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医院病例组合规划中的流程数据分析。

Process data analytics for hospital case-mix planning.

机构信息

School of Information Systems, Queensland University of Technology, Brisbane, Australia.

School of Information Systems, Queensland University of Technology, Brisbane, Australia.

出版信息

J Biomed Inform. 2022 May;129:104056. doi: 10.1016/j.jbi.2022.104056. Epub 2022 Mar 23.

Abstract

The composition and volume of patients treated in a hospital, i.e., the patient case-mix, directly impacts resource utilisation. Despite advances in technology, existing case-mix planning approaches are mostly manual. In this paper, we report on a solution that was developed in collaboration with the Queensland Children's Hospital for supporting its case-mix planning using process mining. We investigated (1) How can process mining capabilities be used to inform hospital case-mix planning?, and (2) How can process data be used to assess hospital capacity assessment and inform hospital case-mix planning? The major contributions of this paper include (i) an automated workflow to support both process mining analysis, and capacity assessment, (ii) a process mining analysis designed to detect process performance and variations, and (iii) a novel capacity assessment model based on limiting-resource saturation.

摘要

医院收治患者的构成和数量,即患者病例组合,直接影响资源利用。尽管技术在不断进步,但现有的病例组合规划方法大多是手动的。在本文中,我们报告了一个与昆士兰儿童医院合作开发的解决方案,该解决方案使用流程挖掘来支持其病例组合规划。我们调查了:(1)如何利用流程挖掘功能为医院病例组合规划提供信息?以及(2)如何利用流程数据评估医院容量并为医院病例组合规划提供信息?本文的主要贡献包括:(i)一个自动化工作流程,支持流程挖掘分析和容量评估;(ii)一个旨在检测流程性能和变化的流程挖掘分析;以及(iii)一个基于限制资源饱和的新容量评估模型。

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