A CASE-MIX CLASSIFICATION-SYSTEM FOR MEDICAL REHABILITATION

Dissatisfaction with Medicare's current system of paying for rehabilit ation care has led to proposals for a rehabilitation prospective payme nt system, but first a classification system for rehabilitation patien ts must be created. Data for 36,980 patients admitted to and discharge d from 125 rehabilitation facilities between January 1, 1990, and Apri l 19, 1991, were provided by the Uniform Data System for Medical Rehab ilitation. Classification rules were formed using clinical judgment an d a recursive partitioning algorithm. The Functional Independence Meas ure version of the Function Related Groups (FIM-FRGs) uses four predic tor variables: diagnosis leading to disability, admission scores for m otor and cognitive functional status subscales as measured by the Func tional Independence Measure, and patient age. The system contains 53 F RGs and explains 31.3% of the variance in the natural logarithm length of stay for patients in a validation sample. The FIM-FRG classificati on system is conceptually simple and stable when tested on a validatio n sample. The classification system contains a manageable number of gr oups, and may represent a solution to the problem of classifying medic al rehabilitation patients for payment, facility planning, and researc h on the outcomes, quality, and cost of rehabilitation.