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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doaj-b0cf1f31cb084072980795ddd151d9602020-11-25T00:03:10ZengBCS, The Chartered Institute for ITJournal of Innovation in Health Informatics2058-45552058-45632018-10-0125314214810.14236/jhi.v25i3.986870Automated conflict resolution between multiple clinical pathways: a technology reportIan Litchfield0Alice Turner1Ruth Backman2João Bosco Ferreira Filho3Mark Lee4University of BirminghamInstitute of Applied Health Research, College of Medical and Dental Sciences, University of BirminghamInstitute of Applied Health Research, College of Medical and Dental Sciences, University of BirminghamDepartment of Computer Science, Federal University of CearaSchool of Computer Science, College of Engineering and Physical Sciences, University of BirminghamBackground: 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.https://hijournal.bcs.org/index.php/jhi/article/view/986Computer Software Applicationsmultimorbiditycare pathways |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ian Litchfield Alice Turner Ruth Backman João Bosco Ferreira Filho Mark Lee |
spellingShingle |
Ian Litchfield Alice Turner Ruth Backman João Bosco Ferreira Filho Mark Lee Automated conflict resolution between multiple clinical pathways: a technology report Journal of Innovation in Health Informatics Computer Software Applications multimorbidity care pathways |
author_facet |
Ian Litchfield Alice Turner Ruth Backman João Bosco Ferreira Filho Mark Lee |
author_sort |
Ian Litchfield |
title |
Automated conflict resolution between multiple clinical pathways: a technology report |
title_short |
Automated conflict resolution between multiple clinical pathways: a technology report |
title_full |
Automated conflict resolution between multiple clinical pathways: a technology report |
title_fullStr |
Automated conflict resolution between multiple clinical pathways: a technology report |
title_full_unstemmed |
Automated conflict resolution between multiple clinical pathways: a technology report |
title_sort |
automated conflict resolution between multiple clinical pathways: a technology report |
publisher |
BCS, The Chartered Institute for IT |
series |
Journal of Innovation in Health Informatics |
issn |
2058-4555 2058-4563 |
publishDate |
2018-10-01 |
description |
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. |
topic |
Computer Software Applications multimorbidity care pathways |
url |
https://hijournal.bcs.org/index.php/jhi/article/view/986 |
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