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Peer-Reviewed Publication
Appl Clin Inform2026;17(1):107-117.January 1, 2026Journal Article

The Clinical Utility of Traditional and Machine Learning Alarms during the Care of Acutely Ill Patients.

Nicole Rosario1, Henry M Mitchell1, Sylvia Zhang2, Nandakumar Selvaraj2, Xiaozhu Zhang2, Carme Hernandez1,3,4, Stuart R Lipsitz1,5, David M Levine1,5
1Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States.
2Biofourmis, Inc, Boston, Massachusetts, United States.
3Hospital Clínic, Barcelona, Spain.
4University of Barcelona, Barcelona, Spain.
5Harvard Medical School, Boston, Massachusetts, United States.
PubMed PMC DOI PDF

Abstract

Despite low-level evidence, acutely ill patients are often continuously monitored. This creates high false alarm rates and alarm fatigue with unclear clinical effectiveness. We compare metrics, including alarm burden, area under the receiver operator characteristic curve (auROC), sensitivity, and specificity for threshold, score (i.e., National Early Warning Score [NEWS]), and machine learning (ML…

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