Automated conflict resolution between multiple clinical pathways: a technology report
Automated conflict resolution between multiple clinical pathways: a technology report
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DOI：
10.14236/jhi.v25i3.986
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发表时间：
2018-07
影响因子：
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通讯作者：
I. Litchfield;A. Turner;R. Backman;J. B. Filho;P. Weber;Mark Lee
中科院分区：
文献类型：
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作者：
I. Litchfield;A. Turner;R. Backman;J. B. Filho;P. Weber;Mark Lee
背景：在英国，患有三种或三种以上长期疾病的人数持续增长，合并疾病患者的管理很复杂。在治疗多发病患者时，一个根本的问题是理解和检测不同指南之间的冲突点，到目前为止，这些指南依赖于个别临床医生整理不同的信息。目的我们将开发一个框架来模拟一组不同的护理路径，并研究如何自动检测和解决冲突。我们将利用这些知识开发一个供临床医生使用的软件工具，该工具可以绘制指南，强调这些指南之间冲突的根本原因，并提出可能解决它们的方法。方法我们的工作分为三个阶段。首先，我们将为六种最常见的慢性疾病的临床路径建立准确的模型；其次，我们将自动识别和检测路径上的冲突来源以及如何解决这些冲突。第三，我们将提供一个案例研究来证明我们方法的有效性，使用一个临床医生团队来检测和解决一个虚构的患有多种常见疾病的患者的治疗冲突，并将他们的发现和建议与使用我们的新软件自动得出的结果和建议进行比较。讨论这篇文章描述了一种重要的基于软件的方法的开发，用于识别临床指南之间的冲突。我们的发现将支持临床医生在初级和二级保健环境中治疗多发病患者。
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.