Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research.

OBJECTIVE: To determine the suitability of insurance claims information for use in clinical outcomes research in ischemic heart disease. DESIGN: Concordance study of two databases. SETTING: Tertiary care referral center. PATIENTS: A total of 12,937 consecutive patients hospitalized for cardiac catheterization for suspected ischemic heart disease between July 1985 and May 1990. INTERVENTIONS: Two-by-two tables were used to compute overall and kappa measures of agreement comparing clinical versus claims data for 12 important predictors of prognosis in patients with ischemic heart disease. MEASUREMENTS: Kappa statistics (agreement adjusted for chance agreement) were used to quantify agreement rates. RESULTS: Agreement rates between the clinical and claims databases ranged from 0.83 for the diagnosis of diabetes to 0.09 for the diagnosis of unstable angina (kappa values). Claims data failed to identify more than one half of the patients with prognostically important conditions, including mitral insufficiency, congestive heart failure, peripheral vascular disease, old myocardial infarction, hyperlipidemia, cerebrovascular disease, tobacco use, angina, and unstable angina, when compared with the clinical information system. CONCLUSIONS: Our results suggest that insurance claims data lack important diagnostic and prognostic information when compared with concurrently collected clinical data in the study of ischemic heart disease. Thus, insurance claims data are not as useful as clinical data for identifying clinically relevant patient groups and for adjusting for risk in outcome studies, such as analyses of hospital mortality.

Duke Scholars

Author James Gerard Jollis Medicine, Cardiology

Author Elizabeth Ray DeLong Biostatistics & Bioinformatics, Division of Biostatistics

Author Lawrence H. Muhlbaier Biostatistics & Bioinformatics, Division of Biostatistics

Author Daniel Benjamin Mark Medicine, Cardiology