An ontology-based approach for detecting and classifying inappropriate prescribing

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.