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Information Technology · Integration

HL7 FHIR Mapping Agent

Maps HL7 v2 and legacy messages to FHIR resources and validates payload completeness for downstream systems.

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The work it takes off your plate

Integration teams spend weeks hand-mapping HL7 v2 segments and proprietary feeds into FHIR resources, then discover missing required elements only after downstream apps fail. Inconsistent code systems, partial demographics, and silent nulls create clinical and revenue risk. The HL7 FHIR Mapping Agent automates v2-to-FHIR transformation, terminology alignment, and completeness validation so downstream systems receive conformant, usable payloads.

How it works

The agent parses inbound HL7 v2 and legacy messages, maps segments to FHIR R4 resources using configurable profiles, normalizes terminologies, validates required elements and references, and publishes clean bundles or rejects with structured error reports for interface remediation.

  1. 1Parse and Classify Inbound MessagesClassified, parseable messages routed to the correct mapping profile.
  2. 2Map Segments to FHIR ResourcesDraft FHIR resources/bundles with provenance to source segments.
  3. 3Normalize Terminology and ReferencesTerminology-aligned resources with reference integrity checks complete.
  4. 4Validate Completeness and PublishConformant FHIR payloads delivered or actionable validation failures returned.

  1. Step 1: Parse and Classify Inbound Messages

    • Ingest HL7 v2 ADT, ORM, ORU, RDE, DFT, and defined legacy flat/XML formats
    • Detect message type, trigger event, version, and sending application
    • Validate structural syntax before semantic mapping

    Result: Classified, parseable messages routed to the correct mapping profile.

  2. Step 2: Map Segments to FHIR Resources

    • Transform PID/PD1 to Patient, PV1/PV2 to Encounter, IN1 to Coverage, OBX/OBR to Observation/DiagnosticReport, RXA/RXE to Medication resources
    • Apply site-specific field overrides and extension policies
    • Preserve original message identifiers for traceability

    Result: Draft FHIR resources/bundles with provenance to source segments.

  3. Step 3: Normalize Terminology and References

    • Map local codes to LOINC, SNOMED, RxNorm, CVX, and ICD-10 where configured
    • Resolve practitioner, location, and organization references against master data
    • Fill or flag missing must-support elements per implementation guide

    Result: Terminology-aligned resources with reference integrity checks complete.

  4. Step 4: Validate Completeness and Publish

    • Run FHIR validation (structure, cardinality, profiles, invariants)
    • Quarantine non-conformant payloads with field-level error details
    • Publish valid bundles to FHIR servers, queues, or downstream APIs and ACK source systems

    Result: Conformant FHIR payloads delivered or actionable validation failures returned.

Why use it

  • Faster Modernization. Accelerate v2-to-FHIR migration without brittle one-off scripts.
  • Profile Awareness. Configurable IGs and must-support enforcement.
  • Terminology Quality. Automated LOINC/SNOMED/RxNorm alignment.
  • Field-Level Errors. Interface engineers fix root causes quickly.
  • Downstream Trust. Consumers receive complete, validated resources.