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数据流的定义:在HL7 FHIR中运行MIABIS

Radovan Tomášik¹, Šimon Koňár², Niina Eklund³

¹Faculty of Informatics, Masaryk University, Botanická 68a, Brno, 60200, Czech Republic; Bank of Biological Material, Masaryk Memorial Cancer Institute, Žlutý kopec 7, Brno, 656 53, Czech Republic; BBMRI-ERIC, Neue Stiftingtalstrasse 2/B/6, Graz, 8010, Austria.

Journal of biomedical informatics

|September 29, 2025

概括

本研究介绍了使用HL7 FHIR.使用生物银行最低信息标准 (MIABIS) 的机器可读实现. 这使生物库和样本级数据的无交换成为可能,增强生物医学研究的互操作性和数据的再利用.

科学领域:

生物医学信息学生物医学信息学
这是生物银行.
数据标准数据标准

背景情况:

生物库对于数据驱动的生物医学研究至关重要,但缺乏样本数据的标准化格式,阻碍了互操作性.
像MIABIS这样的现有概念模型面临着由于抽象性和多样化的实现而面临的采用挑战.
将各种数据源 (医疗保健,注册表,研究) 集成到生物库中需要一种机器可读的解决方案.

研究的目的:

开发一个实用,运营实施MIABIS的现实世界数据交换.
为了创建一个标准化,机器可读的格式,以颗粒,样本相关的生物库数据.
提高生物库数据在研究和临床环境中的互操作性和可重复使用性.

主要方法:

系统评估数据交换标准,包括HL7 FHIR和OMOP CDM.
开发基于FHIR的MIABIS代表性,支持复杂的生物银行结构.
创建辅助工具:一个Python库和一个可用性实现指南.

主要成果:

为核心MIABIS实体创建了9个可互操作的FHIR配置文件,遵守FHIR标准.
开发了一个开源的Python库,用于方案验证和FHIR交互抽象.
基于FHIR的MIABIS实现在BBMRI-ERIC使用真实世界的数据进行了验证,并证明了与联合基础设施的兼容性.

结论:

提供了一种机器可读,可互操作的MIABIS实现,促进跨生物库和卫生系统的数据交换.
与HL7 FHIR集成提供了可重复使用的工具和未来数据模型演变的框架.
这种方法支持整合到临床和研究工作流程中,改善数据的可发现性,重复使用和协作.

关键词:

生物银行生物银行这是公平的,公平的.菲希尔 (FHIR) 是一个人.HL7 HL7 HL7 HL7 HL7 在线互操作性互操作性互操作性米亚比斯 (MIABIS) 是一个美丽的城市.

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