一个基于过程采矿的健康公平监测框架
Jan Niklas Adams1,2, Jennifer Ziegler3, Matthew McDermott4
1Chair of Process and Data Science, RWTH Aachen University, Aachen, Germany.
PLOS digital health
|August 28, 2024
概括
一个新的框架通过分析患者护理流程,精确地衡量健康公平. 它确定了非英语发言者的败血症治疗延迟,突出了改善医疗保健公平性的关键领域.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 衡量健康公平的衡量方法
- 在医疗保健中的过程采矿.
背景情况:
- 医疗保健存在差异,但缺乏全面衡量健康公平的工具.
- 现有的工具往往专注于护理的孤立方面,而不是整个患者旅程.
- 准确的测量至关重要,因为美国医疗保险支付可能很快就会与健康公平联系起来.
研究的目的:
- 为全面评估健康公平提出一个新的过程挖掘框架.
- 识别和分析单个和多个治疗步骤之间的差异.
- 为制定政策和研究提供一个工具,专注于公平的医疗保健.
主要方法:
- 使用事件日志,详细说明患者护理行动.
- 应用了过程挖掘框架来分析处理途径.
- 专注于重症监护室 (ICU) 中的败血症管理,检查性别和英语水平.
主要成果:
- 在败血症治疗中没有发现基于性别的显著差异.
- 英语水平有限的患者在治疗开始时经历了延迟.
- 随后的治疗步骤对于所有患者群体来说都是相似的,尽管最初的延迟.
结论:
- 拟议的框架提供了一种全面的方法来识别医疗保健差异.
- 过程挖掘可以确定复杂的护理途径中的不平等.
- 解决语言障碍对于改善及时和公平的护理服务至关重要.
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