Abstract：
OBJECTIVE: This study aims to enhance the analysis of healthcare processes by introducing Object-Centric Process Mining (OCPM). By offering a holistic perspective that accounts for the interactions among various objects, OCPM transcends the constraints of conventional patient-centric process mining approaches, ensuring a more detailed and inclusive understanding of healthcare dynamics.
METHODS: We develop a novel method to transform the Observational Medical Outcomes Partnership Common Data Models (OMOP CDM) into Object-Centric Event Logs (OCELs). First, an OMOP CDM4PM is created from the standard OMOP CDM, focusing on data relevant to generating OCEL and addressing healthcare data\'s heterogeneity and standardization challenges. Second, this subset is transformed into OCEL based on specified healthcare criteria, including identifying various object types, clinical activities, and their relationships. The methodology is tested on the MIMIC-IV database to evaluate its effectiveness and utility.
RESULTS: Our proposed method effectively produces OCELs when applied to the MIMIC-IV dataset, allowing for the implementation of OCPM in the healthcare industry. We rigorously evaluate the comprehensiveness and level of abstraction to validate our approach\'s effectiveness. Additionally, we create diverse object-centric process models intricately designed to navigate the complexities inherent in healthcare processes.
CONCLUSIONS: Our approach introduces a novel perspective by integrating multiple viewpoints simultaneously. To the best of our knowledge, this is the inaugural application of OCPM within the healthcare sector, marking a significant advancement in the field.
METHODS: We develop a novel method to transform the Observational Medical Outcomes Partnership Common Data Models (OMOP CDM) into Object-Centric Event Logs (OCELs). First, an OMOP CDM4PM is created from the standard OMOP CDM, focusing on data relevant to generating OCEL and addressing healthcare data\'s heterogeneity and standardization challenges. Second, this subset is transformed into OCEL based on specified healthcare criteria, including identifying various object types, clinical activities, and their relationships. The methodology is tested on the MIMIC-IV database to evaluate its effectiveness and utility.
RESULTS: Our proposed method effectively produces OCELs when applied to the MIMIC-IV dataset, allowing for the implementation of OCPM in the healthcare industry. We rigorously evaluate the comprehensiveness and level of abstraction to validate our approach\'s effectiveness. Additionally, we create diverse object-centric process models intricately designed to navigate the complexities inherent in healthcare processes.
CONCLUSIONS: Our approach introduces a novel perspective by integrating multiple viewpoints simultaneously. To the best of our knowledge, this is the inaugural application of OCPM within the healthcare sector, marking a significant advancement in the field.
摘要：
目的：本研究旨在通过引入以对象为中心的过程挖掘（OCPM）来增强对医疗保健过程的分析。通过提供一个整体的视角来解释各种物体之间的相互作用，OCPM超越了传统的以患者为中心的过程挖掘方法的约束，确保对医疗保健动态有更详细和包容性的了解。
方法：我们开发了一种新颖的方法，将观察性医疗结果伙伴关系通用数据模型（OMOPCDM）转换为以对象为中心的事件日志（OCEL）。首先,OMOPCDM4PM是从标准OMOPCDM创建的，专注于与生成OCEL相关的数据，并解决医疗保健数据的异质性和标准化挑战。第二,此子集根据指定的医疗保健标准转换为OCEL，包括识别各种对象类型，临床活动，和他们的关系。该方法在MIMIC-IV数据库上进行了测试，以评估其有效性和实用性。
结果：我们提出的方法在应用于MIMIC-IV数据集时有效地产生OCEL，允许在医疗保健行业实施OCPM。我们严格评估的全面性和抽象水平，以验证我们的方法的有效性。此外,我们创建了不同的以对象为中心的过程模型，这些模型错综复杂地设计用于导航医疗保健过程中固有的复杂性。
结论：。我们的方法通过同时整合多个观点引入了一种新颖的视角。据我们所知,这是OCPM在医疗保健领域的首次应用，标志着该领域的重大进步。
方法：我们开发了一种新颖的方法，将观察性医疗结果伙伴关系通用数据模型（OMOPCDM）转换为以对象为中心的事件日志（OCEL）。首先,OMOPCDM4PM是从标准OMOPCDM创建的，专注于与生成OCEL相关的数据，并解决医疗保健数据的异质性和标准化挑战。第二,此子集根据指定的医疗保健标准转换为OCEL，包括识别各种对象类型，临床活动，和他们的关系。该方法在MIMIC-IV数据库上进行了测试，以评估其有效性和实用性。
结果：我们提出的方法在应用于MIMIC-IV数据集时有效地产生OCEL，允许在医疗保健行业实施OCPM。我们严格评估的全面性和抽象水平，以验证我们的方法的有效性。此外,我们创建了不同的以对象为中心的过程模型，这些模型错综复杂地设计用于导航医疗保健过程中固有的复杂性。
结论：。我们的方法通过同时整合多个观点引入了一种新颖的视角。据我们所知,这是OCPM在医疗保健领域的首次应用，标志着该领域的重大进步。
