Automated conflict resolution between multiple clinical pathways:A technology report

Abstract

Background The number of people in the UK with three or more long-term conditions continues to grow and the management of patients with co-morbidities is complex. In treating patients with multimorbidities, a fundamental problem is understanding and detecting points of conflict between different guidelines which to date has relied on individual clinicians collating disparate information. Objective We will develop a framework for modelling a diverse set of care pathways, and investigate how conflicts can be detected and resolved automatically. We will use this knowledge to develop a software tool for use by clinicians that can map guidelines, highlight root causes of conflict between these guidelines and suggest ways they might be resolved. Method Our work consists of three phases. First, we will accurately model clinical pathways for six of the most common chronic diseases; second, we will automatically identify and detect sources of conflict across the pathways and how they might be resolved. Third, we will present a case study to prove the validity of our approach using a team of clinicians to detect and resolve the conflicts in the treatment of a fictional patient with multiple common morbidities and compare their findings and recommendations with those derived automatically using our novel software. Discussion This paper describes the development of an important software-based method for identifying a conflict between clinical guidelines. Our findings will support clinicians treating patients with multimorbidity in both primary and secondary care settings.

Publication DOI: https://doi.org/10.14236/jhi.v25i3.986
Divisions: College of Engineering & Physical Sciences
Additional Information: Copyright © 2018 The Author(s). Published by BCS, The Chartered Institute for IT under Creative Commons license http://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords: Clinical guidance,Conflict identification,Decision support,Multimorbidity,Patient pathways,Health Informatics,Computer Science Applications,Health Information Management
Publication ISSN: 2058-4563
Last Modified: 08 Jan 2024 08:54
Date Deposited: 26 Nov 2018 10:43
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2018-11-01
Accepted Date: 2018-09-01
Authors: Litchfield, Ian
Turner, Alice
Backman, Ruth
Ferreira Filho, João Bosco
Weber, Phil
Lee, Mark

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