

23.9%). Medication errors were mostly seen in the private hospital (367; 23.9%).

Classification of ADEs Incidents by service type

Page 12 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



13

The incidence of ADEs was higher in the ICUs at 13.7 (95% CI 11.6-16.1) per

1000 patients-days and 17.4 (95% CI 14.7-20.3) per 100 admissions, followed by the

medical units 6.1 (95% CI 4.7-7.7) per 1000 patients-days and 4.8,(95% CI 3.8-6.1) per

100 admissions (Table 4).

Medication classes involved in ADEs, PADEs and medication errors with low risk to cause harm

Anticoagulants (21.6%) and antibiotics (20.8%) were the most common medication

classes associated with ADEs. Medication classes most commonly associated with

PADEs were antibiotics (31.3%) followed by anticoagulants (17.3%) and

antihypertensives (9.3%) (Table 5).


The kappa value for the presence of ADEs was 0.71; for the presence of

medication errors it was 0.67, and for the presence of potential ADEs it was 0.60. The


definitely or probably not preventable). For the severity of ADEs, the kappa value was

0.74 (fatal vs. significant, serious or life-threatening), 0.63 (life-threatening vs.

significant, serious or fatal), 0.53 (significant vs. serious, life-threatening or fatal), 0.48

(serious vs. life-threatening or fatal) (Table 6).

Factors associated with ADEs

Factors significantly associated with ADEs included age; (OR, 1.012; 95%CI,

1.003 – 1.021) number of medications (OR, 1.062; 95%CI, 1.008 – 1.119), length of

hospital stay (OR, 1.025; 95%CI, 1.015 – 1.035) and admission to the ICUs and

medicine units (OR, 3.276; 95%CI, 2.005 – 5.354) and (OR, 1.736; 95%CI, 1.078 –

Page 13 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



14

2.796), respectively (Table 7). Gender was not significantly associated with ADEs (p =

0.248); therefore, it was not included in the multivariate analysis.

Page 14 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



15

DISCUSSION


common with one third caused by medication errors judged to be preventable. Errors

resulting from preventable ADEs were most common in the prescribing stage followed

by the dispensing and administration stages. The majority of the preventable ADEs

were judged to be serious. The incidence of ADEs reported in our study was similar to

that found in previous studies (2, 5). However, a higher incidence was reported in Japan

(4). The differences between our study results and the results from the Japanese study

could be the longer length of hospital stay in Japan and differences in healthcare

systems between countries. The similarity between our findings and the US study could

be because of our use of the same methods for data collection, ADE detection, and

event classification and the similarities in the healthcare systems. The incidence in the

prescribing stage in the current study was higher than those reported in Malaysia

(25.15%) (12), Indonesia (20.4%) (13) and Thailand (1%)(14).

The kappa values reported in our study range from substantial to moderate

according to the measure of the strength of agreement suggested by Landis & Koch

(1977)(15). The lowest level of agreement in the current study was reported for

judgment regarding the severity of the incidents (0.48 and 0.52). However a similar

study reported kappa values lower than those found in our study (0.32 and 0.37) (2).

We included 3985 patients and found 245 ADEs, of which 35% were judged to

be preventable. Gurwitz and colleagues (8) identified 546 ADEs during 2403 nursing

Page 15 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



16

home residence admissions and reported that 51% of the observed ADEs were

preventable. Bates et al (2) determined the incidence of ADEs in 4,031 patients and

found 247 ADEs, of which 28% were deemed preventable. In 2009, Hug et al. (16)

assessed the occurrence of ADEs in 1200 patients from six community hospitals and

identified 180 ADEs, of which 75% were preventable. Recently a multicentre cohort

study of 3,459 patients identified 1010 ADEs and found that 14% of the identified ADEs

were preventable (4).

Regarding PADEs we noticed that only one third of the events were intercepted.

