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

Area of Science:

• Gerontology
• Public Health
• Emergency Medicine

Background:

• Older adults experience frequent falls post-Emergency Department (ED) discharge.
• Current fall screening tools in the ED are often underperforming or impractical.
• There is a need for effective, easily deployable fall risk prediction models for this population.

Purpose of the Study:

• To develop and evaluate a parsimonious predictive model for falls within 6 months after ED discharge.
• To assess the utility of combining electronic health record (EHR) data with brief ED-based screenings for fall risk prediction.
• To identify key predictors of falls in older adults following ED visits.

Main Methods:

• A prospective cohort study enrolled 412 community-dwelling adults aged 60+ years post-ED visit.
• Data included EHR variables (comorbidities, medications) and ED screenings (living situation, fall history).
• Multivariable LASSO logistic regression models (EHR-only, ED screen-only, combined) were used to predict falls over 6 months.

Main Results:

• The combined model (EHR + ED screens) showed superior predictive performance (AUC=0.75) compared to EHR-only (AUC=0.67) or ED screen-only (AUC=0.71).
• Key predictors included anemia, use of oral hypoglycemics, living situation, social engagement, and prior fall history.
• A 9-item risk score (6 EHR, 3 ED screen) effectively stratified patients into low (score 0-5) and high (score 6-25) risk categories.

Conclusions:

• Integrating EHR data with brief ED screenings significantly improves the prediction of fall risk in older adults after ED discharge.
• The developed risk score facilitates patient stratification, enabling targeted preventive interventions.
• Further validation of this risk score in independent cohorts is warranted.