%0 Journal Article %J Circulation %D 2016 %T Study of Cardiovascular Health Outcomes in the Era of Claims Data: The Cardiovascular Health Study. %A Psaty, Bruce M %A Delaney, Joseph A %A Arnold, Alice M %A Curtis, Lesley H %A Fitzpatrick, Annette L %A Heckbert, Susan R %A McKnight, Barbara %A Ives, Diane %A Gottdiener, John S %A Kuller, Lewis H %A Longstreth, W T %K Blood Glucose %K Cardiovascular Diseases %K Female %K Follow-Up Studies %K Health Surveys %K Hospitalization %K Hospitals, Veterans %K Humans %K Insurance Claim Review %K International Classification of Diseases %K Lipids %K Male %K Managed Care Programs %K Medicare %K Risk Factors %K Sampling Studies %K Treatment Outcome %K United States %X

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.

%B Circulation %V 133 %P 156-64 %8 2016 Jan 12 %G ENG %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/26538580?dopt=Abstract %R 10.1161/CIRCULATIONAHA.115.018610