Prediction of hospital readmission for heart failure: development of simple risk score based on administrative dat

OBJECTIVES The purpose of this study was to develop convenient and inexpensive method for identifying an individual’s risk for hospital readmission for congestive heart failure (CHF) using information derived exclusively from administrative dat sources and available at the time of an index hospital discharge. BACKGROUND Rates of readmission are high after hospitalization for CHF. The significant determinants of rehospitalization are debated. METHODS Administrative information on all 1995 hospital discharges in New York State which were assigned International Classification of Diseases–9–Clinical Modification codes indicative of CHF in the principal diagnosis position were obtained. The following were compared among hospital survivors who did and did not experience readmission: demographics, comorbid illness, hospital type and location, processes of care, length of stay and hospital charges. RESULTS total of 42,731 black or white patients were identified. The subgroup of 9,112 patients (21.3%) who were readmitted were distinguished by greater proportion of blacks, higher prevalence of Medicare and Medicaid insurance, more comorbid illnesses and the use of telemetry monitoring during their index hospitalization. Patients treated at rural hospitals, those discharged to skilled nursing facilities and those having echocardiograms or cardiac catheterization were less likely to be readmitted. Using multiple regression methods, simple methodology was devised that segregated patients into low, intermediate and high risk for readmission. CONCLUSIONS Patient characteristics, hospital features, processes of care and clinical outcomes may be used to estimate the risk of hospital readmission for CHF. However, some of the variation in rehospitalization risk remains unexplained and may be the result of discretionary behavior by physicians and patients.