Evaluation of a machine learning capability for a clinical decision support system to enhance antimicrobial stewardship programs.

Journal: Artificial intelligence in medicine
Published Date: Feb 22, 2016

Abstract

OBJECTIVE: Antimicrobial stewardship programs have been shown to limit the inappropriate use of antimicrobials. Hospitals are increasingly relying on clinical decision support systems to assist in the demanding prescription reviewing process. In previous work, we have reported on an emerging clinical decision support system for antimicrobial stewardship that can learn new rules supervised by user feedback. In this paper, we report on the evaluation of this system.

Authors

  • Mathieu Beaudoin
    Department of Computer Science, Université de Sherbrooke, 2500 boul. de l'Université, Sherbrooke, Québec, Canada J1K 2R1. Electronic address: mathieu.beaudoin@usherbrooke.ca.
  • Froduald Kabanza
    Department of Computer Science, Université de Sherbrooke, 2500 boul. de l'Université, Sherbrooke, Québec, Canada J1K 2R1. Electronic address: froduald.kabanza@usherbrooke.ca.
  • Vincent Nault
    Department of Microbiology and Infectious Diseases, Université de Sherbrooke, 3001 12e Avenue Nord, Sherbrooke, Québec, Canada J1H 5N4. Electronic address: vincent.nault@usherbrooke.ca.
  • Louis Valiquette
    Department of Microbiology and Infectious Diseases, Université de Sherbrooke, 3001 12e Avenue Nord, Sherbrooke, Québec, Canada J1H 5N4. Electronic address: louis.valiquette@usherbrooke.ca.

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