extract-clinical-entities-to-fhir

# Extract clinical entities to FHIR Separate extraction from clinical coding. OpenMed finds spans and supplies the mechanical FHIR builders; the application decides which resource type and status are clinically appropriate. ## Procedure 1. Keep the source synthetic, or de-identify it inside the trusted boundary before extraction. 2. Run `openmed.analyze_text` with the task-appropriate clinical model. 3. Filter predictions by label and confidence; preserve offsets in a PHI-safe audit record. 4. Map each accepted span to the correct FHIR resource type. 5. Add terminology codes only from a user-approved mapping or terminology service. Never invent a code. 6. Assemble resources with `to_bundle` and validate against the target profile. ## Runnable synthetic example Install the model runtime first with `python -m pip install "openmed[hf]"`. ```python import json from openmed import analyze_text from openmed.clinical.exporters.fhir import to_bundle note = "Assessment: type 2 diabetes mellitus is stable on metformin." result = analyze_text( note, model_name="disease_detection_superclinical", confidence_threshold=0.5, ) resources = [{"resourceType": "Patient", "id": "synthetic-patient"}] for index, entity in enumerate(result.entities, start=1): if entity.label.upper() not in {"CONDITION", "DIAGNOSIS", "DISEASE"}: continue resources.append( { "resourceType": "Condition", "id": f"condition-{index}", "clinicalStatus": { "coding": [ { "system": ( "http://terminology.hl7.org/CodeSystem/" "condition-clinical" ), "code": "active", } ] }, "verificationStatus": { "coding": [ { "system": ( "http://terminology.hl7.org/CodeSystem/" "condition-ver-status" ), "code": "confirmed", } ] }, # A text-only CodeableConcept is preferable to an invented code. "code": {"text": entity.text}, "subject": {"reference": "Patient/synthetic-patient"}, } ) if len(resources) == 1: raise RuntimeError("No condition spans met the label and confidence rules") bundle = to_bundle(resources, doc_id="synthetic-note-001") print(json.dumps(bundle, indent=2)) ``` ## Safety checks - Do not put raw identifiers, source text, or reversible mappings in logs, `OperationOutcome.diagnostics`, or trace metadata. - Keep a patient identity service separate from extracted clinical facts. - Preserve negation, temporality, and experiencer context before asserting a resource as active or confirmed. - Use a text-only `CodeableConcept` when no approved code is available. - Validate the Bundle against the receiver's FHIR and profile requirements. - Do not bundle restricted terminologies; use the user's licensed service. ## Repository example Read and run [the redaction-to-FHIR walkthrough](../../examples/first_five_minutes_redact_extract_fhir.py) for an offline-friendly pipeline with deterministic extraction.