评估提取的电子健康记录队列的标准化准则:一个范围审查
Nattanit Songthangtham1, Ratchada Jantraporn2, Elizabeth Weinfurter3
1Institute for Health Informatics, University of Minnesota, Minneapolis MN.
概括
在电子健康记录 (EHR) 中评估队列适应性对于可靠的研究至关重要. 这次审查发现很少有详细的指导方针,强调需要更好的方法来确保EHR数据准确地代表目标人群.
科学领域:
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
- 数据科学数据科学数据科学
背景情况:
- 电子健康记录 (EHR) 数据的二次使用在研究中很常见.
- 通过提取的队列 (队列适应性) 准确地代表目标人群至关重要,但往往被忽视.
- 缺乏标准化的方法阻碍了对队列健康的可靠评估.
研究的目的:
- 从EHR数据中确定评估队列适应性的现有准则.
- 评估这些指南的彻底性和方法细节.
- 确定是否需要全面的最佳实践指南来衡量队列适应性.
主要方法:
- 根据JBI指导和PRISMA-ScR标准进行范围审查.
- 在Medline,Embase和Scopus数据库中进行系统搜索.
- 选了1904个初步结果,其中32篇文章正在进行全面审查.
主要成果:
- 九篇 (28.13%) 的审查文章提供了评估队列适应性的框架.
- 这些框架中只有五个 (15.63%) 提供了足够的细节和定量方法.
- 在对队列适应性评估的全面,可操作的指导方针中存在重大差距.
结论:
- 目前在EHR数据中评估队列适应性的指导方针是不够的.
- 研究人员需要更详细,可计算的方法来评估队列代表性.
- 需要制定一个全面的指导方针,用于测量队列健康的最佳实践.
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