FHIRCat: Enabling the Semantics of FHIR and Terminologies for Clinical and Translational Research

FHIRCat：为临床和转化研究提供 FHIR 语义和术语

• 批准号: 10558595
• 负责人: Robert Richard Freimuth
• 金额: $ 67.82万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10558595
• 关键词: Acceleration; Automation; Catalogs; Clinical; Clinical Data; Clinical Research; Collection; Communities; Data; Data Discovery; Data Set; Data Sources; Databases; Disparate; Electronic Health Record; Extensible Markup Language; Fast Healthcare Interoperability Resources; Foundations; Future; Genetic; Geography; Goals; Health; Healthcare; Human; Informatics; Information Resources; Institution; Language; Link; Maps; Modeling; Ontology; Outcome; Publishing; Readability; Reference Standards; Reproducibility; Research; Research Personnel; Resource Description Framework; Resources; Semantics; Shapes; Slice; Source; Specific qualifier value; Standardization; Structure; System; Technology; Terminology; Translational Research; Validation; Vendor; Vision; Vocabulary; clinical data repository; community engagement; computer based Semantic Analysis; data access; data access system; data integration; data management; data modeling; data repository; data resource; data sharing; data standards; design; information model; interoperability; next generation; novel; open data; open source; open source tool; success; tool

Project Summary HL7 Fast Healthcare Interoperability Resources (FHIR) is an emerging next generation standard framework for the exchange of electronic health record (EHR) data. The FHIR specification defines a common vocabulary and mechanism for sharing EHR data independent of how it is actually stored. All of the major EHR vendors are developing standardized FHIR interfaces to their clinical data. One of the exciting aspects of FHIR is that it is among the first clinical data standards to incorporate the vision of the “Semantic Web” described by Tim Berners-Lee in his oft cited article from 2001. In the article, he asserts that the Semantic Web is the next "killer app" and outlines a formula for success: 1) Represent information and meaning in a single, universal format - Resource Description Framework (RDF); 2) Create a catalog of URIs that serve as shared identifiers for the RDF representation in a given context of use; and 3) Create tools for transforming existing data and knowledge resources into the universal language of RDF and URIs. This allows information from disparate sources and structures to be combined into a single, federated collection of “linked open data”. This linked data model allows clinical data to be combined with other linked data such as environmental, genetic, geographic, and any other relevant data and to be analyzed as an integrated whole. We have previously demonstrated that the combination of RDF, OWL semantics, and the Shape Expressions (ShEx) schema language could theoretically provide a robust platform for integrating disparate data models and paradigms under a single, resource oriented collection of interfaces. The objective of this project is to design, develop and evaluate a novel informatics platform known as FHIRCat that leverages Semantic Web technologies, FHIR models/profiles, and ontologies for effective standards-based data integration and distributed analytics, enabling high-quality reproducible clinical and translational research. Our specific aims are: 1) Develop FHIR ShEx/RDF specification and tools for FHIR data validation; 2) Standardize and deploy the RDF-based data transformation between external models and FHIR; and 3) Build and evaluate a FHIR ontology-based data access (OBDA) system interoperable with clinical data repositories across institutions in partnership with the CTSA National Center for Data to Health (CD2H). The outcome of the project makes it possible to realize Berners-Lee’s vision for healthcare in the very near future, in turn creating new opportunities for advancing the automation of FHIR- based clinical data integration and sharing, and accelerating standards-based data discovery and distributed analytics in clinical and translational research. 1

