The “Clinical & Phenotypic Data Capture & Exchange” (GA4GH::CP) Work Stream is one of the elements of the Global Alliance for Genomics and Health (GA4GH), aimed at developing standard formats for the exchange of genomic data for research and biomedical applications. All members of this team must follow the GA4GH Standards of Professional Conduct.
This Work Stream supports the clinical adoption of genomics through establishing standard ontologies, best practices and information models to describe the clinical phenotype for use in genomic medicine and research, including the capture and exchange of information between electronic health records and research systems.
This workstream has several project areas, focusing on different aspects of the mission:
While ontologies and terminologies provide the standard data concept definitions for capturing clinical information, an information model is required to successfully exchange that information between clinical information systems and with related information systems. A standardized structure for phenotypic data would catalyze integration from distributed sources such as authors, journals, data repositories and clinics when appropriately consented, and accelerate clinical utilization of this data to effect more precise health outcomes. The “Phenopackets” standard will provide information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged.
The Phenopackets Schema FHIR Implementation Guide is an HL7 FHIR Implementation guide based on the approved Phenopackets standard. It will support the standardized exchange of phenotypic information from one health health information system to another through the FHIR API.
Pedigree data is currently represented in heterogeneous formats that frequently result in the use of lowest-common-denominator formats (e.g., PED) or custom JSON formats for data transfer. The need for high quality, unambiguous, computable pedigree and family history information is critical for informing genomic analysis as well as using the information to inform risk to family members. Standardizing the way systems represent family structure will allow patients to share this information more easily between healthcare systems and help software tools to use this information to improve genome analysis and diagnosis.
Please email Lindsay Smith for meeting invitations.