Predictors of readmission among elderly survivors of admission with heart failure,☆☆,

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Abstract

Background Readmission rates for patients discharged with heart failure approach 50% within 6 months. Identifying factors to predict risk of readmission in these patients could help clinicians focus resource-intensive disease management efforts on the high-risk patients. Methods The study sample included patients 65 years of age or older with a principal discharge diagnosis of heart failure who were admitted to 18 Connecticut hospitals in 1994 and 1995. We obtained patient and clinical data from medical record review. We determined outcomes within 6 months after discharge, including all-cause readmission, heart failure–related readmission, and death, from the Medicare administrative database. We evaluated 2176 patients, including 1129 in the derivation cohort and 1047 in the validation cohort. Results Of 32 patient and clinical factors examined, 4 were found to be significantly associated with readmission in a multivariate model. They were prior admission within 1 year, prior heart failure, diabetes, and creatinine level >2.5 mg/dL at discharge. The event rates according to number of risk predictors were similar in the derivation and the validation sets for all outcomes. In the validation cohort, rates for all-cause readmission and combined readmission or death were 26% and 31% in patients with no risk predictors, 48% and 54% in patients with 1 or 2 risk predictors, and 59% and 65% in patients with 3 or all risk predictors. Conclusions Few patient and clinical factors predict readmission within 6 months after discharge in elderly patients with heart failure. Although we were unable to identify a group of patients at very low risk, a group of high-risk patients were identified for whom resource-intensive interventions designed to improve outcomes may be justified. (Am Heart J 2000;139:72-7.)

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The analyses on which this publication is based were performed under contract number 500-96-P549, titled “Utilization and Quality Control Peer Review Organization for the State of Connecticut,” sponsored by the Health Care Financing Administration, Department of Health and Human Services. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. The author assumes full responsibility for the accuracy and completeness of the ideas presented. This article is a direct result of the Health Care Quality Improvement Program initiated by the Health Care Financing Administration, which has encouraged identification of quality improvement projects derived from analysis of patterns of care, and therefore required no special funding on the part of this Contractor. Ideas and contributions to the author concerning experience in engaging with issues presented are welcomed.

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Reprint requests: Harlan M. Krumholz, MD, Yale University School of Medicine, 333 Cedar St, Box 208025, New Haven, CT 06520-8025. E-mail: [email protected]

0002-8703/2000/$12.00 + 0   4/1/100183