Early Warning Scores With and Without Artificial Intelligence

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Authors

Dana P. Edelson · University of Chicago

Matthew M. Churpek · University of Wisconsin–Madison

Kyle A. Carey · University of Chicago

Zhenqiu Lin · Yale University

Chenxi Huang · Yale University

Jonathan Siner · Yale University

Jennifer Johnson ·

Abstract

In this cohort study of inpatient encounters, eCART outperformed the other AI and non-AI scores, identifying more deteriorating patients with fewer false alarms and sufficient time to intervene. NEWS, a non-AI, publicly available early warning score, significantly outperformed EDI. Given the wide variation in accuracy, additional transparency and oversight of early warning tools may be warranted.

Topics & Keywords

Sepsis Diagnosis and Treatment Cardiac, Anesthesia and Surgical Outcomes Hemodynamic Monitoring and Therapy

UN Sustainable Development Goals

Peace, Justice and strong institutions

Publication Details

Published in: JAMA Network Open

Volume 7, Issue 10, pp. e2438986-e2438986

DOI: 10.1001/jamanetworkopen.2024.38986

Field-Weighted Citation Impact: 21.44