在规模上解锁实践模式:使用Epic的宇宙开发临床见解的框架
Kyle Bernard1, Arwen Declan2, Kevin Buell3
1Emergency Medicine, Medical College of Wisconsin, Milwaukee, United States.
Applied clinical informatics
|February 18, 2026
概括
我们使用Epic的Cosmos平台开发了一个可适应的工作流程,用于回顾性临床研究. 这种方法可以快速,可重复的队列构建和分析,以改善患者护理证据.
科学领域:
- 临床信息学 临床信息学
- 健康 数据科学 数据科学
- 追溯研究 追溯研究
背景情况:
- 来自供应商汇总的健康信息交换的现实数据对于回顾性临床研究有价值.
- 史诗的Cosmos平台为大规模研究提供了对非识别电子健康记录 (EHR) 数据的访问权限.
研究的目的:
- 描述使用Cosmos平台进行回顾性研究的可泛化的临床信息学工作流程的代开发.
- 完善用于二次数据分析的协作研究过程.
主要方法:
- 计划-做-研究-行动 (PDSA) 循环被应用,以代地完善研究过程.
- 重点领域包括研究设置,团队组成,技术准备和工作流程优化.
- 在宇宙内部的SlicerDicer接口被用于队列探索和构建.
主要成果:
- 确定了多个需要改进的领域,以简化协作研究.
- 获得了关键的见解,用于定义跨临床和信息学领域的研究团队.
- 建立了针对查询构建,队列构建,数据分析,验证和通信的优化流程.
结论:
- 开发的协作方法支持建立高质量的患者护理临床证据.
- 工作流程有助于快速,可重复的队列构建和分析.
- 这种可适应的模型可以在临床领域应用,并扩展到多组织合作.
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