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医疗保健中的流程挖掘:特点与挑战。

Process mining for healthcare: Characteristics and challenges.

机构信息

Pontificia Universidad Católica de Chile, Chile.

Hasselt University, Belgium; Research Foundation Flanders (FWO), Belgium.

出版信息

J Biomed Inform. 2022 Mar;127:103994. doi: 10.1016/j.jbi.2022.103994. Epub 2022 Jan 29.

Abstract

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

摘要

流程挖掘技术可用于分析业务流程,方法是使用执行过程中记录的数据。这些技术在多个领域得到了应用,包括医疗保健领域,主要侧重于分析诊断、治疗和组织流程。尽管医院中涉及医疗保健流程的员工和机器生成了大量数据,但除了研究环境中的针对性案例研究外,没有证据表明流程挖掘得到了系统采用。在医疗保健中开发和使用流程挖掘时,需要特别关注医疗保健流程的独特特征,例如其可变性和以患者为中心的重点。在此背景下,成立了面向流程的数据科学医疗保健联盟,以推广针对医疗保健流程数据驱动改进的技术的研究和应用。本文是该联盟的一项举措,介绍了成功使用流程挖掘需要考虑的医疗保健领域的独特特征,以及社区未来需要解决的开放性挑战。

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