title: Validation of FIM-MDS crosswalk conversion algorithm.
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.
authors.affiliation: Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611, USA. inga-wang@northwestern.edu
authors.forename: Ying-Chih
authors.initials: YC
authors.lastname: Wang
authors.forename: Katherine L
authors.initials: KL
authors.lastname: Byers
authors.forename: Craig A
authors.initials: CA
authors.lastname: Velozo
mesh_terms: D000203:Activities of Daily Living; D000465:Algorithms; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D008297:Male; D008499:Medical Records; D051346:Mobility Limitation; D012189:Retrospective Studies; D014481:United States; D014493:United States Department of Veterans Affairs