Mitplan: A planning approach to mitigating concurrently applied clinical practice guidelines

Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Marc Carrier

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

7 Scopus citations

Abstract

As the overall population ages, patient complexity and the scope of their care is increasing. Over 60% of the population over 65 years of age suffers from multi-morbidity, which is associated with over two times as many patient-physician encounters. Yet clinical practice guidelines (CPGs) are developed to treat a single disease. To reconcile these two competing issues, we developed a framework for identifying and addressing adverse interactions in multi-morbid patients managed according to multiple CPGs. The framework relies on first-order logic (FOL) to represent CPGs and secondary medical knowledge and FOL theorem proving to establish valid patient management scenarios. In this work, we leverage the framework’s representation capabilities to simplify its mitigation process and cast it as a planning problem represented using the Planning Domain Definition Language (PDDL). We demonstrate the framework’s ability to identify and mitigate adverse interactions using planning actions, add support for durative clinical actions, and show the improved interpretability of management plan recommendations in the context of both proof-of-concept and clinical examples.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings
EditorsDavid Riaño, Szymon Wilk, Annette ten Teije
PublisherSpringer Verlag
Pages93-103
Number of pages11
ISBN (Print)9783030216412
DOIs
StatePublished - 2019
Event17th Conference on Artificial Intelligence in Medicine, AIME 2019 - Poznan, Poland
Duration: Jun 26 2019Jun 29 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11526 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Conference on Artificial Intelligence in Medicine, AIME 2019
Country/TerritoryPoland
CityPoznan
Period6/26/196/29/19

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

  • Clinical practice guidelines
  • Multi-morbidity
  • Planning

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