Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals

Author:

Ben Othman Sarah1ORCID,Decaudin Bertrand2ORCID,Odou Pascal2ORCID,Rousselière Chloé3ORCID,Cousein Etienne3ORCID,Hammadi Slim1ORCID

Affiliation:

1. Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France

2. Univ. Lille, CHU Lille, ULR 7365 - GRITA, F-59000 Lille, France

3. CHU Lille, Institut de Pharmacie, 59000 Lille, France

Abstract

The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect the well-being of hospitalized patients. In this paper we present an automatic system for analyzing prescriptions using Artificial Intelligence (AI) and Machine Learning (ML), with the aim of ensuring patient safety by limiting the risk of prescription errors or drug iatrogeny. Our study is made in collaboration with Lille University Hospital (LUH). We exploited the MIMIC-III (Medical Information Mart for Intensive Care) a large, single-center database containing information corresponding to patients admitted to critical care units at a large tertiary care hospital.

Publisher

IOS Press

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