AI Division faculty publishes in Annals of Emergency Medicine - Improving End-of-Life Screening in the Emergency Department With Collaborative Artificial Intelligence
BIDMC AI Division Faculty, Adrian D. Haimovich MD, PhD, Gabriel Erion-Barner MD, PhD, Larry A. Nathanson MD, and Nathan Shapiro, MD, MPH published in Annals of Emergency Medicine this June 2026. The paper, Improving End-of-Life Screening in the Emergency Department With Collaborative Artificial Intelligence, aimed to compare end-of-life predictions as measured by the physician-answered surprise question (SQ), “Would you be surprised if this patient died in the next 6 months?”), the Geriatric End-of-Life Screening Tool (GEST) artificial intelligence (AI) model, and a new collaborative GEST+SQ model for predicting 6-month mortality in older emergency department (ED) patients.
The study concluded that GEST modestly outperformed the SQ for predicting 6-month mortality. A GEST+SQ collaborative model did not improve discrimination (ROC-AUC) over GEST alone, but improved calibration. Sequential screening using GEST and then the SQ for intermediate-risk patients could decrease physician screening burden by 95% relative to manual, SQ-only screening. Collaborative approaches integrating automated tools with targeted physician input may enhance ED mortality risk assessment while reducing clinician effort.
Haimovich, A. D., Erion-Barner, G., Nathanson, L. A., Cohen, C., Orcutt, R., Desai, S., ... & Schonberg, M. A. (2026). Improving End-of-Life Screening in the Emergency Department With Collaborative Artificial Intelligence. Annals of Emergency Medicine.