Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters’ Views

Marja Härkänen, Kaisa Haatainen, Katri Vehviläinen-Julkunen and Merja Miettinen
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Marja Härkänen: Department of Nursing Science/Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
Kaisa Haatainen: Department of Nursing Science/Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
Katri Vehviläinen-Julkunen: Department of Nursing Science/Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
Merja Miettinen: Kuopio University Hospital, 70210 Kuopio, Finland

IJERPH, 2021, vol. 18, issue 17, 1-12

Abstract: The purpose of this study was to describe incident reporters’ views identified by artificial intelligence concerning the prevention of medication incidents that were assessed, causing serious or moderate harm to patients. The information identified the most important risk management areas in these medication incidents. This was a retrospective record review using medication-related incident reports from one university hospital in Finland between January 2017 and December 2019 (n = 3496). Of these, incidents that caused serious or moderate harm to patients (n = 137) were analysed using artificial intelligence. Artificial intelligence classified reporters’ views on preventing incidents under the following main categories: (1) treatment, (2) working, (3) practices, and (4) setting and multiple sub-categories. The following risk management areas were identified: (1) verification, documentation and up-to-date drug doses, drug lists and other medication information, (2) carefulness and accuracy in managing medications, (3) ensuring the flow of information and communication regarding medication information and safeguarding continuity of patient care, (4) availability, update and compliance with instructions and guidelines, (5) multi-professional cooperation, and (6) adequate human resources, competence and suitable workload. Artificial intelligence was found to be useful and effective to classifying text-based data, such as the free text of incident reports.

Keywords: artificial intelligence; hospital; incident report; medication incident; prevention (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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