项目概要 HL7 快速医疗互操作性资源 (FHIR) 是新兴的下一代标准框架 电子健康记录 (EHR) 数据的交换 FHIR 规范定义了通用词汇表。 以及独立于所有主要 EHR 供应商的实际存储方式共享 EHR 数据的机制。 正在为其临床数据开发标准化 FHIR 接口 FHIR 令人兴奋的方面之一是它 是首批纳入 Tim 描述的“语义网”愿景的临床数据标准之一 Berners-Lee 在他 2001 年发表的经常被引用的文章中提出。在文章中，他断言语义网是下一个“杀手” 应用程序”并概述了成功的公式：1）以单一的通用格式表示信息和含义 - 资源描述框架 (RDF)；2) 创建用作共享标识符的 URI 目录 给定使用环境中的 RDF 表示；以及 3) 创建用于转换现有数据和知识的工具 资源转换为 RDF 和 URI 的通用语言，这允许来自不同来源的信息。 结构被组合成一个“链接的开放数据”的联合集合。 允许临床数据与其他链接数据（例如环境、遗传、地理和任何数据）相结合 其他相关数据并作为一个整体进行分析我们之前已经证明了。 RDF、OWL 语义和形状表达式 (ShEx) 模式语言的组合理论上可以 提供一个强大的平台，用于在单一资源下集成不同的数据模型和范例 该项目的目标是设计、开发和评估一个新颖的接口集合。 称为 FHIRCat 的信息学平台，利用语义 Web 技术、FHIR 模型/配置文件和 用于有效的基于标准的数据集成和分布式分析的本体，从而实现高质量 我们的具体目标是： 1) 开发 FHIR ShEx/RDF。 2）标准化和部署基于RDF的数据转换 外部模型和 FHIR 之间；3) 构建和评估基于 FHIR 本体的数据访问 (OBDA) 与 CTSA National 合作，系统可与跨机构的临床数据存储库互操作 健康数据中心 (CD2H) 该项目的成果使伯纳斯-李的愿景得以实现。 在不久的将来为医疗保健提供服务，从而为推进 FHIR 自动化创造新的机会 基于标准的临床数据集成和共享，加速基于标准的数据发现和分发 临床和转化研究中的分析。 1

项目成果

Shape Expressions (ShEx) schemas for the FHIR R5 specification.

FHIR R5 规范的形状表达式 (ShEx) 架构。

• 发表时间: 2023-12
• 影响因子: 4.5
• 作者: Sharma, Deepak K;Prud'hommeaux, Eric;Booth, David;Nanjo, Claude;Jiang, Guoqian
• 通讯作者: Jiang, Guoqian

Development of a FHIR RDF data transformation and validation framework and its evaluation.

FHIR RDF 数据转换和验证框架的开发及其评估。

• 发表时间: 2021-05
• 影响因子: 4.5
• 作者: Prud'hommeaux, Eric;Collins, Josh;Booth, David;Peterson, Kevin J;Solbrig, Harold R;Jiang, Guoqian
• 通讯作者: Jiang, Guoqian

Developing an ETL tool for converting the PCORnet CDM into the OMOP CDM to facilitate the COVID-19 data integration.

开发 ETL 工具，将 PCORnet CDM 转换为 OMOP CDM，以促进 COVID-19 数据集成。

• 发表时间: 2022-03
• 影响因子: 4.5
• 作者: Yu, Yue;Zong, Nansu;Wen, Andrew;Liu, Sijia;Stone, Daniel J;Knaack, David;Chamberlain, Alanna M;Pfaff, Emily;Gabriel, Davera;Chute, Christopher G;Shah, Nilay;Jiang, Guoqian
• 通讯作者: Jiang, Guoqian

FHIR-Ontop-OMOP: Building clinical knowledge graphs in FHIR RDF with the OMOP Common data Model.

FHIR-Ontop-OMOP：使用 OMOP 通用数据模型在 FHIR RDF 中构建临床知识图。

• 发表时间: 2022-10
• 影响因子: 4.5
• 作者: Xiao, Guohui;Pfaff, Emily;Prud'hommeaux, Eric;Booth, David;Sharma, Deepak K;Huo, Nan;Yu, Yue;Zong, Nansu;Ruddy, Kathryn J;Chute, Christopher G;Jiang, Guoqian
• 通讯作者: Jiang, Guoqian