Institute of Medical Informatics, University Hospital RWTH Aachen, Aachen, Germany.
Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Aachen, Germany.
Stud Health Technol Inform. 2024 Aug 30;317:30-39. doi: 10.3233/SHTI240835.
Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations.
This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data.
Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures.
Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes.
流程挖掘（PM）已成为医疗保健领域的一种变革性工具，可促进流程模型的增强和潜在异常的预测。然而，由于缺乏结构化事件日志和特定的数据隐私法规，PM 在医疗保健中的广泛应用受到了阻碍。
本文介绍了一种将常规医疗保健数据转换为 PM 兼容事件日志的管道，利用《健康数据利用法案》中新增的许可，使用医疗保健数据。
我们的系统利用数据集成中心（DIC）提供的核心数据集（CDS）。它涉及将常规数据转换为快速医疗互操作性资源（FHIR），在本地存储，然后通过适用于任何 DIC 的 FHIR 查询将其转换为标准化的 PM 事件日志。这使得可以在不改变现有 DIC 基础架构的情况下，从各种医疗保健环境中提取详细的、可操作的见解。
遇到的挑战包括处理数据的可变性和质量，以及克服网络和计算限制。我们的管道展示了即使在像医疗保健这样复杂的系统中，也可以应用 PM，通过允许标准化但灵活的分析管道，该管道具有广泛的适用性。成功的应用强调了定制事件日志生成和数据查询功能在实现有效的 PM 应用中的关键作用，从而能够在医疗保健流程中进行基于证据的改进。
