结构化电子健康记录数据的可行性,以促进现实世界的数据研究:ICARE数据方法应用于多中心癌症临床试验
Suzanne George1, Nancy Campbell2, Shauna L Hillman3
1Dana-Farber/Harvard Cancer Center, Boston, Massachusetts, USA.
Cancer
|August 28, 2024
概括
在癌症临床试验中,使用最小的常见瘤数据元素 (mCODE) 模型对电子健康记录 (EHR) 数据进行结构化是可行的. 该ICAREdata项目表明,这种方法可以改善数据提取和共享用于研究.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 临床试验 临床试验
背景情况:
- 电子健康记录 (EHR) 数据往往缺乏结构和标准化,阻碍其在研究中的使用.
- 整合临床试验和现实世界终点数据 (ICAREdata) 项目旨在通过结构化电子健康记录数据来解决这一问题.
研究的目的:
- 使用最小的常见瘤数据元素 (mCODE) 数据模型,在EHR中构建关键研究数据元素.
- 为研究目的提取和传输这些结构化数据.
主要方法:
- ICAREdata项目专注于从EHR捕捉癌症疾病状态和治疗计划的变化.
- 从临床站点使用快速医疗互操作资源 (FHIR) 消息提取数据,并与电子数据捕获 (EDC) 系统进行比较.
- 实施发生在参与瘤学临床试验联盟试验的地点.
主要成果:
- 数据提取和传输完成了来自10个地点的15个试验中的35名患者的数据提取和传输.
- 治疗计划变化和癌症疾病状况的一致率分别为79%和34%.
- 在通过EHR和EDC系统进行评估时,关于癌症疾病状况的共识达到了87%.
结论:
- 在多机构癌症临床试验中,可以使用mCODE和ICAREdata方法来结构化EHR数据.
- EDC 系统可以作为评估 EHR 数据完整性的宝贵参考.
- 未来的努力将优先考虑具有共享定义和简化工作流程的元素.
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