Predicting discharge destination with admission outcome scores in stroke patients.
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...
| Published in: | NeuroRehabilitation Vol. 37; no. 2; pp. 173 - 180 |
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| Main Authors: | , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
2015
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=114834097&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 114834097 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10538135 3RE jtl: NeuroRehabilitation issn: 10538135 maglogo: N pubinfo: dt: 2015 vid: 37 iid: 2 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 114834097 114834097 114834097 10.3233/NRE-151250 114834097 ppf: 173 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Predicting discharge destination with admission outcome scores in stroke patients. aug: au: Ouellette, D. S. Timple, C. Kaplan, S. E. Rosenberg, S. S. Rosario, E. R. affil: Casa Colina Hospital and Centers for Healthcare, Pomona, CA, USA sug: subj: Discharge Planning Methods Patient Care Patient Admission Evaluation Stroke Diagnosis Neurology Human Patient Assessment Outcomes (Health Care) Communities Data Analysis Community Living Case Management United States Stroke Risk Factors Stroke Complications Functional Assessment Inventory International Classification of Diseases Scales Legislation United States Centers for Medicare and Medicaid Services Chi Square Test ROC Curve Data Analysis Software Middle Age Logistic Regression Middle Aged: 45-64 years ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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