It is noteworthy to highlight that three of the four hospitals had clinical pharmacists

monitoring patient treatments and most of the intercepted PADEs were in those

hospitals.


age. Consistent with our results, other studies also reported that admission to ICUs (4,

17) and older age (4, 8) were major factors associated with ADEs. In support of this

finding, perhaps especial care should be given to elderly who are admitted to ICUs


Several important basic medication safety practices are not widely adopted in

most Saudi hospitals (18, 19) . Therefore, there are opportunities for improving the safe

use of medications and preventing ADEs in hospitals in Saudi Arabia. On a national

level, the Saudi Food Drug Authority may lead efforts to prevent ADRs and the Saudi

Medication Safety Centre may lead initiatives to prevent medication errors. For

example, the use of pharmacists to ascertain complete medication histories at

Page 16 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



17



common challenge in Saudi hospitals (22)

There is lack of literature about incident medication errors in Southeast Asian

(23) and the Middle Eastern countries (24). Future research could focus on investigating

the causes of ADEs that occur during the medication use process, especially at the

prescribing stage. More research is needed on the causes of ADEs using both

qualitative and quantitative methodologies using standard definitions of events and

severity classification. Using methods similar to the ones used in this study, the benefits

of interventions to prevent ADEs can be estimated and compared to a rigorously

determined baseline.

This study is limited by a lack of hospitals from small towns and rural areas and it

that these settings have an even higher incidence of ADEs. Finally, our study findings

are not generalisable to overall Saudi Arabia because the study was conducted in

Riyadh only.

In conclusion, ADEs are common in Saudi hospitals, especially in the ICUs,

causing significant morbidity and mortality. While there are variations in the incidence of

ADEs among countries, there are prospects for preventing them. Interventions that are

effective in other countries should be tested in Saudi Arabia. Such interventions may

include but are not limited to implementations of computerised physician entry (CPOE)

with a clinical decision support system (16), involvement of clinical pharmacists as part

of the medical team during physicians rounds (25-27), medication reconciliation to

Page 17 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



18

obtain accurate medication histories at hospital admission, unit transfers during

hospitalization, and discharge from the hospital (28) and changing the currently

available paper-based system to electronic medical records system (29).

Contribution: HA, DB and MDM designed the study. HA and MAM wrote the

manuscript, MAM and YA contributed in the data analysis and management. All authors

contributed to the data collection process, the study idea and design and approved the final

manuscript.



Funding: This work was supported by the National Plan for Science and Technology

(09-BIO708-02).




Page 18 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



19

References

1. Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug events in hospitalized patients.

Adverse Drug Events Prevention Study Group. JAMA 1997;277:307-11.

2. Bates DW, Cullen DJ, Laird N, et al. Incidence of adverse drug events and potential adverse drug

events. Implications for prevention. ADE Prevention Study Group. JAMA 1995;274:29-34.

3. Al Hamid A, Ghaleb M, Aljadhey H, et al. A systematic review of hospitalisation resulting from

medicine related problems in adult patients. Br J Clin Pharmacol 2013;78:202-17.

4. Morimoto T, Sakuma M, Matsui K, et al. Incidence of adverse drug events and medication errors

in Japan: the JADE study. J Gen Intern Med 2011;26:148-53.

5. Aljadhey H, Mahmoud MA, Mayet A, et al. Incidence of adverse drug events in an academic

hospital: a prospective cohort study. Int J Qual Health C 2013;25:648-55.

6. Benkirane R, Pariente A, Achour S, et al. Prevalence and preventability of adverse drug events in

a teaching hospital: a cross-sectional study. East Mediterr Health J 2009;15:1145-55.

7. Stausberg J. International prevalence of adverse drug events in hospitals: an analysis of routine

data from England, Germany, and the USA. BMC Health Serv Res 2014;14:125.

8. Gurwitz JH, Field TS, Harrold LR, et al. Incidence and preventability of adverse drug events

among older persons in the ambulatory setting. JAMA 2003;289:1107-16.

9. Morimoto T, Gandhi TK, Seger AC, et al. Adverse drug events and medication errors: detection

and classification methods. BMJ Qual Saf 2004;13:306-14.

