This before-and-after quasi-experimental study assessed the impact of a deep-learning model (COMPOSER) on sepsis patient outcomes in two emergency departments. The deployment of COMPOSER was significantly associated with a 1.9% absolute reduction in in-hospital sepsis mortality (17% relative decrease), a 5.0% absolute increase in sepsis bundle compliance (10% relative increase), and a 4% reduction in 72-h SOFA change. These findings suggest that COMPOSER's deployment is associated with improved sepsis care and survival.
Publisher
npj Digital Medicine
Published On
Jan 23, 2024
Authors
Aaron Boussina, Supreeth P. Shashikumar, Atul Malhotra, Robert L. Owens, Robert El-Kareh, Christopher A. Longhurst, Kimberly Quintero, Allison Donahue, Theodore C. Chan, Shamim Nemati, Gabriel Wardi
Tags
sepsis
deep learning
COMPOSER
emergency department
patient outcomes
mortality reduction
healthcare innovation
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