Hgear Transformation
Convert HL7 v2 messages and C-CDA clinical documents into FHIR resources. Review source-to-resource mapping and normalization before validating the output for your receiving system.
Transformation tools
Keep the source and the generated FHIR close together so teams can see what changed, where it mapped, and what to inspect next.
HL7 v2 → FHIR
Follow message segments into mapped Patient, Observation and Encounter resources without losing the source context.
C-CDA → FHIR
Bring document sections forward into resource-based workflows while keeping the transformation easy to review.
How it works
Each step stays visible, so a mapping tested in the browser becomes a repeatable pipeline with no surprises.
Paste an HL7 v2 message or upload a C-CDA document, using synthetic or de-identified data for evaluation.
Segments such as PID, PV1 and OBX, or document sections such as problems and medications, map to Patient, Encounter, Observation and related resources.
Dates, identifiers, units and code systems are normalized so the output is consistent across sources.
Compare source and result side by side, validate the bundle, then move the same mapping into your API-driven workflow.
Mapping & normalization
Every generated element can be traced back to the field that produced it, with the normalized value shown beside the original.
PID-5Patient.nameDoe, JohnPID-7Patient.birthDate1980-01-01PV1-2Encounter.classinpatientOBX-3Observation.codeLOINC 8302-2OBX-5/6Observation.value180 cmMost clinical data exchanged today still arrives as HL7 v2 messages from lab, ADT and order feeds, or as C-CDA documents from EHRs and health information exchanges. Modern applications, APIs and analytics platforms expect FHIR resources instead. Transformation is the bridge: it turns message segments and document sections into Patient, Encounter, Observation, Condition and other resources that downstream systems can use directly.
The hard part is not producing JSON, it is producing FHIR you can trust. Hgear keeps the source and the generated resources side by side so mapping decisions stay reviewable, normalizes dates, identifiers, units and code systems on the way through, and runs the same transformation engine in the browser tools and the REST API. A mapping you have tested interactively becomes a repeatable pipeline without changing tools.
Workflow integration
Move from browser-based testing to repeatable transformation inside your applications and pipelines.
Call the same converters from your integration layer
Transform feeds and document sets on a schedule
SaaS, private cloud or on-premises
Common questions
Transformation maps fields from HL7 v2 messages or sections of C-CDA clinical documents into FHIR resources. Review the source alongside the output to check patient identifiers, clinical values, codes and resource references. The mapping depends on the source format and the target FHIR profiles.
Explore HL7 v2 to FHIR conversionCompare the generated resources with the original document, then validate them against the profiles and terminology your receiving system expects. A successful conversion alone does not establish that the data is complete, clinically accurate or ready for production.
Review FHIR validation checksStart with synthetic or de-identified samples representative of your source system. Identify the source format, target FHIR version and profiles, expected volume and deployment requirements. Compare the output with your expected mappings and discuss integration requirements with Hgear before production use.
Explore C-CDA to FHIR conversionWhat's next
Check transformed data against the profiles, terminology and conformance rules your workflow expects.