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Research ArticleAcute Myocardial Infarction: A Comparison ofthe Risk between Physicians and the General Population

Yen-ting Chen,1 Chien-Cheng Huang,1,2,3,4 Shih-Feng Weng,5,6

Chien-Chin Hsu,1,7 Jhi-Joung Wang,5 Hung-Jung Lin,1,7,8 Shih-Bin Su,9,10,11

How-Ran Guo,2,12 and Chi-Wen Juan13,14

Department of Emergency Medicine, Chi-Mei Medical Center, ainan, aiwan

Department of Environmental and Occupational Health, College of Medicine,National Cheng Kung University, ainan, aiwan

Department of Child Care and Education, Southern aiwan University of Science and echnology, ainan, aiwan Department of Emergency Medicine, Kuo General Hospital, ainan, aiwan Department of Medical Research, Chi-Mei Medical Center, ainan, aiwan Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, aiwan Department of Biotechnology, Southern aiwan University of Science and echnology, ainan, aiwan Department of Emergency Medicine, aipei Medical University, aipei, aiwan Department of Leisure, Recreation and ourism Management, Southern aiwan University of Science and echnology,

ainan, aiwanDepartment of Occupational Medicine, Chi-Mei Medical Center, ainan, aiwan Department of Medical Research, Chi-Mei Medical Center, Liouying, ainan, aiwanDepartment of Occupational and Environmental Medicine, National Cheng Kung University Hospital,

ainan, aiwanDepartment of Emergency Medicine, Kuang-ien General Hospital, aichung, aiwanDepartment of Nursing, Hungkuang University, aichung, aiwan

Correspondence should be addressed to Chi-Wen Juan; [email protected]

Received December ; Revised February ; Accepted February

Academic Editor: Kimimasa obita

Copyright Yen-ting Chen et al. Tis is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Physicians in aiwan have a heavy workload and a stressul workplace, both o which may contribute to cardiovascular disease.However, the risk o acute myocardial inarction (AMI) in physicians is not clear. Tis population-based cohort study used aiwansNational Health Insurance Research Database. We identied , physicians as the case group and randomly selected ,nonmedicalstaff patients as the controlgroup. We useda conditional logistic regression to comparethe AMI risk between physiciansand controls. Subgroup analyses o physician specialty, age, gender, comorbidities, area, and hospital level werealso done. Physicianshave a higher prevalence o HN (.% versus .%, < 0.0001) and hyperlipidemia (.% versus .%, < 0.0001) but alower risk o AMI than did the controls (adjusted odds ratio (AOR): .; % condence interval (CI): ..) afer adjustingor DM, HN, hyperlipidemia, and area. Between medical specialty, age, and area subgroups, differences in the risk or having anAMIwerenonsignicant. Medical centerphysicians hada lowerrisk (AOR: .; %CI: ..)than didlocalclinic physicians.aiwans physicians had higher prevalences o HN and hyperlipidemia, but a lower risk o AMI than did the general population.Medical center physicians had a lower risk than did local clinic physicians. Physicians are not necessary healthier than the generalpublic, but physicians, especially in medical centers, have a greater awareness o disease and greater access to medical care, whichpermits timely treatment and may prevent critical conditions such as AMI induced by delayed treatment.

Hindawi Publishing CorporationBioMed Research InternationalVolume 2015, Article ID 904328, 6 pageshttp://dx.doi.org/10.1155/2015/904328
http://dx.doi.org/10.1155/2015/904328http://dx.doi.org/10.1155/2015/904328

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BioMed Research International

1. Introduction

Tere is a relationship between physician health and qual-ity o care []. Tere are higher risks o medical errors,adverse events, andattentional ailures by physicians who re-

quently work extended shifs []. Te Institute o Medicine

reported that every year between , and , deathsoccur because o iatrogenic errors []. Moreover, it is com-mon or physicians to be reluctant to seek health care rom

their colleagues because they do not want to be embar-rassed or are araid o losing their job or other reasons[]. Consequently, physicians may tend to work through ill-

nesses and provide patients inappropriate care [].

