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A case-mix classification system for medical rehabilitation
Authors:MG Stineman  JJ Escarce  JE Goin  BB Hamilton  CV Granger  SV Williams
Affiliation:Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia 19104-2676.
Abstract:Dissatisfaction with Medicare's current system of paying for rehabilitation care has led to proposals for a rehabilitation prospective payment system, but first a classification system for rehabilitation patients must be created. Data for 36,980 patients admitted to and discharged from 125 rehabilitation facilities between January 1, 1990, and April 19, 1991, were provided by the Uniform Data System for Medical Rehabilitation. Classification rules were formed using clinical judgment and a recursive partitioning algorithm. The Functional Independence Measure version of the Function Related Groups (FIM-FRGs) uses four predictor variables: diagnosis leading to disability, admission scores for motor and cognitive functional status subscales as measured by the Functional Independence Measure, and patient age. The system contains 53 FRGs and explains 31.3% of the variance in the natural logarithm length of stay for patients in a validation sample. The FIM-FRG classification system is conceptually simple and stable when tested on a validation sample. The classification system contains a manageable number of groups, and may represent a solution to the problem of classifying medical rehabilitation patients for payment, facility planning, and research on the outcomes, quality, and cost of rehabilitation.
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