Improving the performance of clinical decision support for early detection of sepsis

a retrospective observational cohort study

Ling Li*, Kasun Rathnayake, Malcolm Green, Mary Fullick, Amith Shetty, Scott Walter, Jeffrey Braithwaite, Harvey Lander, Johanna I. Westbrook

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

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Abstract

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 cases and patient deterioration (in-hospital mortality or ICU admission). Four revised options had higher sensitivity but lower specificity than the original rule. After discussion with clinical experts, two revised options with the highest sensitivity were selected. Further analysis on the number of alerts and time intervals between alerts and patient outcomes was conducted to decide the option to be implemented. This study has provided a data-driven approach to improve the CDS on early detection of sepsis.

Original languageEnglish
Title of host publicationMEDINFO 2019
Subtitle of host publicationHealth and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
EditorsLucila Ohno-Machado, Brigitte Seroussi
Place of PublicationAmsterdam
PublisherIOS Press
Pages679-683
Number of pages5
ISBN (Electronic)9781643680033
ISBN (Print)9781643680026
DOIs
Publication statusPublished - 21 Aug 2019
Event17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France
Duration: 25 Aug 201930 Aug 2019

Publication series

NameStudies in Health Technology and Informatics
Volume264
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference17th World Congress on Medical and Health Informatics, MEDINFO 2019
CountryFrance
CityLyon
Period25/08/1930/08/19

Bibliographical note

Copyright International Medical Informatics Association (IMIA) and IOS Press 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Clinical Decision Support Systems
  • Early Diagnosis
  • Sepsis

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    Li, L., Rathnayake, K., Green, M., Fullick, M., Shetty, A., Walter, S., ... Westbrook, J. I. (2019). Improving the performance of clinical decision support for early detection of sepsis: a retrospective observational cohort study. In L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 679-683). (Studies in Health Technology and Informatics; Vol. 264). Amsterdam: IOS Press. https://doi.org/10.3233/SHTI190309