可扩展和可解释的替代方案,用于表型评估的图表审查,使用来自电子健康记录的标准化结构化数据进行表型评估
Anna Ostropolets1, George Hripcsak1,2, Syed A Husain3
1Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, United States.
Journal of the American Medical Informatics Association : JAMIA
|October 17, 2023
概括
知识增强电子概况审查 (KEEPER) 为使用结构化电子健康数据进行患者表型评估提供了手动图表审查的更快,更可靠的替代方案. 这种工具提高了观察性研究的效率和临床医生的同意.
科学领域:
- 医疗信息学 医疗信息学
- 临床研究方法论 临床研究方法论
- 在医疗保健中的数据科学.
背景情况:
- 手动图表审查是现型评估的既定标准,但对于大型电子健康记录 (EHR) 和索赔数据研究来说不可扩展.
- 观测性研究需要有效和可解释的方法来进行大规模的表型评估.
研究的目的:
- 评估结构化数据的有效性,以有效和可解释的表型评估,作为手动图表审查的替代方案.
- 评估一种新型工具的性能,即知识增强电子概况审查 (KEEPER),用于表型评估.
主要方法:
- 开发了KEEPER以提取和标准化基于临床推理原则的特定患者结构化数据元素.
- 通过交叉设计,将KEEPER的性能 (间隔协议,准确性,时间) 与使用四种不同的临床条件的手动图表审查进行了比较.
主要成果:
- KEEPER的确诊速度是手动查看图表的两倍.
- 在KEEPER和手册审查之间,一致的患者分类为88.1%,使用KEEPER和手册审查 (76.3%) 的临床医生同意率更高 (91.2%).
- 差异主要是由于缺少数据和解释差异.
结论:
- 结构化数据,当由临床推理策划和组织时,可以实现高效和可解释的表型评估.
- KEEPER表现出不低于手动图表审查的性能,实现了显著的时间节省和改善了临床医生的协议.
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