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

Author

Listed:
  • 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
    Kuopio University Hospital, 70210 Kuopio, Finland)

  • Katri Vehviläinen-Julkunen

    (Department of Nursing Science/Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
    Kuopio University Hospital, 70210 Kuopio, Finland)

  • Merja Miettinen

    (Kuopio University Hospital, 70210 Kuopio, Finland)

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.

Suggested Citation

  • Marja Härkänen & Kaisa Haatainen & Katri Vehviläinen-Julkunen & Merja Miettinen, 2021. "Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters’ Views," IJERPH, MDPI, vol. 18(17), pages 1-12, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:17:p:9206-:d:626597
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    References listed on IDEAS

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    1. Jeongeun Kim & David W Bates, 2013. "Medication administration errors by nurses: adherence to guidelines," Journal of Clinical Nursing, John Wiley & Sons, vol. 22(3-4), pages 590-598, February.
    2. Marja Härkänen & Susanna Saano & Katri Vehviläinen‐Julkunen, 2017. "Using incident reports to inform the prevention of medication administration errors," Journal of Clinical Nursing, John Wiley & Sons, vol. 26(21-22), pages 3486-3499, November.
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