Machine Learning–Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

Key Points Question Do machine learning approaches improve the ability to predict clinical outcomes and disposition of children at emergency department triage? Findings In this prognostic study of a nationally representative sample of 52 037 emergency department visits by children, machine learning–based triage models had better discrimination ability for clinical outcomes and disposition compared with the conventional triage approaches, with a higher sensitivity for the critical care outcome and higher specificity for the hospitalization outcome. Meaning Machine learning may improve the prediction ability of triage approaches and could be used to reduce undertriage of critically ill children and to improve resource allocation in emergency departments.