gms | German Medical Science

Introduction: In the health IT environment, two frameworks have become important due to their significant roles and widespread adoption: the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) by the Observational Health Data Sciences and Informatics (OHDSI) network and the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR). The increasing utilization of these underscores their importance in health IT ecosystems [1], [2]. As part of our ongoing mission to improve data interoperability in healthcare, we aim to explore current approaches of bidirectionally translating data from one format to the other. Complementing the data analysis strengths of the OMOP CDM with ubiquitous FHIR-based health records can foster the generation of medical evidence in upcoming years. Recognizing these benefits, collaborations between OHDSI and HL7 have formed [3]. with the potential to propel the already fruitful conjunctive use of OMOP and FHIR [4]. To exemplify the advantages of OMOP-FHIR integrations, we pay special attention to the domain of immunization-related data: embedding FHIR-based vaccination records into the analysis tools provided by the OMOP toolchain can improve the awareness of adverse drug reactions (ADRs) in vaccination development.

Implementing comprehensive translations between both formats necessitates rules that relate the structure of one format to the other, called mapping, and integration systems to carry out the data transformation based on the rules.

Methods: We conducted a scoping review to identify existing solutions to these translations, focusing on the integrations system and their respective architectural design as well as the mapping rules they facilitate to describe the transformation. Special attention was given to the domain of immunization-related data. We categorized the retrieved literature as mapping or integration and further subdivided the class of integrations based on the methods they employ to realize the data transformation.

Results: Our review indicates little consensus regarding thorough mapping strategies. Yet, we were able to retrieve a range of architectures for integrating OMOP and FHIR that employ custom mapping descriptions. Despite varied approaches and techniques, there is a noticeable lack of comprehensive overviews in the existing literature.

Discussion: Effective integration of OMOP and FHIR is critical for the seamless healthcare information exchange, particularly for vaccination-related data. Nevertheless, the field of OMOP-FHIR remains deficient in coordinated effort. A majority of the integration approaches is designed as one-way pipeline from FHIR resources to the OMOP CDM underlining the importance of OMOP for data processing down the line. Challenges continue to exist due to the complexity of data formats. The works we examined indicate that data transformation can be streamlined if the target format is formally well-defined, for example, the FHIR ontology [5].

Conclusively, this review highlights the need for continued development of robust integration systems and suggests areas for future research to enhance the interoperability of health IT systems.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.