Bruce M Psaty1, Joseph A Delaney2, Alice M Arnold2, Lesley H Curtis2, Annette L Fitzpatrick2, Susan R Heckbert2, Barbara McKnight2, Diane Ives2, John S Gottdiener2, Lewis H Kuller2, W T Longstreth2. 1. From Cardiovascular Health Research Unit, Department of Medicine (B.M.P.), Department of Epidemiology (B.M.P., J.A.D., S.R.H.), Department of Health Services (B.M.P.), Department of Biostatistics (A.M.A., B.M.), Department of Global Health (A.L.F.), Department of Family Medicine (A.L.F.), and Department of Neurology (W.T.L.), University of Washington, Seattle; Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P., S.R.H.); Department of Medicine, Duke University, Durham, NC (L.H.C.); Department of Epidemiology, University of Pittsburgh, PA (D.I., L.H.K.); and Department of Medicine, University of Maryland, Baltimore (J.S.G.). psaty@u.washington.edu. 2. From Cardiovascular Health Research Unit, Department of Medicine (B.M.P.), Department of Epidemiology (B.M.P., J.A.D., S.R.H.), Department of Health Services (B.M.P.), Department of Biostatistics (A.M.A., B.M.), Department of Global Health (A.L.F.), Department of Family Medicine (A.L.F.), and Department of Neurology (W.T.L.), University of Washington, Seattle; Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P., S.R.H.); Department of Medicine, Duke University, Durham, NC (L.H.C.); Department of Epidemiology, University of Pittsburgh, PA (D.I., L.H.K.); and Department of Medicine, University of Maryland, Baltimore (J.S.G.).
Abstract
BACKGROUND: Increasingly, the diagnostic codes from administrative claims data are being used as clinical outcomes. METHODS AND RESULTS: Data from the Cardiovascular Health Study (CHS) were used to compare event rates and risk factor associations between adjudicated hospitalized cardiovascular events and claims-based methods of defining events. The outcomes of myocardial infarction (MI), stroke, and heart failure were defined in 3 ways: the CHS adjudicated event (CHS[adj]), selected International Classification of Diseases, Ninth Edition diagnostic codes only in the primary position for Medicare claims data from the Center for Medicare & Medicaid Services (CMS[1st]), and the same selected diagnostic codes in any position (CMS[any]). Conventional claims-based methods of defining events had high positive predictive values but low sensitivities. For instance, the positive predictive value of International Classification of Diseases, Ninth Edition code 410.x1 for a new acute MI in the first position was 90.6%, but this code identified only 53.8% of incident MIs. The observed event rates for CMS[1st] were low. For MI, the incidence was 14.9 events per 1000 person-years for CHS[adj] MI, 8.6 for CMS[1st] MI, and 12.2 for CMS[any] MI. In general, cardiovascular disease risk factor associations were similar across the 3 methods of defining events. Indeed, traditional cardiovascular disease risk factors were also associated with all first hospitalizations not resulting from an MI. CONCLUSIONS: The use of diagnostic codes from claims data as clinical events, especially when restricted to primary diagnoses, leads to an underestimation of event rates. Additionally, claims-based events data represent a composite end point that includes the outcome of interest and selected (misclassified) nonevent hospitalizations.
BACKGROUND: Increasingly, the diagnostic codes from administrative claims data are being used as clinical outcomes. METHODS AND RESULTS: Data from the Cardiovascular Health Study (CHS) were used to compare event rates and risk factor associations between adjudicated hospitalized cardiovascular events and claims-based methods of defining events. The outcomes of myocardial infarction (MI), stroke, and heart failure were defined in 3 ways: the CHS adjudicated event (CHS[adj]), selected International Classification of Diseases, Ninth Edition diagnostic codes only in the primary position for Medicare claims data from the Center for Medicare & Medicaid Services (CMS[1st]), and the same selected diagnostic codes in any position (CMS[any]). Conventional claims-based methods of defining events had high positive predictive values but low sensitivities. For instance, the positive predictive value of International Classification of Diseases, Ninth Edition code 410.x1 for a new acute MI in the first position was 90.6%, but this code identified only 53.8% of incident MIs. The observed event rates for CMS[1st] were low. For MI, the incidence was 14.9 events per 1000 person-years for CHS[adj] MI, 8.6 for CMS[1st] MI, and 12.2 for CMS[any] MI. In general, cardiovascular disease risk factor associations were similar across the 3 methods of defining events. Indeed, traditional cardiovascular disease risk factors were also associated with all first hospitalizations not resulting from an MI. CONCLUSIONS: The use of diagnostic codes from claims data as clinical events, especially when restricted to primary diagnoses, leads to an underestimation of event rates. Additionally, claims-based events data represent a composite end point that includes the outcome of interest and selected (misclassified) nonevent hospitalizations.
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