Validation of the Casa Colina Fall Risk Assessment Scale in Predicting Falls in Inpatient Rehabilitation Facilities.
Autor: Kaplan, Stephanie E.; Cournan, Michele; Gates, Jason; Thorne, Melanie; Jones, Annette; Ponce, Tom; Rosario, Emily R.
Publication year: 2020
Rehabilitation nursing : the official journal of the Association of Rehabilitation Nurses
issn:2048-7940 0278-4807
doi: 10.1097/rnj.0000000000000180
Abstract:
OBJECTIVE: The aim of this study was to assess the validity, efficacy, and generalizability of a fall risk assessment tool created specifically for inpatient rehabilitation facilities (IRFs). DESIGN: The Casa Colina Falls Risk Assessment Scale (CCFRAS) was assessed both retrospectively and prospectively on consecutive patients at three IRFs to determine the sensitivity and specificity of this tool in predicting fall risk. SETTING: The setting was in three IRFs. PARTICIPANTS: Individuals admitted to three IRFs participated in the study. MAIN OUTCOMES MEASURES: 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. RESULTS: The sensitivity and specificity of the CCFRAS ranged from 75% to 80% and from 47% to 70%, respectively, for the different IRFs. Using a logistic regression analysis, we identified the optimal CCFRAS cutoff score for identifying high-risk patients at each individual facility, thus improving the specificity to 70%-79%. CONCLUSION: Multisite evaluation of this assessment tool indicates that the CCFRAS is effective and broadly generalizable for predicting patients at high risk for falling.
Language: eng
Rights:
Pmid: 30747793
Tags: Humans; Aged; Female; Male; Middle Aged; Retrospective Studies; Oklahoma; Logistic Models; New York; Accidental Falls/*prevention & control/statistics & numerical data; Rehabilitation Centers/organization & administration/statistics & numerical data; Delaware; Risk Assessment/methods/*standards/statistics & numerical data
Link: https://pubmed.ncbi.nlm.nih.gov/30747793/
