Development of a Fall Risk Score for Older Adults Incorporating Electronic Health Record and Emergency Department Screening Measures

Background Older adults have high rates of falls after Emergency Department (ED) discharge; yet existing screening tools either underperform or are too difficult to deploy. This study aimed to evaluate a parsimonious predictive model for falls within 6 months post‐ED discharge, utilizing both typical electronic health record (EHR) data and brief ED‐based screenings. Methods In a prospective cohort study from September 2023 to May 2024, 412 community‐dwelling adults aged ≥ 60 years who ambulate without assistance were enrolled during ED visits. Baseline data included EHR‐derived variables (e.g., comorbidities, medication use) and ED screens (e.g., living situation, fall history). Participants were followed for 6 months to document fall occurrences. Multivariable LASSO logistic regression models to predict any fall were then constructed: Model 1 (EHR), Model 2 (ED screens), and Model 3 (combined). Model performance was evaluated using discrimination and calibration metrics, including area under the receiver operating characteristic (AUC) curves. Results Of the 356 participants with complete follow‐up, 104 (29.2%) experienced at least one fall. Model 3 demonstrated superior predictive performance (AUC = 0.75) compared to Model 1 (AUC = 0.67) and Model 2 (AUC = 0.71). Significant predictors in the combined model included anemia (OR = 3.19), use of oral hypoglycemics (OR = 2.26), living with less than two other people (OR = 3.79), infrequently leaving home (OR = 1.97), and a history of ≥ 3 falls in the prior 6 months (OR = 12.11). A risk score made up of 9 items (6 EHR; 3 ED screen) categorizing participants as high risk (score 6–25) or low risk (score 0–5) resulted in sensitivity = 64%, specificity = 75%, positive likelihood ratio = 2.54, and negative likelihood ratio = 0.49. Conclusions Integrating EHR data with brief ED‐based screenings enhances the prediction of fall risk among older adults post‐ED discharge. The developed risk score effectively stratifies patients into low versus high risk, facilitating targeted prevention interventions. Further validation in independent cohorts is needed.