Automated conflict resolution between multiple clinical pathways: A technology report

Ian Litchfield, Alice Turner, Ruth PALMER, Joao Bosco Ferreira Filho, Philip Weber

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
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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.

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.

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.
This paper describes the development of an important software-based method for identifying conflict between clinical guidelines. Our findings will support clinicians treating patients with multimorbidity in both primary and secondary care settings.
Original languageEnglish
Pages (from-to)142-148
JournalJournal of innovation in health informatics
Issue number3
Publication statusPublished - Sept 2018


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