Improving the Performance of Clinical Decision Support for Early Detection of Sepsis: A Retrospective Observational Cohort Study

@article{Li2019ImprovingTP,
  title={Improving the Performance of Clinical Decision Support for Early Detection of Sepsis: A Retrospective Observational Cohort Study},
  author={Ling Li and Kasun Rathnayake and Malcolm Green and Mary Fullick and Amith L Shetty and Scott R. Walter and Jeffrey Braithwaite and Harvey Lander and Johanna I. Westbrook},
  journal={Studies in health technology and informatics},
  year={2019},
  volume={264},
  pages={
          679-683
        }
}
Sepsis remains a significant global health problem. It is a life-threatening, but poorly defined and recognized condition. Early recognition and intervention are essential to optimize patient outcomes. Automated clinical decision support systems (CDS) may be particularly beneficial for early detection of sepsis. The aim of this study was to use retrospective data to develop and evaluate seven revised versions of an electronic sepsis alert rule to assess their performance in detecting sepsis… 

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