Solution

FHIR Data Harmonizer

For CIOs, interoperability leads, and health-data teams at providers, payers, and health-tech companies: every clinical source converted to validated FHIR R4, with terminology mapped and exceptions held for a steward.

HL7 V2 messagesC-CDA documentsClinical notesLab resultsFHIR R4 resources
Validated against US Core before anything publishesSNOMED, LOINC, and RxNorm mapped automaticallyEvery resource traced to its source message

The problem

Why this exists

Formats

Every system speaks its own dialect

HL7 V2 from one EHR, C-CDA from another, labs as PDFs, registries as CSVs. Assembling one longitudinal record across them is a systems-integration project that never ends.

Mandates

Deadlines outpace interfaces

CMS and ONC rules require FHIR readiness on a timeline that hand-written point-to-point interfaces cannot meet — and each new source restarts the mapping work.

Silent

Bad mappings pass through quietly

Traditional converters drop free-text narrative and push unresolved local codes downstream. The damage surfaces months later, in analytics nobody can reconcile.

The product, not a promise

A patient record you can interrogate

FHIR Data Harmonizer — workspace
Patient — merged from three sources, US Core validatedValidcited
Observation — local lab code mapped to LOINCMapped · tracedcited
MedicationRequest — RxNorm mapped from C-CDA sourceValidcited
Encounter — clinical narrative captured with the structured dataWhole recordcited
Local code with two candidate SNOMED mappings — held for steward reviewverify
HUMAN-APPROVED BEFORE IT POSTS

How it works

File in. Answer out.

  1. 1

    Ingest

    Clinical data arrives as HL7 V2 messages, C-CDA documents, PDFs, or CSVs from any EHR.

  2. 2

    Identify

    Agents recognize the resources inside — Patient, Encounter, Observation — whatever the source format.

  3. 3

    Map

    Local codes convert to SNOMED, LOINC, and RxNorm; fields map to the correct FHIR profiles.

  4. 4

    Validate

    Every resource is tested against its implementation guide, such as US Core or CARIN Blue Button.

  5. 5

    Publish

    Clean FHIR APIs and bulk exports serve authorized systems, with mapping exceptions held for steward review.

Who it's for

Built for the people who own the outcome

Integration engineer

Interfaces you stop hand-writing.

  • One pipeline for structured messages and unstructured documents
  • Terminology mapping without per-source scripts
  • Failures land in an exception queue with the source attached

CIO / interoperability lead

Mandate deadlines met, data actually usable.

  • FHIR R4 output validated against US Core and CARIN Blue Button
  • One canonical format from every source system you have
  • New sources onboard into the same pipeline, no rip-and-replace

Data steward & compliance

Every resource defends its lineage.

  • Trace links from each resource back to the source message or document
  • Unresolved mappings held for review instead of passed through
  • Consent managed at a granular level for partner API access
Health systemsPayersHealth information exchangesHealth-tech vendorsClinical researchLabs & diagnostics
FHIR R4validated against US Core profiles
SNOMED · LOINC · RxNormterminology mapped automatically
100%resources traced to source data

Patient data is locked in whatever format each system happened to speak: HL7 V2 from one EHR, C-CDA from another, lab results as PDFs, registries as CSVs. Assembling a longitudinal record across them is a systems-integration project — and CMS and ONC mandates now require FHIR readiness that legacy interfaces cannot deliver.

Any format in, validated FHIR out

The harmonizer replaces point-to-point interfaces and manual mapping with agents that ingest whatever arrives. Structured messages and unstructured documents are parsed in the same pipeline: the system identifies the FHIR resources inside — Patient, Encounter, Observation, Medication — and maps them to the correct R4 profiles without hand-written scripts. Free-text clinical notes keep their narrative content alongside the structured data, so the patient record stays whole.

Terminology gets the same treatment. Local drug and lab codes convert automatically to RxNorm, LOINC, and SNOMED, which is what makes the output usable — data that shares a schema but still speaks local vocabularies cannot be analyzed together.

Validation, with humans on the exceptions

Every generated resource is tested against its implementation guide — US Core, CARIN Blue Button, or your own profiles — before it is published. Resources that fail validation, and mappings the system cannot resolve confidently, are flagged and held for a data steward’s review rather than passed through silently. Each published resource keeps its trace links back to the source message or document, so any value in the FHIR output can be followed to the data it came from.

Compliance is the mandate; usefulness is the payoff. Harmonized records support real-world evidence work — aggregating disparate patient histories for clinical trial matching — and can be exposed through validated FHIR APIs to authorized partner applications, with consent managed at a granular level. One canonical format, from every source you have.

Objections, answered

What teams ask us first

What happens when a mapping is wrong or uncertain?

It never publishes. Resources that fail profile validation, and mappings below confidence, queue for a data steward with the source data attached. What does publish carries trace links, so any value in the FHIR output can be followed back to the message or document it came from.

We validate against our own implementation guides, not just US Core.

Validation runs against the profiles you designate — US Core, CARIN Blue Button, or your own IGs. Every generated resource is tested against those profiles before it is published.

Where does PHI live?

In your environment. The platform deploys in private cloud or on-premises and is certified to ISO 27001 and SOC 2. Published FHIR APIs serve only authorized systems, with consent managed at a granular level.

How long from connecting a source to seeing FHIR output?

Ingestion handles HL7 V2, C-CDA, PDFs, and CSVs as they are, so validated resources flow as soon as a source connects. The ongoing work is your terminology edge cases, burned down through the steward queue rather than blocking the pipeline.

Bring your messiest HL7 feed.

Watch it become validated US Core FHIR — terminology mapped, narrative captured, trace links intact — live in the demo.

Request a demo