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


METHODS
Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital.


METHODS
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.


METHODS
Not applicable.


METHODS
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.
UPMC Rehabilitation Institute, Pittsburgh, PA, USA Centers for Rehab Services, Pittsburgh, PA, USA breisingertp@upmc.edu.
Terry P
TP
Breisinger
Department of Occupational Therapy, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA, USA Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Elizabeth R
ER
Skidmore
Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Christian
C
Niyonkuru
Department of Occupational Therapy, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA, USA.
Lauren
L
Terhorst
UPMC Rehabilitation Institute, Pittsburgh, PA, USA University of Pittsburgh School of Nursing, Pittsburgh, PA, USA.
Grace B
GB
Campbell
D000058:Accidental Falls / Q000517:prevention & control* / Q000706:statistics & numerical data; D017677:Age Distribution; D019540:Area Under Curve; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009730:Nursing Assessment; D011237:Predictive Value of Tests; D011446:Prospective Studies; D058996:Quality Improvement; D012372:ROC Curve; D012047:Rehabilitation Centers; D018570:Risk Assessment / Q000145:classification* / Q000379:methods; D020521:Stroke / Q000145:classification / Q000150:complications*; D000071939:Stroke Rehabilitation
Falls; prediction; rehabilitation; stroke