10. Bates DW, Boyle DL, Vliet MVV, et al. Relationship between Medication Errors and Adverse Drug

Events. J Gen Intern Med 1995;10:199-205.

11. WHO. WHO Definitions [cited 2014]. Available from:

http://www.who.int/medicines/areas/quality_safety/safety_efficacy/trainingcourses/definitions.pdf

12. Abdullah DC, Ibrahim NS, Ibrahim MI. Medication errors among geriatrics at the outpatient

pharmacy in a teaching hospital in Kelantan. Malays J Med Sci 2004;11:52-8.

13. Ernawati DK, Lee YP, Hughes JD. Nature and frequency of medication errors in a geriatric ward:

an Indonesian experience. Therapeutics and clinical risk management 2014;10:413-21.

14. Sangtawesin V, Kanjanapattanakul W, Srisan P, et al. Medication errors at Queen Sirikit National

Institute of Child Health. J Med Assoc Thai 2003;3:S570–5.

15. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics.

1977;33:159-74.

16. Hug BL, Witkowski DJ, Sox CM, et al. Adverse Drug Event Rates in Six Community Hospitals and

the Potential Impact of Computerized Physician Order Entry for Prevention. J Gen Intern Med

2010;25:31-8.

17. Benkirane RR, Abouqal R, Haimeur CC, et al. Incidence of adverse drug events and medication

errors in intensive care units: a prospective multicenter study. J Patient Saf 2009;5:16-22.

18. Aljadhey H, Alhusan A, Alburikan K, et al. Medication safety practices in hospitals: A national

survey in Saudi Arabia. Saudi Pharm J 2013;21:159-64.

19. Alkhani S, Ahmed Y, Bin-Sabbar N, et al. Current practices for labeling medications in hospitals in

Riyadh, Saudi Arabia. Saudi Pharm J 2013;21:345-9.

20. Abuyassin BH, Aljadhey H, Al-Sultan M, et al. Accuracy of the medication history at admission to

hospital in Saudi Arabia. Saudi Pharm J 2011;19:263-7.

21. Al-Ghamdi SA, Mahmoud MA, Alammari MA, et al. The outcome of pharmacist counseling at the

time of hospital discharge: an observational nonrandomized study. Ann Saudi Med 2012;32:492-7.

22. Alshaikh M, Mayet A, Aljadhey H. Medication error reporting in a university teaching hospital in

Saudi Arabia. J Patient Saf 2013;9:145-9.

Page 19 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



20

23. Salmasi S, Khan TM, Hong YH, et al. Medication Errors in the Southeast Asian Countries: A

Systematic Review. PloS one 2015;10:e0136545.

24. Alsulami Z, Conroy S, Choonara I. Medication errors in the Middle East countries: a systematic

review of the literature. Eur J Clin Pharmacol 2013;69:995-1008.

25. Kucukarslan SN, Peters M, Mlynarek M, et al. Pharmacists on rounding teams reduce

preventable adverse drug events in hospital general medicine units. Arch Intern Med 2003;163:2014-8.

26. Schnipper JL, Kirwin JL, Cotugno MC, et al. Role of pharmacist counseling in preventing adverse

drug events after hospitalization. Arch Intern Med 2006;166:565-71.

27. Leape LL, Cullen DJ, Clapp MD, et al. Pharmacist participation on physician rounds and adverse

drug events in the intensive care unit. JAMA 1999;282:267-70.

28. Tam VC, Knowles SR, Cornish PL, Fine N, Marchesano R, Etchells EE. Frequency, type and clinical

importance of medication history errors at admission to hospital: a systematic review. CMAJ

2005;173:510515.

29. Liu M, Hinz ERM, Matheny ME, Denny JC, Schildcrout JS, Miller RA, et al. Comparative analysis of

pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records.

JAMIA 2013;20:420-6.

