A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Nov 1, 2020

Abstract

OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.

Authors

  • Jennifer Corny
    Pharmacy Department, Groupe Hospitalier Paris Saint Joseph, Paris, France.
  • Asok Rajkumar
    Pharmacy Department, Groupe Hospitalier Paris Saint Joseph, Paris, France.
  • Olivier Martin
    Lumio Medical, Paris, France.
  • Xavier Dode
    Centre National Hospitalier d'Information sur le Médicament, Paris, France.
  • Jean-Patrick Lajonchère
    Executive Management, Paris Saint Joseph Hospital, Paris, France.
  • Olivier Billuart
    Medical Information Department, Paris Saint Joseph Hospital, Paris, France.
  • Yvonnick Bézie
    Pharmacy Department, Groupe Hospitalier Paris Saint Joseph, Paris, France.
  • Anne Buronfosse
    Medical Information Department, Paris Saint Joseph Hospital, Paris, France.

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