Abstract
Objective: The purpose of this secondary data analysis was to identify key factors predictive of falls in hospitals.
Background: Patient falls remain a major concern for hospitals. Falls can increase patient morbidity/mortality and increase legal risk/cost for institutions. While a number of high-risk falls assessments are available, key predictors of falls have not been identified.
Methods: A secondary data analysis was performed on 281,865 high-risk falls assessments collected in a multisite study.
Results: For the total sample, logistic regression analyses demonstrated that 3 factors, falls within the past 6 months (OR=2.98), confusion (odds ratio, 2.05), taking a laxative (odds ratio, 1.54), are strong predictors of falling. Similar results were found for individual hospitals, different units within hospitals, and urban versus rural hospital locations.
Conclusion: Findings suggest that assessments of fall risk should heavily weigh the 3 predictors identified in this study. Another approach would be to intervene based on these predictors.