电子健康记录和语义问题使用快速医疗互操作性资源:系统地图审查
Fouzia Amar1, Alain April1, Alain Abran1
1École de technologie supérieure - ETS, Montreal, QC, Canada.
Journal of medical Internet research
|January 30, 2024
概括
这项研究审查了关于Fast Healthcare互操作性资源 (FHIR) 语义互操作性的70篇论文,对绘图,ML/NLP和本体学等方法进行分类. 调查结果强调需要更好的工具和服务来改善医疗保健数据交换和解释.
科学领域:
- 医疗信息学 医疗信息学
- 计算机科学 计算机科学
背景情况:
- 电子健康记录 (EHR) 和物联网中的互操作性问题阻碍了数据交换和解释.
- 快速医疗互操作性资源 (FHIR) 标准对于实现医疗保健中的语义互操作性至关重要.
- 将临床数据结构化和映射到FHIR中可以提高共享数据的质量.
研究的目的:
- 对FHIR语义互操作性资源和术语的研究进行清单.
- 识别和分类用于增强FHIR语义互操作性的方法和贡献.
主要方法:
- 进行了系统映射审查 (SMR).
- 搜索了10个电子数据库,查找2012年至2022年间发表的研究.
- 选择并分析了70项FHIR研究.
主要成果:
- 提出的语义方法被分为映射,术语服务,基于RDF/OWL的,注释,机器学习 (ML) /自然语言处理 (NLP) 和基于本体学的方法.
- 贡献被分为框架/架构,模型,技术,比较服务和工具建议.
- 框架或架构提案是最常见的贡献.
结论:
- FHIR通过数据收集,注释,建模和映射来促进语义互操作性.
- 机器学习和NLP对非结构化数据具有前景,但需要术语服务和自动化工具.
- 自动注释和本体论比较工具可以减少人类的努力,加快采用.
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