A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines

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

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

Abstract

Representation of clinical knowledge is still an open research topic. In particular, classical languages designed for representing clinical guidelines, which were meant for producing diagnostic and treatment plans, present limitations such as for re-using, combining, and reasoning over existing knowledge. In this paper, we address such limitations by proposing an extension of the TMR conceptual model to represent clinical guidelines that allows re-using and combining knowledge from several guidelines to be applied to patients with multimorbidities. We provide means to (semi)automatically detect interactions among recommendations that require some attention from experts, such as recommending more than once the same drug. We evaluate the model by applying it to a realistic case study involving 3 diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with two other existing methods.
Original languageEnglish
Title of host publicationKnowledge Engineering and Knowledge Management - 19th International Conference, EKAW 2014, Proceedings
Pages591-606
Number of pages16
Volume8876
ISBN (Electronic)9783319137032
Publication statusPublished - 2014
EventThe 19th International Conference on Knowledge Engineering and Knowledge Management - Linköping, sweden
Duration: 24 Nov 201428 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8876
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceThe 19th International Conference on Knowledge Engineering and Knowledge Management
Period24/11/1428/11/14

Bibliographical note

Proceedings title: Proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014)
Publisher: Springer
Editors: K Janowicz, S Schlobach, S Lambrix, E Hyvonen

Keywords

  • Clinical knowledge representation
  • Combining medical guidelines
  • Multimorbidity
  • Reasoning

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