Automated conflict resolution between multiple clinical pathways: a technology report

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 gu...

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Bibliographic Details
Main Authors: Ian Litchfield, Alice Turner, Ruth Backman, João Bosco Ferreira Filho, Mark Lee
Format: Article
Language:English
Published: BCS, The Chartered Institute for IT 2018-10-01
Series:Journal of Innovation in Health Informatics
Subjects:
Online Access:https://hijournal.bcs.org/index.php/jhi/article/view/986
Description
Summary: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 howthey 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.
ISSN:2058-4555
2058-4563