The following is a summary of “Development of an emergency department triage tool to predict admission or discharge for older adults,” published in the February 2025 issue of International Journal of Emergency Medicine by Abugroun et al.
Older adults (OAs) arrived at Emergency Departments (ED) with complex conditions, necessitating triage models for effective disposition decisions, though existing models often proved inadequate for this group.
Researchers conducted a retrospective study to introduce a triage model that improved early risk stratification and disposition planning for this population.
They analyzed National Hospital Ambulatory Medical Care Survey data (2015–2019) for individuals with ED aged ≥60 years, excluding those who died in the ED or left against medical advice. Key predictors were selected through least absolute shrinkage and selection operator (LASSO) and backward stepwise selection. Model performance was measured using area under the receiver operating characteristic curve (AUC) and calibration plots, while decision curve analysis assessed clinical utility. Risk thresholds (< 0.1, 0.1–0.5, > 0.5) classified individuals into low, moderate, and high-risk groups, ensuring a balance between sensitivity and specificity.
The results showed that out of 13,431 individuals, 3,180 (23.7%) required admission. Key predictors included ambulance arrival, chronic conditions, gastrointestinal bleeding, and abnormal vital signs. The model demonstrated strong discrimination (AUC 0.73) and reliable calibration, confirmed through 10-fold cross-validation (mean AUC 0.73, SD 0.02). Decision curve analysis indicated net benefit across clinically relevant thresholds. At 0.1 and 0.5 thresholds, 18.9% were classified as low-risk (91.2% accuracy) and 7.9% as high-risk (57.7% accuracy). Adjusting thresholds to 0.2 and 0.4 expanded low-risk (55.4%, 87.9% accuracy) and high-risk (14.1%, 53.7% accuracy) groups.
Investigators concluded that this OA-focused risk score, using readily available data, enhanced early discharge, prioritized admissions for high-risk patients, and improved ED care delivery.
Source: intjem.biomedcentral.com/articles/10.1186/s12245-025-00825-3
