James G. Jollis

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.

BACKGROUND: Limited data exist on recent demographic and microbiological changes in infective endocarditis (IE) and the impact of these changes on patient survival. METHODS: Data were collected from all patients with definite or possible IE at Duke University Medical Center, Durham, NC, from 1993 to 1999. Logistic regression analysis was used to identify demographic and microbiological changes that occurred in patients with IE over the study period. The impact of these changes on survival was evaluated using Cox proportional hazards modeling. RESULTS: Among the 329 study patients, rates of hemodialysis dependence, immunosuppression, and Staphylococcus aureus infection increased during the study period (P=.04, P=.008, and P<.001, respectively), while rates of infection due to viridans group streptococci decreased (P=.007). Hemodialysis was independently associated with S aureus infection (odds ratio, 3.1; 95% confidence interval, 1.6-5.9). Patients with S aureus IE had a higher 1-year mortality rate (43.9% vs 32.5%; P=.04) that persisted after adjustment for other illness severity characteristics (hazard ratio, 1.5; 95% confidence interval, 1.03-2.3). CONCLUSIONS: The demographic and microbiological characteristics of IE at our institution have changed over the past decade in ways that suggest a link between medical practice and IE characteristics. Staphylococcus aureus has emerged as a dominant cause of IE, and is an independent predictor of mortality. These findings identify clinical settings that may warrant closer surveillance and more aggressive measures in the identification and prevention of endocarditis.