Emergency department narratives for early risk stratification of serious disposition in older adults after falls: A survival modelling study with external validation.

Abstract

Older adults presenting to the emergency department (ED) following a fall represent a clinically heterogeneous population, ranging from those with minor injuries to those requiring urgent intervention. Accurate risk stratification at triage is critical, yet triage decisions are often made before physiological measurements are available. ED narratives documented in free-text fields may encode rich clinical signals collected at ED triage but remain largely underused for decision support. To develop and externally validate a survival model that uses free-text ED narratives to rank older adult fall patients by risk of serious disposition at the point of ED triage, without requiring physiological measurements, to support early resource allocation in high-volume or resource-constrained emergency settings. We conducted a retrospective cohort study using the National Electronic Injury Surveillance System (NEISS). The development cohort included ED visits from 2019-2022 with verified unintentional falls (n=7921). The external validation cohort comprised visits from 2013-2022 from hospitals not included in the development cohort. Text embeddings of processed narratives were used as inputs to an XGBoost-based survival model. The reported time from fall to ED arrival was extracted from narrative fields and used as the event time variable. Model performance was assessed using various metrics, including the Inverse Probability of Censoring Weighting Concordant Index (IPCW C-index). The model achieved an IPCW C-index of 0.776 (95% CI: 0.773-0.779) on the development cohort and 0.724 (95% CI: 0.719-0.728) on the external cohort, demonstrating discrimination above chance. Aggregated LIME analysis identified narrative features associated with high risk of serious disposition included mechanisms of injury and contextual factors. A survival model using only free-text ED narratives achieved good discrimination for serious disposition after geriatric falls, with external validation (IPCW C-index 0.724) supporting generalizability. This narrative-only approach, requiring no physiological measurements, may enable early risk stratification in resource-limited emergency settings. Prospective validation on real-time triage notes is warranted.