An ontology-based approach for detecting and classifying inappropriate prescribing

Guilherme Alfredo Redeker*, Juliana Kuster Filipe Bowles*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

The Beers Criteria, widely used by healthcare professionals, list so-called Potentially Inappropriate Medications (PIMs) which older adults in certain circumstances should avoid. Manually identifying medications that belong to the Beers Criteria can be time-consuming and error-prone, as the criteria are complex and subject to frequent updates. Moreover, it is not available in a (formal) representation that health systems can interpret and reason with automatically. This paper proposes an ontology as a formal representation of the Beers Criteria, and describes the elements and the taxonomy underlying the ontology. We include inference rules to enable automated detection and categorisation of drugs classified as PIMs. By automatically detecting drugs that belong to the Beers Criteria, the ontology, once linked with decision support systems, can be used to support healthcare providers in ensuring that older adults receive safe and effective medical care.
Original languageEnglish
Title of host publicationRuleML+RR’23
Subtitle of host publication17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway
EditorsJan Vanthienen, Tomáš Kliegr, Paul Fodor, Davide Lanti, Dörthe Arndt, Egor V. Kostylev, Theodoros Mitsikas, Ahmet Soylu
PublisherCEUR-WS
Chapter7459
Number of pages15
Publication statusPublished - 15 Sept 2023

Publication series

NameCEUR Workshop Proceedings
Volume3485
ISSN (Electronic)1613-0073

Keywords

  • Ontology
  • Inference rules
  • Potentially inappropriate medications
  • Clinical decision support systems

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