根据临床系统对SNOMED CT集群器在组织电子健康记录问题列表中的准确性和覆盖率的评估:观察性研究
Rashaud Senior1, Timothy Tsai2, William Ratliff3
1Duke University Health System, Durham, NC, United States.
JMIR medical informatics
|June 5, 2024
概括
实施SNOMED CT概念集群器提高了电子健康记录中问题列表组织的准确性. 这种增强的系统准确地反映了临床系统,改善了患者数据管理和临床实用性.
科学领域:
- 医疗信息学 医疗信息学
- 临床数据管理 临床数据管理
- 卫生信息系统 卫生信息系统
背景情况:
- 电子健康记录 (EHR) 经常受到重复,冲突或过时诊断的过载问题列表 (PL) 的影响.
- 有限的EHR配置选项,如基本的字母化,阻碍了有效的PL组织和临床使用.
- 不一致的PL结构阻碍了有效的审查和准确的患者健康问题的表现.
研究的目的:
- 评估SNOMED CT (医学临床术语系统化命名法) 概念群组在EHR内排序问题列表诊断的准确性.
- 评估一种新开发的组织患者问题列表系统的临床实用性.
主要方法:
- 开发了21个基于系统或条件的群组,使用1211个SNOMED CT等级概念和布尔逻辑来重组EHR的PL.
- 从50名多次接触的患者中提取了诊断;两名医生独立将诊断分类为临床系统组.
- 使用科恩 κ统计数据和评估的性能指标,包括灵敏度,特异性,PPV和F1分数,计算了interrater可靠性.
主要成果:
- 总共分析了50名患者的869个诊断,初步同意了821个系统归因.
- 评价者之间的可靠性很强 (科恩 κ = 0.7),有16个诊断需要裁决.
- 基于SNOMED CT的鱼表现出高准确度:97.6%的灵敏度,58.7%的特异性,96.8%的积极预测值,F1得分为0.972.
结论:
- 使用SNOMED CT概念集群器的问题列表组织有效地根据临床专业或疾病对诊断进行分类.
- 开发的小群精确地反映了临床系统,显著改善了PL组织.
- 成功实施导致这些基于SNOMED CT的群群被EHR供应商为他们的基础系统采用.
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