在基于FHIR的患者数据和基于FHIR的资格标准之间进行匹配
Brian S Alper1,2, Joanne Dehnbostel1,2, Khalid Shahin1,2
1Computable Publishing LLC Ipswich Massachusetts USA.
Learning health systems
|October 20, 2023
概括
罢工匹配功能使用JavaScript将患者数据与临床试验资格标准进行比较. 该软件通过将患者特征与研究要求相匹配,促进了护理点的决策支持.
科学领域:
- 医疗信息学 医疗信息学
- 临床决策支持系统 临床决策支持系统
- 生物医学数据标准 生物医学数据标准
背景情况:
- 为了方便患者在研究中参与研究,以及在护理点获得临床决策支持,需要有效地将患者的特征与资格标准相匹配.
- 现有的系统可能缺乏标准化的方法来比较各种患者数据,并满足复杂的研究要求.
- 健康七级 (HL7) 快速医疗互操作性资源 (FHIR) 标准为健康数据交换提供了一个框架.
研究的目的:
- 开发一个软件功能,即Strike-a-Match功能,自动比较患者特征与研究研究或临床决策支持的资格标准.
- 作为一个系统的原则证明,以促进患者特定的临床决策支持的治疗点认可.
- 通过使用一个共同的信息模型,实现匹配功能的共享.
主要方法:
- 在JavaScript (ES6+) 中实现的Strike-a-Match函数接受两个数据集:一个定义符合条件的数据集 (HL7 FHIR EvidenceVariable Resource JSON) 和另一个定义患者特征的数据集 (FHIR Bundle Resource JSON包括患者,观察和条件资源).
- 该功能处理这些输入,以确定患者的特征是否符合指定的合格标准.
- 附带的符合资格标准的匹配软件演示界面提供了匹配结果的人类可读的显示.
主要成果:
- 罢工匹配功能成功确定患者是否符合定义的资格标准.
- 这代表了第一个比较患者特征和资格标准的软件应用程序,仅使用HL7 FHIR JSON数据.
- 一个开源的符合资格标准的软件库可用于功能共享.
结论:
- 罢工匹配功能展示了一种可行的自动化方法,用于将患者数据与临床研究资格标准相匹配.
- 这项技术可以显著提高患者招募研究的效率,并改善临床决策支持的临床决策支持.
- 使用HL7 FHIR进行标准化数据交换对于这种匹配系统的互操作性和成功至关重要.
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