Page 20 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



21

Tables


Gender

Male 2102 (52.7) -

Female 1883(47.3) -

Hospital type





Service

Medicine 1352(33.9) -

Surgery 1771(44.5) -


Age, years - 43.4 (±19.0)

Length of Hospital Stay, days - 8.1 (±10.2)

Comorbidities (Charlson’s index weight) - 1.1 (±1.4)


Table 2. Overall Incidence of ADEs, potential ADEs and medication errors with low risk t cause harm

Total number

of incidents

=1531


(95% CI)

Crude rate per 1000 patient-days (95%

CI)


Potential ADEs (PADEs) 677 44.2 16.9 (15.7 – 18.3) 21.8 (20.2 – 23.5)



ADEs (Harm) 245 16 6.1 (5.4 – 6.9) 7.9 (6.9 – 8.9)



Medication errors with low risk to cause harm include those medication errors with low risk to cause ADEs or PADEs. ADEs, adverse drug events

Table 3. Classification of ADEs by Hospital Type


stay

ADEs crude rate per 1000 patient- days (95% CI)



(95% CI)

Hospital 1

83 9585 8.7 (6.9-10.6) 977 8.5(6.8-10.4)

Hospital 2

53 9032 5.9 (4.4-7.6) 2033 2.6 (2.1-3.3)

Hospital 3

13 6613 2.1(1.1-3.2) 683 2.1(1.1-3.2)

Hospital4

96 5766 16.6(13.5-20.2) 292 32.9(27.7-38.4)

Hospital 1= Teaching hospital, Hospital 2=Private hospital, Hospital 3= small government hospital, Hospital 4=Large government

hospital


Units ADEs Patient-days, No

ADEs Crude rate per 1000 patient-days (95% CI)



(95% CI)

Medical 66 10767 6.1(4.7-7.7) 1352 4.8(3.8-6.1)

Surgical 29 9310 3.1(2.1-4.4) 1771 1.6(1.1-2.3)

ICU 150 10919 13.7(11.6-16.1) 862 17.4(14.7-20.3)


Page 21 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



22

Table 5. Medication classes involved in ADEs, PADEs and medication errors with low risk to cause harm

Medication classes ADEs, n (%)

(n= 245)

PADEs n (%)

(n= 677)

Medication errors with low risk to cause harm n (%)

(n= 609)

Antibiotics 51(20.8) 212(31.3) 193(31.7)

Anticoagulants 53(21.6) 117(17.3) 92(15.1)

Antihypertensives 49(20) 63(9.3) 61(10)

NSAIDs 11(4.5) 41(6.1) 55(9)

GI-medicines 4(1.6) 43(6.4) 39(6.4)

Antidiabetics 5(2) 32(4.7) 26(4.3)

Steroids 14(5.7) 12(1.8) 17(2.8)

Electrolytes 7(2.9) 19(2.8) 6(1)

Cardiovasculars 4(1.6) 15(2.2) 11(1.8)

Dyslipidemic agents 7(2.9) 16(2.4) 6(1)

Analgesics 4(1.6) 9(1.3) 15(2.5)

Antiasthmatics 5(2) 14(2.1) 6(1)

Antituberculosis 3(1.2) 11(1.6) 7(1.1)

Vitamins 0 8(1.2) 5(0.8)

Antifungals 1(0.5) 4(0.6) 6(1)

Antiseizures 5(2) 3(0.4) 2(0.3)

Antipsychotics 1(0.5) 3(0.4) 6(1)

Thyroid agents 0 5(0.7) 3(0.5)

Antivirals 4(1.6) 2(0.3) 1(0.2)

Antihistamines 1(0.5) 3(0.4) 1(0.2)

Sedatives 4(1.6) 1(0.1) 0

Anticancers 0 3(0.4) 2(0.3)

Others 12(4.9) 41(6.1) 49(8)

Page 22 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



23

Table 6. Interrator reliability of the incident type and their severity and preventability

