Motivation and Mandate

The widespread adoption of Electronic Health Records and Electronic Medical Records provides a mechanism for information from genomics to be integrated into existing or emerging digital health infrastructure to support patient care. The existing health information infrastructure that needs to work with the genomics includes the request for a genomics test, the sharing of the results from the test and the representation of genomics information in clinical information systems.
This Work Stream will support the clinical adoption of genomics through establishing standard ontologies and information models to describe the clinical phenotype for use in genomic medicine and research, including the capture and exchange of information between electronic clinical systems and research.

Existing Standards

The Clinical and Phenotype Data Capture Work Stream will seek to leverage key existing standards that support clinical data capture and exchange. These include:

• Human Phenotype Ontology – The Human Phenotype Ontology (HPO) aims to provide a standardized vocabulary of phenotypic abnormalities encountered in human disease.
• SNOMED CT – a comprehensive, multilingual clinical healthcare terminology to encode the meanings that are used in health information and support the effective clinical recording of data.
• The HL7 Fast Health Interoperable Resources (FHIR) standard – a specification to enable the transfer of healthcare information over standard APIs.

A number of GA4GH Driver Projects are already developing the information infrastructure (forms, term lists, information models) which they are using to support the capture or sharing of information. This includes the forms which they are using to capture data on patients as they are sequenced as part of clinical demonstration projects. These examples will provide an important starting point for understanding the terminology and information models that are needed to describe a clinical phenotype to support clinical care and research.
Representing these data as FHIR resources with standard terminologies such as SNOMED CT and HPO will enable interoperability in the health system and support data analytics in research.

Proposed Solution

The potential solution set for this Work Stream will include:

• Further development of key terminologies, such as HPO and SNOMED CT, to support the capture of clinical phenotype information.
• Development of standard processes for defining a Reference Set of terms relevant for a particular disease or condition.
• A standard set of FHIR resources for describing a clinical phenotype.