Automated conflict resolution for patients with multiple morbidity being treated using more than one set of single condition clinical guidance: A case study

Abstract

Background The number of people in the UK with two or more conditions continues to grow and their clinical management is complicated by the reliance on guidance focused on a single condition. This leaves individual clinicians responsible for collating disparate information from patient management systems and care recommendations to manually manage the contradictions that exist in the simultaneous treatment of various conditions. Methods/design We have devised a modelling language based on BPMN that allows us to create computer interpretable representations of single condition guidance and incorporate patient data to detect the points of conflict between multiple conditions based on their transformation to logical constraints. This has been used to develop a prototype clinical decision support tool that we can use to highlight the causes of conflict between them in three main areas: medication, lifestyle and well-being, and appointment bookings. Results The prototype tool was used to discern contradictions in the care recommendations of chronic obstructive pulmonary disease and osteoarthritis. These were presented to a panel of clinicians who confirmed that the tool produced clinically relevant alerts that can advise clinicians of the presence of conflicts between guidelines relating to both clashes in medication or lifestyle advice. Conclusions The need for supporting general practitioners in their treatment of patients remains and this proof of concept has demonstrated that by converting this guidance into computer-interpretable pathways we can use constraint solvers to readily identify clinically relevant points of conflict between critical elements of the pathway.

Publication DOI: https://doi.org/10.1016/j.compbiomed.2022.105381
Divisions: College of Business and Social Sciences > Aston Institute for Forensic Linguistics
College of Engineering & Physical Sciences
Additional Information: © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license 4.0 Funding Information: The main funding for this project was provided by Engineering and Physical Sciences Research Council EP/M014401/1 .
Uncontrolled Keywords: Care guidance,Computer interpretable guidelines,Constraint solvers,Decision support,Multiple morbidity,Patient pathways,Primary care,Computer Science Applications,Health Informatics
Publication ISSN: 1879-0534
Last Modified: 13 Jun 2024 07:20
Date Deposited: 11 May 2022 10:38
Full Text Link: https://researc ... ltiple-morbidit
Related URLs: https://linking ... 010482522001731 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-05-01
Published Online Date: 2022-03-04
Accepted Date: 2022-03-02
Authors: Litchfield, Ian
Turner, Alice M.
Ferreira Filho, João Bosco
Lee, Mark
Weber, Phil (ORCID Profile 0000-0002-3121-9625)

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record