关于UMLS和SNOMED-CT对编码结果概念的适用性
Abigail Newbury1, Hao Liu1, Betina Idnay1
1Department of Biomedical Informatics, Columbia University, New York City, NY 10032, United States.
Journal of the American Medical Informatics Association : JAMIA
|August 24, 2023
概括
统一医学语言系统 (UMLS) 和SNOMED-CT对编码随机对照试验摘要的临床结果的覆盖范围有限. 提高这些术语对于医学研究中的语义互操作性至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 临床研究信息学 临床研究信息学
背景情况:
- 从临床研究中自动提取PICO (人口,干预,比较,结果) 实体正在推进.
- 临床研究数据的语义互操作性受到提取实体缺乏标准化术语的阻碍.
- 在随机对照试验 (RCT) 摘要中编码结果概念对于证据评估至关重要.
研究的目的:
- 评估统一医学语言系统 (UMLS) 和SNOMED-CT对编码RCT摘要中发现的结果概念的适用性.
- 在这些标准术语中评估结果实体的覆盖范围和映射准确性.
主要方法:
- 开发并验证了一个结果注释指南,用于对结果实体的手动注释.
- 在PubMed上手动注释了来自500个RCT摘要的2617个临床显著结果实体.
- 使用MetaMap将注释结果映射到UMLS中,并执行手动搜索以区分系统和术语错误.
主要成果:
- 只有44%的注释结果概念被UMLS完全覆盖.
- 67%的完全映射的概念是复杂的,需要多个UMLS条目来表示.
- 在61%的完全映射的结果中,SNOMED-CT是来源.
结论:
- 在UMLS和SNOMED-CT中,在RCT摘要中显示出临床结果概念的覆盖范围存在重大差距.
- 特定领域,如新陈代谢和营养,感染和传染病,需要在UMLS中扩展结果概念的表现.
- 需要进一步的研究来评估人口,干预和比较实体的术语覆盖范围,以改善计算表示和临床证据评估.
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