Poster ID
P-12
Poster Title
FHIR Molecular Definition: Emerging Clinical Standards and Alignment with GA4GH VRS
Authors
Aly Khalifa, Ph.D.[1,2]; Salem Bajjali, M.S.[1,2]; Sarah Senum, M.S.[1,2]; Xianfeng Chen, Ph.D.[2,3];
Robert R. Freimuth, Ph.D.[1,2]
1 Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota
2 Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota
3 Department of Quantitative Health Sciences, Mayo Clinic, Phoenix, Arizona
Robert R. Freimuth, Ph.D.[1,2]
1 Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota
2 Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota
3 Department of Quantitative Health Sciences, Mayo Clinic, Phoenix, Arizona
Abstract
The HL7® Fast Healthcare Interoperability Resources (FHIR®) Standard aims to represent clinical and
biomedical concepts using web technologies to support information sharing and development of
healthcare applications. In 2016, the HL7 Clinical Genomics Work Group (CG WG) formed the
Information Modeling subgroup to take a data-first approach to modeling genomic concepts, striving to
maintain rigorous domain semantics that both eliminate ambiguity and enable computability. The IM
subgroup worked in parallel with the GA4GH Genomic Knowledge Standards (GKS) Work Stream,
leveraging the concepts defined in the Variation Representation Specification (VRS), expanding them to
support a broad array of clinical use cases, and ultimately developing FHIR specifications to support
clinical testing and reporting.
We describe the Molecular Definition FHIR resource, a generalized and extensible model to support
omic data types that prioritizes semantic expressiveness, clarity, and computability. FHIR profiles for
Sequence, Allele, and Variation are aligned with the VRS as much as possible. Mappings between the
specifications illustrate areas of alignment and identify technical or conceptual gaps. Tooling (Python
code and Jupyter notebooks) demonstrates translation between FHIR and VRS data structures using
expert-curated examples derived from clinical genomic tests.
As GA4GH moves increasingly towards clinical applications it will be critical to maximize interoperability
between GA4GH and HL7 FHIR specifications. This work is an example of how GA4GH can influence the
development of specifications by other organizations, and it not only highlights the opportunity for
increased coordination between GA4GH and HL7, but also demonstrates the success that can be
achieved from those efforts.
Acknowledgements:
This work was performed as part of the HL7 CG WG and it leveraged GA4GH GKS discussions and
products. The authors were solely responsible for the development of the FHIR-VRS mappings and
software tooling. We thank the participants in HL7 and GA4GH for their contributions to this work.
biomedical concepts using web technologies to support information sharing and development of
healthcare applications. In 2016, the HL7 Clinical Genomics Work Group (CG WG) formed the
Information Modeling subgroup to take a data-first approach to modeling genomic concepts, striving to
maintain rigorous domain semantics that both eliminate ambiguity and enable computability. The IM
subgroup worked in parallel with the GA4GH Genomic Knowledge Standards (GKS) Work Stream,
leveraging the concepts defined in the Variation Representation Specification (VRS), expanding them to
support a broad array of clinical use cases, and ultimately developing FHIR specifications to support
clinical testing and reporting.
We describe the Molecular Definition FHIR resource, a generalized and extensible model to support
omic data types that prioritizes semantic expressiveness, clarity, and computability. FHIR profiles for
Sequence, Allele, and Variation are aligned with the VRS as much as possible. Mappings between the
specifications illustrate areas of alignment and identify technical or conceptual gaps. Tooling (Python
code and Jupyter notebooks) demonstrates translation between FHIR and VRS data structures using
expert-curated examples derived from clinical genomic tests.
As GA4GH moves increasingly towards clinical applications it will be critical to maximize interoperability
between GA4GH and HL7 FHIR specifications. This work is an example of how GA4GH can influence the
development of specifications by other organizations, and it not only highlights the opportunity for
increased coordination between GA4GH and HL7, but also demonstrates the success that can be
achieved from those efforts.
Acknowledgements:
This work was performed as part of the HL7 CG WG and it leveraged GA4GH GKS discussions and
products. The authors were solely responsible for the development of the FHIR-VRS mappings and
software tooling. We thank the participants in HL7 and GA4GH for their contributions to this work.
Digital Poster