Affiliations: Casa Colina Hospital and Centers for Healthcare, Pomona, CA, USA
Correspondence:
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Address for correspondence: Emily R. Rosario, PhD, Director of Research Institute, Casa Colina Hospital and Centers for Healthcare, 255 East Bonita Avenue, Pomona, CA 91767, USA. Tel.: +1 909 596 7733/Ext. 3036; Fax: +1 909 593 0153; E-mail: erosario@casacolina.org
Abstract: BACKGROUND:The goal of this study was to predict the discharge location for stroke patients. OBJECTIVE:To design a tool to assess a community discharge that will assist in development of individualized care plans and discharge planning. METHODS:Patients (N = 407) hospitalized for an acute stroke in an inpatient rehabilitation facility were used for this retrospective study. Admission data from the Functional Independence Measure (FIM) and Simplified Stroke Rehabilitation Assessment of Movement (S-STREAM) were used to determine predictive factors for a community discharge. RESULTS:Logistic regressions and chi-square analyses were used to determine admission factors that predict a community discharge and the cut off score for each predictive variable. The S-STREAM, Motor FIM, Total FIM, FIM Bladder, FIM bed transfer, FIM toilet transfer, FIM bathing, and FIM memory were predictive of a community discharge. A predictive tool with a sensitivity and specificity of 76% and 64% was developed using the combined relative risk scores of the S-Stream, FIM Bladder, FIM Bed Transfer and FIM Memory. CONCLUSIONS:By using outcome data at the time of admission, a discharge destination can be predicted for stroke patients with significant sensitivity and specificity.
Keywords: Stroke, outcome, discharge destination, case management, community discharge
