Logo for the Journal of Rehab R and D

Volume 45 Number 7, 2008
   Pages 1065 — 1076

Abstract - Validation of FIM-MDS crosswalk conversion algorithm

Ying-Chih Wang, PhD;1* Katherine L. Byers, PhD;2 Craig A. Velozo, PhD, OTR/L3-4

1Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL; 2Department of Clinical Administration and Rehabilitation Counseling, Texas Tech University Health Sciences Center, Lubbock, TX; 3Department of Veterans Affairs Health Services Research and Development (R&D) and Rehabilitation R&D,
Rehabilitation Outcomes Research Center, North Florida/South Georgia Veterans Health System, Gainesville, FL; 4Department of Occupational Therapy, University of Florida, Gainesville, FL

Abstract — In this study, we performed a validation analysis of a crosswalk that converts Functional Independence Measure (FIM) scores to Minimum Data Set (MDS) scores and vice versa in order to achieve score compatibility. Data from 2,130 patients were obtained from the Department of Veteran Affairs' Austin Automation Center. The conversion algorithm was tested at the (1) individual patient level, (2) classification level, and (3) facility level. The validity testing resulted in mixed findings. The mean MDS-derived FIM (FIMc) scores were within 1.3 and 0.1 points of the mean actual FIM (FIMa) scores for the motor and cognition scales, respectively. Kappa statistics demonstrated a fair to substantial (0.37-0.66) strength of agreement between functional-related group classifications generated from the FIMa and FIMc scores. Four of the five facilities had an average point difference of 2.4 between the mean FIMa and FIMc scores. While the sample distributions were similar, individual score comparisons fell short of expectations. Only 37% to 67% of the FIMc scores were within 5 points of the FIMa scores. The crosswalk algorithm demonstrated a convenient way to achieve score comparisons across different rehabilitation settings. However, the effectiveness of a single measure or of crosswalk conversions may ultimately depend on the quality of the data.

Key words: Centers for Medicare and Medicaid Services, conversion algorithm, crosswalk, equating, Functional Independence Measure, inpatient rehabilitation facility, Minimum Data Set, patient outcomes, rehabilitation, skilled nursing facilities.

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