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: 10005525
• 负责人: Guoqian Jiang
• 金额: $ 60.1万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-13 至 2021-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005525
• 关键词: Automation; Catalogs; Clinical; Clinical Data; Clinical Research; Collaborations; Collection; Communities; Data; Data Analytics; Data Discovery; Data Science; Data Set; Data Sources; Databases; Electronic Health Record; Extensible Markup Language; Face; Fast Healthcare Interoperability Resources; Foundations; Future; Genetic; Geography; Goals; Healthcare; Human; Informatics; Information Resources; International; Language; Link; Modeling; Observational Study; Ontology; Outcome; Publishing; Readability; Reference Standards; Reproducibility; Research; Research Personnel; Resource Description Framework; Resources; Semantics; Shapes; Slice; Source; Standardization; Structure; System; Technology; Terminology; Translational Research; Validation; Vendor; Vision; Vocabulary; base; clinical data warehouse; computer based Semantic Analysis; data access; data exchange; data integration; data management; data modeling; data resource; data sharing; data warehouse; design; health data; information model; next generation; novel; open data; open source; success; tool

Project Summary HL7 Fast Healthcare Interoperability Resources (FHIR) is an emerging next generation standard framework for the exchange of electronic healthcare information. One of the exciting aspects of FHIR is that it is one of the first clinical data standards to incorporate the vision of the “Semantic Web” described by Tim Berners-Lee in 2001. In it, 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 environmental, genetic, geographic, and any other relevant data and to be analyzed as an integrated whole. Today, the latest FHIR release 1) can represent clinical information in RDF and 2) provides a catalog of shared standardized RDF identifiers for healthcare. Tools exist today that can transform XML, spreadsheets, databases etc. into RDF. What is still missing, however, are mechanisms that convert to and from the shared standard FHIR catalog identifiers and their equivalent in other clinical information models. We have previously demonstrated that the combination of RDF, OWL semantics and the Shape Expressions (ShEx) schema language could be an ideal platform for integrating disparate data models and paradigms under a single, resource oriented collection of interfaces, making it possible to complete Berners-Lee's vision for healthcare which, in turn, creates new opportunities for the clinical data integration and standards-based discovery and analytics for clinical and translational research. The objective of the this project is to design, develop and evaluate a novel informatics platform known as FHIRCat that leverages Semantic Web technologies, FHIR models and profiles, and ontologies for effective standards-based data integration for 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 a FHIR ontology-based data access (OBDA) system for clinical data repositories. 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 analytics in clinical and translational research. 1

项目总结