证明临床试验常规收集的医疗保健系统数据的数据完整性 (DEDICaTe):一个概念验证研究
Macey L Murray1,2,3, Laura Sato4, Jaspal Panesar4
1MRC Clinical Trials Unit at UCL (MRC CTU), Institute of Clinical Trials and Methodology, UCL, London, UK.
Health informatics journal
|September 18, 2024
概括
一个新的数据情报工具,Central Metastore,成功地跟踪了国家健康数据集的完整性和来源. 这提高了在临床试验中使用真实世界的数据的信任和透明度.
科学领域:
- 医疗信息学 医疗信息学
- 临床试验数据管理
- 数据治理数据治理
背景情况:
- 现实世界健康数据,也称为例行收集的健康数据,具有改变临床试验行为的巨大潜力.
- 确保这些数据的完整性和来源对于它们在试验中的适当使用以及防止资源重复至关重要.
- 之前的研究强调了需要强大的方法来管理和验证卫生系统数据用于研究目的.
研究的目的:
- 评估英格兰NHS的Central Metastore工具在为国家卫生数据集捕获详细元数据和血统信息方面的可行性.
- 证明该工具在提供数据来源方面的能力,以支持对临床试验数据的信任和透明度.
- 开发一个标准化的流程和指导文件,用于摄入和管理医疗系统数据在中央的metastore.
主要方法:
- 使用Central Metastore工具进行了一项概念验证研究.
- 该工具被用于摄入和处理四个关键数据集:医院病例统计 (入院患者护理,门诊患者,重症监护) 和民事死亡登记 (英格兰和威尔士).
- 这个过程包括收集信息,将数据输入到工具中,并自动生成血统图来说明数据完整性.
主要成果:
- 中央大数据存储成功地吸收,存储和显示了足够详细的数据来源,以促进信任和透明度.
- 该工具证明了其支持在临床试验中使用国家健康数据集的能力.
- 从多个来源收集信息被确定为最耗时的步骤,强调需要保持一致的记录.
结论:
- 中央大数据库是为国家卫生数据集提供基本元数据和血统信息的可行工具.
- 该工具增强了用于临床试验应用的真实数据的完整性,来源和可靠性.
- 在不同来源的数据记录中,标准化和一致性对于高效的数据智能流程至关重要.
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