In aiwan, the launch o the National Health Insur-ance (NHI) program dramatically changed the nations health

services industry. Universal health insurance gave all citizensequal access to health care []. By the end o , almost all

(.%) o the countrys eligible population had enrolled in

the NHI []. Because o the increased demand or healthcare,aiwans physicians may have greater workloads than do

physicians in other nations []. A study reported that thecomparison o mean hours o physicians work was h/week

in US; . h/week in European Union; h/week in NewZealand; and h/week in aiwan []. Hal o aiwanese

physicians work more than h/week, .% work as manyas h/week, and that .% need an average o extra workhours or morning meetings, academic research,and teaching

[]. In addition, the increase o lawsuits or malpracticeproducesanothersource o stressor physicians in aiwan[].

Te number o physicians per , people in aiwan was .

in , much less than in Singapore (.), Korea (.), Japan(.), the United States (.), and the United Kingdom (.)[]. Moreover, the availability o NHI has increased thedemand or healthcare in aiwan. For example, the number

o outpatient visits per person increased rom . in to. in [, ]. Te annual number o outpatient visits

per physician in aiwan increased to , in , rom only, in , which indicates that workloads and stress levels

are increasing or physicians in aiwan [,].

One study [] showed that physicians in aiwan are

at higher risks o developing respiratory system and neo-plastic diseases compared with other healthcare workers.

Compared with the general population, however, their riskso hospitalization were lower or all causes and or seven

major disease-specic standardized hospitalization ratios:(i) neoplasms; (ii) endocrine, nutritional, and metabolicdisease and immunity disorders; (iii) mental disorders; (iv)

circulatory system diseases; (v) respiratory system diseases;(vi) genitourinary system diseases; (vii) and musculoskeletal

system and connective tissue diseases. Individual diseaseswithin these seven categories were not provided; thereore,

we wanted to investigate acute myocardial inarction (AMI)in aiwans physicians, in which a stressul workplace was a

signicant risk actor []. We hypothesized that physicianshave a higher risk o AMI than does the general population.

2. Methods

.. Data Sources. aiwans NHI Program, a universal health-care system that covers % o the countrys populationo . million, has one o the largest and most completepopulation-based healthcare claims datasets in the world[].

Te NHI Research Database (NHIRD) contains encryptedpatient identication numbers, ICD--CM (InternationalClassication o Diseases, Ninth Revision, Clinical Modi-cation) codes or clinical diagnoses and procedures, detailso prescribed drugs, dates o admission and discharge, andbasic sociodemographic inormation, including gender anddate o birth. Inormation on medical personnel (includingphysicians and other healthcare providers) is also availableand includes datelicensed, specialty, work area, hospital level,types o employment, and encrypted identication number,which can be linked to the aorementioned claims data.All the expenses or diabetes mellitus (DM), hypertension(HN), hyperlipidemia, and AMI are covered by NHI.

.. Ethics Statement. Tis study was conducted accordingto the Declaration o Helsinki and was approved by theInstitutional Review Board (IRB) at Chi-Mei Medical Center.Te IRB waived the need or inormed consents (writtenand oral) rom the patients because the dataset used in thisstudy consists o nationwide, unidentiable, secondary datareleased to the public or research. Tis waiver does notadversely affect the rights and welare o the patients.

.. Selection of Cases and Controls. Data on the physicianswere obtained rom the Registry o Medical Personnel (PER),which contained all registered medical staff in . We

then excluded physicians who were dual specialists (e.g., aphysician board certied in internal medicine andemergencymedicine) and physicians who were not specialists (i.e.,residents) (Figure ). We excluded dual specialists becauseo the difficulty involved with assigning them to a specicsubgroup or comparison. We excluded residents becausetheir practice time in individual specialties is short. In thecontrol group, we selected three matches (nonmedical staff)per case rom the Longitudinal Health Insurance Database (LHID), which contains all claims data o onemillion (.% o the total population) beneciaries whowere randomly selected in (Figure ). Tere are nosignicant differences in age, gender, or health care costs

between the LHID and all NHI enrollees. Controls werematched with cases by age, birth year, and gender (Figure ).

