Prabath Jayathissa, Lukas Rohatsch, Stefan Sauermann, Rada Hussein
{"title":"OMOP-on-FHIR: Integrating the Clinical Data Through FHIR Bundle to OMOP CDM.","authors":"Prabath Jayathissa, Lukas Rohatsch, Stefan Sauermann, Rada Hussein","doi":"10.3233/SHTI250432","DOIUrl":null,"url":null,"abstract":"<p><p>The harmonization of the OMOP Common Data Model (CDM) with HL7 FHIR aims to enhance interoperability in clinical research by harmonizing diverse healthcare datasets. This process, referred to as OMOP-on-FHIR, leverages FHIR Bundles for real-time clinical data exchange and transforms these resources into OMOP CDM format using an ETL process. The ETL pipeline, facilitated by tools like XSLT, enables the extraction, transformation, and loading of data while maintaining semantic consistency. By bridging these two standards, OMOP-on-FHIR promotes the seamless exchange of data across clinical systems and research-oriented databases, supporting global health studies, advanced analytics, and personalized medicine. This methodology advances cross-border research by providing a standardized approach to data management and analysis, thereby improving healthcare outcomes.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"327 ","pages":"667-671"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in health technology and informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI250432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The harmonization of the OMOP Common Data Model (CDM) with HL7 FHIR aims to enhance interoperability in clinical research by harmonizing diverse healthcare datasets. This process, referred to as OMOP-on-FHIR, leverages FHIR Bundles for real-time clinical data exchange and transforms these resources into OMOP CDM format using an ETL process. The ETL pipeline, facilitated by tools like XSLT, enables the extraction, transformation, and loading of data while maintaining semantic consistency. By bridging these two standards, OMOP-on-FHIR promotes the seamless exchange of data across clinical systems and research-oriented databases, supporting global health studies, advanced analytics, and personalized medicine. This methodology advances cross-border research by providing a standardized approach to data management and analysis, thereby improving healthcare outcomes.