Human factor driven approach to the design of decision support systems to prevent medical errors – the PSIP project

Marie-Catherine Beuscart-Zéphir
University of Lille, Faculty of Medicine, France
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Medical care is intended to improve health, but often patients are harmed by the care they receive. As drug ordering and administration is the most common therapeutic treatment, adverse drug events (ADE’s) are the most common adverse event occurring during the care process.

Adverse drug events endanger the patients’ safety and instigate considerable extra hospital costs. Therefore, a significant reduction of preventable ADE is a challenging issue in Public Health. The European project Patient Safety through Intelligent Procedures in medication (PSIP) aims at preventing medical errors. The objectives are: (1) to facilitate the systematic production of epidemiological knowledge on ADE’s and (2) to improve the entire medication cycle in a hospital environment.

The first sub-objective is to produce knowledge on ADE’s by data mining of structured hospital databases, and semantic mining of free-texts. This will provide a list of observed ADE, with frequencies and probabilities, thus giving a better understanding of potential risks. The second sub-objective is to deliver health provider and patients contextualized decision support by giving alerts and offering recommendations fitting the local risk parameters.

In the project human factors principles are considered a critical component of ADE characterization and prevention, and human factors methods have been applied with each step in the project. This presentation describes how the human factors principles have been applied in the design process of the clinical decision support prototypes designed in the PSIP project.