通过模拟驱动的资源分配来改善医疗保健中的组织流程:方法论和现实世界的案例研究
Francesco Vinci1, Davide Aloini2, Elisabetta Benevento2
1Department of Mathematics, University of Padua, Padua, 35121, Italy.
Artificial intelligence in medicine
|March 11, 2026
概括
提高医疗保健效率需要优化流程. 这项研究使用过程挖掘和模拟来进行数据驱动资源分配,大大减少了急诊室患者等待时间.
科学领域:
- 医疗保健管理健康管理
- 运营研究 运营研究
- 数据科学数据科学数据科学
背景情况:
- 人口老龄化给医疗保健系统带来压力,需要提高效率和有效性.
- 医疗保健的提供依赖于由法规和协议管理的复杂过程.
- 传统的过程分析方法在复杂的医疗环境中存在局限性.
研究的目的:
- 引入一种新的方法来改进医疗保健组织流程,使用数据驱动的资源配置.
- 利用过程挖掘和模拟来创建医疗保健操作的现实模型.
- 通过客观,数据驱动的洞察力,提高医疗保健系统的效率和有效性.
主要方法:
- 利用过程挖掘从交易系统数据中发现客观的,数据驱动的模拟模型.
- 采用模拟建模来分析和评估过程改进的替代"what-if"场景.
- 将该方法应用于急诊室,以专注于减少患者等待时间.
主要成果:
- 通过数据驱动的资源配置,证明了患者等待时间 (88%) 的潜在大幅减少.
- 与拟议的改进相关的成本增加 (7%-8%) 略微增加.
- 突出提升了对患者到达激增的过程弹性,改善了应急准备.
结论:
- 过程挖掘和模拟提供了一个强大的,数据驱动的方法来优化医疗保健过程.
- 该方法允许实现现实的建模和改进测试,而不会破坏实时操作.
- 优化医疗保健流程可以大大减少等待时间,提高系统的弹性.
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