Generalizing the Detection of Internal and External Interactions in Clinical Guidelines

Veruska Carretta Zamborlini, Rinke Hoekstra, Marcos Da Silveira, Cedric Pruski, Annette ten Teije, Frank van Harmelen

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper presents a method for formally representing Computer-Interpretable Guidelines to deal with multimorbidity. Although some approaches for merging guidelines exist, improvements are still required for combining several sources of information and coping with possibly conflicting pieces of evidence coming from clinical studies. Our main contribution is twofold: (i) we provide general models and rules for representing guidelines that expresses evidence as causation beliefs; (ii) we introduce a mechanism to exploit external medical knowledge acquired from Linked Open Data (Drugbank, Sider, DIKB) to detect potential interactions between recommendations. We apply this framework to merge three guidelines (Osteoarthritis, Diabetes, and Hypertension) in order to illustrate the capability of this approach for detecting potential conflicts between guidelines and eventually propose alternatives.
Original languageEnglish
Title of host publicationHEALTHINF 2016 - 9th International Conference on Health Informatics, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
PublisherSciTePress
Pages105-116
Number of pages12
ISBN (Electronic)978-989-758-170-0
DOIs
Publication statusPublished - 2016
Event9th International Conference on Health Informatics, HEALTHINF 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 - Rome, Italy
Duration: 21 Feb 201623 Feb 2016

Conference

Conference9th International Conference on Health Informatics, HEALTHINF 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
CountryItaly
CityRome
Period21/02/1623/02/16

Keywords

  • Clinical guidelines
  • Knowledge representation
  • Ontologies
  • Semantic web

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