Signal · Frailty
Validated triage tool for same-day emergency care outperforms existing scores in a deprived urban population
A retrospective diagnostic study of 152,877 emergency department attendances across three Birmingham hospitals derives and internally validates a new triage tool for identifying patients suitable for same-day emergency care, outperforming existing prediction scores.
A retrospective diagnostic study across three hospitals in a deprived urban UK setting analysed 152,877 unplanned emergency department attendances by adults needing internal medicine assessment, and derived a new prediction tool for identifying patients suitable for same-day emergency care (SDEC) Primary Study. The two existing scores currently in clinical use, the Glasgow Admission Prediction Score (GAPS) and the Ambulatory Score (AmbS), showed only moderate discrimination (AUROC 0.741 and 0.733 respectively). The new SDEC Triage Tool (SDEC-T), which combines elements of GAPS, AmbS, the National Early Warning Score 2 (NEWS2) and presenting complaint, achieved an AUROC of 0.850 on internal validation.
This is the strongest available evidence benchmark for same-day-care triage accuracy to date, but it remains an internally validated tool: the authors have not yet reported external validation in an independent population, and the study’s median patient age of 58 means the tool has not been tested specifically against a frailty-stratified (Clinical Frailty Scale) cohort.
Stakeholders involved in the tool’s development judged it acceptable and suitable for deployment across hospitals with varying digital maturity, since it draws on variables already recorded in standard clinical data rather than requiring new data collection. For services planning same-day emergency care capacity, this represents a directly transferable candidate triage instrument, though local validation — particularly for older, frailer patients — would be a prerequisite before adoption.
Sources
- Atkin C, Gallier S, Hodson J, et al. Enhancing the accuracy of a multivariable prediction model to identify medical patients suitable for same day emergency care services. BMJ Health & Care Informatics. 2026;33(1). doi:10.1136/bmjhci-2024-101382 PMID 42575541
