Archives of Rehabilitation Research and Clinical Translation (Dec 2022)
Casa Colina Fall Risk Assessment Scale—Revised: Predicting Falls in Inpatient Rehabilitation Facilities
Abstract
Objective: To revise the Casa Colina Fall risk assessment scale (CCFRAS) using the new Medicare standards required functional ability quality measures and to assess the sensitivity and specificity of this revised fall risk assessment tool. Design: The Casa Colina Fall risk assessment scale—revised (CCFRAS-R) was assessed both retrospectively and prospectively on consecutive patients at 3 inpatient rehabilitation facilities (IRFs) to determine the sensitivity and specificity of this tool in predicting fall risk. Setting: Three IRFs. Participants: A total of 6253 adult patients (N=6253) admitted to 1 of 3 IRF settings including those with stroke, brain injury, spinal cord injury, and other conditions requiring medical rehabilitation, with mean age of 66 years; 50% were female and 50% were male. Interventions: Not applicable. Main Outcomes: Each IRF quantified the number of falls detected for the patient population under evaluation and determined the site-specific sensitivity and specificity of the CCFRAS-R. Results: Quality measures were analyzed for predicting fall risk using logistic regression analyses and found that impaired toileting hygiene, impaired toilet transfer, impaired chair/bed transfer, and difficulty walking 3 meters were the most significant predictors for falls. The area under the curve was used to determine the cut-off score and new scoring for the revised falls scale. A second data set was used to validate the tool showing a sensitivity and specificity of 0.6 and 0.62, respectively (P=.001). The degree of “agreeability” between the original scale and the revised scale was 0.72. Conclusion: This multi-site data set predicted quality measures for the risk of falling resulting in a revised fall risk assessment scale for IRFs. Evaluation of this revised assessment tool indicates that the CCFRAS-R is effective and broadly generalizable for predicting patients at high risk for falling although the sensitivity and specificity of the tool may vary slightly based on environmental differences and patient acuity.
