Abstract
Agarwal V, McRae MP, Bhardwaj A, Teasell RW. A model to aid in the prediction of discharge location for stroke rehabilitation patients. Arch Phys Med Rehabil 2003;84:1703–9. Objective To determine which demographic and medical factors recorded on admission to a rehabilitation unit best predict discharge accommodation outcomes. Design Retrospective chart review. Setting Inpatient rehabilitation unit in an academic hospital in southwestern Ontario, Canada. Participants One hundred four stroke patients (54 women, 50 men; mean age, 72.0y) admitted to the rehabilitation unit over a 4-year period. Interventions All patients underwent evaluations by the physical therapy, occupational therapy, social work, speech pathology, and psychology departments. Patients were divided into 2 groups: (1) no change in premorbid accommodation and (2) change in premorbid accommodation. Main outcome measures Demographic, clinical, and housing information (premorbid, discharge) and functional data (FIM™ instrument, Chedoke-McMaster Stroke Assessment [CMSA] Impairment Inventory, Berg Balance Scale [BBS]) were recorded for each patient. Results Of 104 patients, 24 were discharged with a change in premorbid accommodation. Change in discharge location was significantly associated with age, gender, and the presence of premorbid social support ( P<.01), but not with type of premorbid living arrangement. Statistically significant differences were noted between total FIM scores ( P<.001), BBS scores ( P<.001), and the postural component of the CMSA Impairment Inventory ( P<.03). A logistic regression model, predicting 67% of the variance, was created to predict discharge accommodations. Conclusions Patients admitted to the rehabilitation unit can be scored to obtain their predicted chance of being discharged with a change from their premorbid accommodations. The equation is relatively easy to calculate and is based on data that are commonly collected in rehabilitation.
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