OBJECTIVE: To present a new version (2.0) of the Functional Independence Measure-Function Related Group (FIM-FRG) case-mix measure. DATA SOURCE/STUDY SETTING: 85,447 patient discharges from 252 freestanding facilities and hospital units contained in the 1992 Uniform Data System for Medical Rehabilitation. STUDY DESIGN: Patient impairment category, functional status at admission to rehabilitation, and patient age were used to develop groups that were homogeneous with respect to length of stay. Within each impairment category patients were randomly assigned to one data set to create the system (through recursive partitioning) or a second set for validation. Clinical and statistical criteria were used to increase the percentage of patients classified, expand the impairment categories of FIM-FRGs Version 1.1, and evaluate the incremental predictive ability of coexisting medical diagnoses. Predictive stability over time was evaluated using 1990 discharges. PRINCIPAL FINDINGS: In Version 2.0, the percentage of patients classified was increased to 92 percent. Version 2.0 includes two new impairment categories and separate groups for patients admitted to rehabilitation for evaluation only. Coexisting medical diagnoses did not improve LOS prediction. The system explains 31.7 percent of the variance in the logarithm of LOS in the 1992 validation sample, and 31.0 percent in 1990 discharges. CONCLUSIONS: FIM-FRGs Version 2.0 includes more specific impairment categories, classifies a higher percentage of patient discharges, and appears sufficiently stable over time to form the basis of a payment system for inpatient medical rehabilitation.
OBJECTIVE: To present a new version (2.0) of the Functional Independence Measure-Function Related Group (FIM-FRG) case-mix measure. DATA SOURCE/STUDY SETTING: 85,447 patient discharges from 252 freestanding facilities and hospital units contained in the 1992 Uniform Data System for Medical Rehabilitation. STUDY DESIGN:Patient impairment category, functional status at admission to rehabilitation, and patient age were used to develop groups that were homogeneous with respect to length of stay. Within each impairment category patients were randomly assigned to one data set to create the system (through recursive partitioning) or a second set for validation. Clinical and statistical criteria were used to increase the percentage of patients classified, expand the impairment categories of FIM-FRGs Version 1.1, and evaluate the incremental predictive ability of coexisting medical diagnoses. Predictive stability over time was evaluated using 1990 discharges. PRINCIPAL FINDINGS: In Version 2.0, the percentage of patients classified was increased to 92 percent. Version 2.0 includes two new impairment categories and separate groups for patients admitted to rehabilitation for evaluation only. Coexisting medical diagnoses did not improve LOS prediction. The system explains 31.7 percent of the variance in the logarithm of LOS in the 1992 validation sample, and 31.0 percent in 1990 discharges. CONCLUSIONS: FIM-FRGs Version 2.0 includes more specific impairment categories, classifies a higher percentage of patient discharges, and appears sufficiently stable over time to form the basis of a payment system for inpatient medical rehabilitation.
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