Severity Agreement % Kappa value

Exclude vs ADEs, PADE or medication error 56.4 0.63

ADEs vs PADE, medication error or exclude 93.6 0.71

PADEs vs ADE, medication error or exclude 70.9 0.62

Medication error vs ADEs, PADE or exclude 93.7 0.67

Preventable vs non-preventable ADEs 92.2 0.68

Fatal vs Life-threatening, serious or significant 100 0.74

Life-threatening vs fatal serious or significant 100 0.63

Serious vs fatal, life-threatening or significant 60.5 0.48

Significant vs fatal, life-threatening or serious 84.2 0.52



95% CI P value Adjusted Odds Ratio

95% CI P value


Age 1.024 1.017 1.032 <0.001 1.012 1.003 1.021 0.009

Number of medications 1.193 1.148 1.240 <0.001 1.062 1.008 1.119 0.023

Charlson’s comorbidity index weight

1.251 1.158 1.352 <0.001 1.041 0.937 1.157 0.452

Length of hospital stay 1.042 1.034 1.051 <0.001 1.025 1.015 1.035 <0.001

Gender (Male)a 0.848 0.642 1.121 0.248 - - - -

ICUb 7.786 5.259 11.528 <0.001 3.276 2.005 5.354 <0.001

Medicineb 2.539 1.664 3.872 <0.001 1.736 1.078 2.796 0.023


b

Page 23 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



215x279mm (300 x 300 DPI)

Page 24 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from



Appendix A: Examples of PADEs

Prescribing

The physician ordered lisinopril, 5 mg tablet, once daily even though the patient was not hypertensive and had no indication for the

drug. The order was intended for another patient and the nurse intercepted the error.

Transcribing

A 74-year old man with diabetes mellitus, hypertension and recurrent urinary tract infections was admitted to the medical ward.

Meropenem, 500 mg intravenously, every eight hours was ordered. In the morning round, the infectious disease consultant verbally

asked the intern to change meropenem to imipenem 500 mg intravenously every six hours. However, the intern mistakenly

transcribed it as meropenem. This error was caught, corrected, and noted as an error in the patient’s medical record.

Dispensing

An order of metoclopramide 10 mg was sent to the pharmacy. The nurse obtained the drug from the pharmacy, but from the

appearance of the solution, she suspected that the preparation was not metoclopramide. The nurse contacted the pharmacy and the

pharmacist found that it was the wrong medication, although the label was stated that it was metoclopramide.

Administering

A nurse handled two capsules for two different patients in Room #8 and Room #9. She almost accidentally gave the wrong

medication (switched) to each patient. However, the patient in Room # 9 knew her medication and she said, “This is not my

medicine,” and the error was intercepted by the patient.

Page 25 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960

on Decem


http://bmjopen.bm

j.com/

BM


jopen-2015-010831 on 12 July 2016. Dow

nloaded from




Section/Topic Item


Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 6

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 5

Objectives 3 State specific objectives, including any prespecified hypotheses 5

Methods

Study design 4 Present key elements of study design early in the paper 6


collection

6

Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up 6



applicable

6

Data sources/

measurement



7


Study size 10 Explain how the study size was arrived at 6


why

8

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 8

(b) Describe any methods used to examine subgroups and interactions 8




Results

Page 26 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960






10

(b) Give reasons for non-participation at each stage 10

(c) Consider use of a flow diagram 24


confounders

10


(c) Summarise follow-up time (eg, average and total amount) 6

Outcome data 15* Report numbers of outcome events or summary measures over time 10



12




Discussion

Key results 18 Summarise key results with reference to study objectives 14

Limitations



15 -16

Generalisability 21 Discuss the generalisability (external validity) of the study results 16

Other information



17





Page 27 of 27


BMJ Open

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960



BMJ Open · Mahmoud, Mansour Ahmed, Yusuf; King Saud University, Medication Safety Research Chair...

Documents

Transcript of BMJ Open · Mahmoud, Mansour Ahmed, Yusuf; King Saud University, Medication Safety Research Chair...