Abstract T P122: Functional Independence Measure Scores Predict Self-care Levels Required for Post-acute Stroke Patients Classified by the Long-Term Care Insurance System in Japan: A Multicenter Retrospective Cohort Study

Abstract

Background and purpose: Early prediction of clinical outcomes in stroke patients is socioeconomically important. The aim of this study was to clarify whether Functional Independence Measure (FIM) scores on admission can predict their discharge destinations and future self-care levels required for post-acute stroke patients classified by the Long-Term Care Insurance (LTCI) system, the national insurance plan for care in Japan. Methods: We enrolled post-acute stroke patients admitted to 12 convalescent rehabilitation wards (CRW) from 9 acute stroke centers. A CRW was defined as a specialized ward for intensive rehabilitation to prevent a bedridden state and to promote home rehabilitation by improving ability to perform activities of daily living. We evaluated self-care abilities using FIM scores and modified Rankin Scale (mRS) scores as traditional assessment scales and compared with certified self-care levels within the LTCI system (seven levels; slight impairment to bedridden). We divided patients into those who were discharged home from a CRW and all others. Results: Among 1261 patients (47% female, mean age 75 years), 984 (78%) were discharged home. FIM scores at discharge were significantly correlated with both mRS scores at discharge and certified self-care levels within the LTCI system (P < .001). The cut-off values for home discharge were a FIM score on admission of 50 points and an age of 75 years. On multivariate analysis, FIM scores ≥50 on admission [odds ratio (OR), 95% confidence interval (95% CI); 5.80, 4.30-7.91] and age <75 years (2.16, 1.60-2.95) were independently associated with home discharge. Conclusions: FIM scores in post-acute stroke patients can predict self-care levels within the LTCI system. Early prediction of self-care levels may promote careful preparation of healthcare planning and improve the efficiency of stroke management.