The Challenge      

We have entered the age of molecular science. The genomic data associated with this era is complex and as we move toward including additional “omics”, the complexity and size of the data will dramatically increase

Even as genomic data is increasingly stored in EHRs, this will not be a complete solution. Next generation sequencing (NGS) can identify thousands to millions of variants, whose clinical significance can change over time as our knowledge evolves. Without comprehensive and continuously updated clinical knowledge tied to these findings, providers will be overwhelmed trying to understand genomic and newer “omics” data in relationship to their patients. Today's EHRs are not designed to manage such a large volume of results and continuously changing implications

Why Genomics Operations?

FHIR Genomics operations are based on the premise that an organization’s genomic data is stored in a repository, either in or alongside an EHR, possibly along with phenotype annotations. This data may be stored in FHIR format and/or alternate formats (e.g. VCF format). FHIR Genomics operations essentially 'wrap' the repository, hiding its complexity, and presenting a uniform interface to developers, regardless of internal repository data structures. 

How are Operations Different from Queries?

FHIR operations are standard FHIR queries on steroids. They supplement standard FHIR queries, in a number of ways. For instance, FHIR operations can be used to “interpret” information in the message, querying and joining multiple data sets, or normalizing data to minimize inconsistency in variant representation. This is particularly relevant in genomics, where a tremendous amount of raw data exists in non-FHIR formats, and where inconsistency in variant representation is a known barrier to matching a patient’s genetic profile against knowledge bases – for clinical trials matching, for precision medication selection, etc.

FHIR Genomics Operations Support a Multitude of Clinical Scenarios

FHIR Genomics Operations and associated APIs ease the development and population of data for many types of applications including SMART-ON-FHIR clinical genomics apps, Clinical Decision Support, and EHR screens/visualizations. The operation/API can “pull” data with specific genotype or phenotype information for a patient or population. Genomics Applications can be developed to fulfill diverse needs. A few examples include:

• Matching a cancer patient to available clinical trials based on identified somatic variants
• Providing clinical decision support based on the most current knowledge of a patient's risk as knowledge of their variants evolves
• Screening for actionable hereditary conditions
• Identifying a risk for adverse medication reactions based on pharmacogenomic variants    

Reference Implementation for Genomics Operations - Swagger Interface [https://fhir-gen-ops.herokuapp.com/]

Use Case Team