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The ClearPath Method for Care Pathway Process Mining and Simulation

机译:用于护理途径过程挖掘和模拟的ClearPath方法

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Process mining of routine electronic healthcare records can help inform the management of care pathways. Combining process mining with simulation creates a rich set of tools for care pathway improvement. Healthcare process mining creates insight into the reality of patients' journeys through care pathways while healthcare process simulation can help communicate those insights and explore "what if options for improvement. In this paper, we outline the ClearPath method, which extends the PM2 process mining method with a process simulation approach that address issues of poor quality and missing data and supports rich stakeholder engagement. We review the literature that informed the development of ClearPath and illustrate the method with case studies of pathways for alcohol-related illness, giant-cell arteritis and functional neurological symptoms. We designed an evidence template that we use to underpin the fidelity of our simulation models by tracing each model element back to literature sources, data and process mining outputs and insights from qualitative research. Our approach may be of benefit to others using process-oriented data science to improve healthcare.
机译:常规电子医疗记录的过程挖掘可以帮助告知护理途径。将过程挖掘与模拟相结合,可以创建一套完善的护理途径改善工具。医疗保健过程挖掘可以洞悉患者通过护理途径的真实情况,而医疗保健过程模拟则可以帮助传达这些见解并探索“如果有什么话可以改善”。在本文中,我们概述了ClearPath方法,该方法扩展了PM2过程挖掘一种过程仿真方法,该方法可解决质量低劣和数据丢失的问题,并支持利益相关者的广泛参与;我们回顾了为ClearPath的发展提供信息的文献,并通过案例研究了酒精相关疾病,巨细胞动脉炎的途径我们设计了一个证据模板,通过将每个模型元素追溯到文献来源,数据和过程挖掘输出以及定性研究的见解,来支撑仿真模型的真实性。我们的方法可能会对其他人有所帮助使用面向过程的数据科学来改善医疗保健。

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