Title

The Stroke Assessment of Fall Risk (SAFR): Predictive validity in inpatient stroke rehabilitation

DOI

10.1177/0269215514534276

Document Type

Journal Article

Publication Date

12-26-2014

Publication Title

Clinical Rehabilitation

Volume

28

Issue

12

First Page

1218

Last Page

1224

ISSN

2692155

Keywords

Falls, prediction, rehabilitation, stroke

Abstract

Objective: To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Design and setting: Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Participants: Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Interventions: Not applicable. Main outcome measure(s): Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. Results: A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). Conclusions: An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted.

Open Access

Green Accepted

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