在医疗保健数据驱动的业务流程模拟中的交互式瓶颈检测:埃及案例研究

Wessam Ahmed AlBakary, Ahmed Ahmed Hesham Sedky, W. Abdelmoez
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引用次数: 0

摘要

使用在业务流程执行期间记录的数据,可以利用流程挖掘技术来检查这些流程。这些方法用于各种领域,包括医疗保健,主要用于分析组织、诊断和治疗过程。尽管医疗保健操作中涉及的人员和设备在医疗保健信息系统中产生了大量数据,但由于模拟,组织能够在实施建议的流程修改之前验证其效果。医疗保健行业正在使用信息系统来存储越来越多的流程执行数据。通过使用瓶颈检测和数据驱动的流程建模,可以利用这些信息,例如,协助医疗设施管理部门做出能力管理决策。然而,医疗保健实际事件日志中的数据质量问题经常影响模拟结果的准确性。在这项工作中,我们使用从埃及医疗机构收集的数据集来显示将瓶颈检测纳入数据驱动过程模拟的效果以及领域专业知识的重要性,同时考虑到事件日志的数据质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive Bottleneck Detection in Data Driven Business Process Simulation in Healthcare: Egyptian Case Study
Using the data logged during the execution of business processes, process mining techniques can be utilized to examine those processes. These methods are used in a variety of fields, including healthcare, where they are primarily used to analyze organizational, diagnostic, and therapeutic processes. The organization is able to verify the effects of the suggested process modifications before implementing them thanks to simulation, despite the enormous volume of data that humans and equipment involved in healthcare operations are generating in healthcare information systems. Information systems are being used in the healthcare industry to store a growing amount of process execution data. With the use of bottleneck detection and data-driven process modelling, this information could be utilized, for instance, to assist medical facility management with capacity management decisions. However, data quality problems in healthcare real-world event logs frequently compromise the accuracy of simulation results. In this work, we use datasets gathered from Egyptian healthcare facilities to show the effects of incorporating bottleneck detection to the data driven process simulation as well as the importance of domain expertise, taking into account the event log's data quality.
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