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Updated: May 10, 2026

Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
Predicting and assessing fall risk in an acute inpatient rehabilitation facility
Emily R Rosario1, Stephanie E Kaplan, Sepehr Khonsari
1Casa Colina Hospital for Rehabilitative Medicine, Pomona, California, USA.
Purpose:
Unintentional falls account for 70% of all hospital accidents. The objective of this study was to identify risk factors for falls and develop an assessment tool specific for an inpatient rehabilitation facility setting.
Design/Method:
Diagnosis and Functional Independence Measure (FIM) scores were collected for 174 patients to assess predictors for fall risk. Independent t-tests, chi-square, and logistic regression analysis were conducted to examine differences between fallers and nonfallers.
Findings:
We identified several risk factors for falls including 4 FIM items: toileting, bed transfer, tub/shower transfer, and stairs; and three diagnoses: right stroke, traumatic brain injury, and amputation. From these findings, we completed initial development of a risk assessment tool.
Conclusions:
Evaluation of the tool suggests good specificity with 20%-30% of the patient population identified as high risk and good sensitivity by correctly predicting nearly 90% of patient falls.
Clinical Relevance:
Continued evaluation of this assessment tool is needed to identify effectiveness in predicting patients who are at high risk for falling.
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