We linked to the diagnostic codes through the inpatientand ambulatory care claims databases o the NHI. Commoncomorbidities that might affect the risk o AMI are DM (ICD- code ), HN (ICD- codes ), and hyperlipi-demia (ICD- codes ). Tese three comorbidities werecounted i they were diagnosed in or more ambulatory careclaims coded months beoreJanuary , , index medicalcare date.

.. Exposure Assessment. We compared the risk o AMIbetween physicians and controls by tracing their medical

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Case group

Physicians from2009 Registry

of Medical Personnel (PER)

Control group

LHID2000 database

Matching (1:3): age and gender

Exclusion

(1) Dual specialists

(2) Nonspecialist

Case group

Physicians

Control group

Trace medical history between

Compare AMI risk

Physician subgroup

analysis

N = 28,062 N = 84,186

2007 and 2011

Nonmedical staff

Nonmedical staff from

F : Flowchart or the study. AMI: acute myocardial inarction;LHID: Longitudinal Health Insurance Database.

histories between and (Figure ). AMI was identi-ed using a computerized algorithm that included the ICD-code o .

.. Physician Subgroup Analysis. We also analyzed the sub-groups o physicians or specialty, age, gender, geographicalarea, comorbidities, and hospital level (Figure ). Te special-ists who practice in emergency and critical care (i.e., internal

medicine, surgery, obstetrics and gynecology, pediatrics, andemergency medicine) may have a higher risk o havingan AMI because they lead more stressul lives. Tereore,we divided physicians into six subgroups or comparison:internal medicine, surgery, obstetrics and gynecology, pedi-atrics, emergency medicine, and others (e.g., dermatologyand amily medicine).

.. Statistical Analyses. Differences in baseline characteris-tics and comorbid variables between the two groups wereevaluated using Students test or continuous variables and

Pearson 2 tests or categorical variables. We used conditionallogistic regression to obtain the odds ratio (OR) o AMI

between physicians and controls. Moreover, or the physi-cian subgroup analysis, an unconditional multiple logisticalregression was used to explore the risk o AMI in the differentspecialties. SAS .. or Windows (SAS Institute, Cary, NC,USA) was used or all analyses. Signicance was set at .

, (.) , (.)

, (.) , (.)

, (.) , (.)

Age (years) .. .. >.

Gender >.

Male , (.) , (.)

Female , (.) , (.)

Comorbidity

DM

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: Te risk or an AMI between physicians and controls (conditional logistical regression analysis).

Group Number (%) Crude OR (% CI) value Adjusted OR (% CI) value

Physicians (n= ,) (.) . (..) . . (..)

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: Te risk or an AMI between physician subgroups (condi-tional logistical regression analysis).

Variable Number (%) Adjusted OR

(% CI)

Specialty

Internal medicine (.) . (..)

Surgery (.) . (..)

Obstetrics and gynecology (.) . (..)

Pediatrics (.) . (..)

Emergency medicine

Others (.) .

Age (years)

(.) .

(.) . (..)

(.) . (..)

Gender

Male (.)

Female

Comorbidity

DM

Yes (.) . (..)

No (.) .

HN

Yes (.) .

(..)

No (.) .

Hyperlipidemia

Yes (.) . (..)

No (.) .Geographical area

North (.) .

Central (.) . (..)

South (.) . (..)

East (.) . (..)

Level o hospital employed in

Medical Center (.) .

(..)

Regional hospital (.) .

(..)

Local hospital (.) . (..)

Local clinic (.) .Adjusted by age, DM, HN, hyperlipidemia, geographical area, and level ohospital employed in. AMI: acute myocardial inarction; OR: odds ratio; CI:condence interval; DM: diabetes mellitus; HN: hypertension. value

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Acknowledgments

Tis study was supported by Grants CMFHR romthe Chi-Mei Medical Center. Tis study is based in part ondata rom the aiwan National Health Insurance ResearchDatabase provided by the National Health Insurance Admin-istration, Ministry o Health and Welare, and managedby National Health Research Institutes (Register numberNHIRD-- and number NHIRD--). Te authorsthank Bill Franke or his invaluable advice and editorialassistance.

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