Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model

Sophie-Camille Hogue; Flora Chen; Geneviève Brassard; Denis Lebel; Jean-François Bussières; Audrey Durand; Maxime Thibault

Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model

Machine Learning 2020-11-04 v1

Authors: Sophie-Camille Hogue , Flora Chen , Geneviève Brassard , Denis Lebel , Jean-François Bussières , Audrey Durand , Maxime Thibault

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Abstract

The objective of this work was to assess the clinical performance of an unsupervised machine learning model aimed at identifying unusual medication orders and pharmacological profiles. We conducted a prospective study between April 2020 and August 2020 where 25 clinical pharmacists dichotomously (typical or atypical) rated 12,471 medication orders and 1,356 pharmacological profiles. Based on AUPR, performance was poor for orders, but satisfactory for profiles. Pharmacists considered the model a useful screening tool.

Keywords

unsupervised learning medication orders pharmacological profiles clinical pharmacists anomaly detection AUPR

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@article{arxiv.2011.01925,
  title  = {Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model},
  author = {Sophie-Camille Hogue and Flora Chen and Geneviève Brassard and Denis Lebel and Jean-François Bussières and Audrey Durand and Maxime Thibault},
  journal= {arXiv preprint arXiv:2011.01925},
  year   = {2020}
}

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Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract

Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model

Abstract

Keywords

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