Prediction of hospital readmission for heart failure: Development of a simple risk score based on administrative data

Citation
Ef. Philbin et Tg. Disalvo, Prediction of hospital readmission for heart failure: Development of a simple risk score based on administrative data, J AM COL C, 33(6), 1999, pp. 1560-1566
Citations number
32
Categorie Soggetti
Cardiovascular & Respiratory Systems","Cardiovascular & Hematology Research
Journal title
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
ISSN journal
07351097 → ACNP
Volume
33
Issue
6
Year of publication
1999
Pages
1560 - 1566
Database
ISI
SICI code
0735-1097(199905)33:6<1560:POHRFH>2.0.ZU;2-B
Abstract
OBJECTIVES The purpose of this study waste develop a convenient and inexpensive method for identifying an individual's risk for hospital readmission for congesti ve heart failure (CHF) using information derived exclusively from administr ative data sources and available at the time of an index hospital discharge . BACKGROUND Rates of readmission are high after hospitalization for CHF. The significan t determinants of rehospitalization are debated. METHODS Administrative information on all 1995 hospital discharges in New York Stat e which were. assigned International Classification of Diseases-9-Clinical Modification codes indicative of CHF in the principal diagnosis position we re obtained. The following were compared among hospital survivors who did a nd did not experience readmission: demographics, comorbid illness, hospital type and location, processes of care, length of stay and hospital charges. RESULTS A total of 42,731 black or white Patients were identified. The subgroup of 9,112 patients (21.3%) who were readmitted were distinguished by a greater proportion of blacks, a higher prevalence of Medicare and Medicaid insuranc e, more comorbid illnesses and the use of telemetry monitoring during their index hospitalization. Patients treated at rural hospitals, those discharg ed to skilled nursing facilities and those having echocardiograms or cardia c catheterization were less likely to be readmitted. Using multiple regress ion methods, a simple methodology was devised that segregated patients into low, intermediate and high risk for readmission. CONCLUSION 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 unexplaine d and may be the result of discretionary behavior by physicians and patient s. (C) 1999 by the American College of Cardiology.