Exporting To Fhir

What it does

When your agent uses it

• Wants standards-conformant FHIR JSON
• Condition/Observation/MedicationStatement
• CodeableConcept
• RxNorm/LOINC/ICD-10/SNOMED coding

Example prompts

• “/exporting-to-fhir”

Requirements

• Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1NER — openmed.analyze_text(note, model_name=...) → result.entities.
2. 2Classify each span: a disease label → Condition; a drug → MedicationStatement;
3. 3Ground the surface text to a code out of process (terminology server or
4. 4Build the CodeableConcept with coding(...) + codeable_concept(...).
5. 5Wrap it in the resource shell (set clinicalStatus/status, subject,
6. 6Reference the Patient/Encounter via {"reference": "Patient/"}.
7. 7Pass the list to to_bundle(...) (assembling-fhir-bundles) and validate

What it can do on your machine

Read from SKILL.md and the folder at commit 34d7b8c. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • hl7.org
  • terminology.hl7.org
  • snomed.info
  • unitsofmeasure.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Exporting To Fhir loads about 2.6k tokens when it runs. Until then it costs about 176 tokens; SKILL.md has 647 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~176

When it runs · the whole SKILL.md, loaded when a task matches

~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from maziyarpanahi/openmed at commit 34d7b8c, republished under its Apache-2.0 licence (© maziyarpanahi). 647 words, ~2,603 tokens.

name

exporting-to-fhir

description

Convert OpenMed NER output (entities from openmed.analyze_text) into FHIR R4 resources — Condition, MedicationStatement, Observation — using OpenMed's built-in FHIR R4 export helpers in openmed.clinical.exporters. Covers the verified CodeableConcept builder (coding, codeable_concept, system_uri), deterministic fullUrl references, and OperationOutcome reporting. Use after running OpenMed NER when the user wants standards-conformant FHIR JSON, mentions FHIR, Condition/Observation/MedicationStatement, CodeableConcept, RxNorm/LOINC/ICD-10/SNOMED coding, or interoperability with an EHR. Pairs after extracting-clinical-entities; feeds assembling-fhir-bundles and validating-us-core.

license

Apache-2.0

metadata.project

OpenMed

metadata.category

fhir-interop

metadata.pairs

after

metadata.version

1.0

# CodeableConcept builder — openmed/clinical/exporters/codeable_concept_simple.py
from openmed.clinical.exporters.codeable_concept_simple import (
    system_uri,        # vocab id -> canonical HL7 system URI
    coding,            # (system, code, display) -> Coding dict
    codeable_concept,  # [Coding, ...] -> CodeableConcept dict (deterministic order)
)

# Bundle + reference + OperationOutcome — openmed/clinical/exporters/fhir/
from openmed.clinical.exporters.fhir import (
    to_bundle,                 # [resource, ...] -> R4 transaction Bundle
    deterministic_fullurl,     # (doc_id, index) -> stable urn:uuid
    OperationOutcomeIssue,     # issue dataclass
    to_operation_outcome,      # [issue, ...] -> OperationOutcome
    from_validation_result,    # validator result -> OperationOutcome
)

import openmed
from openmed.clinical.exporters.codeable_concept_simple import coding, codeable_concept

# 1) NER (synthetic note — no real PHI)
result = openmed.analyze_text(
    "Assessment: type 2 diabetes mellitus, stable.",
    model_name="disease_detection_superclinical",
)
# result.entities -> EntityPrediction(text, label, confidence, start, end)
span = result.entities[0]            # e.g. text="type 2 diabetes mellitus"

# 2) Ground to a code OUT OF PROCESS (your terminology server / mapping table).
#    OpenMed bundles no restricted vocab — see querying-terminology-service.
icd_code, snomed_code = "E11.9", "44054006"

# 3) Build the CodeableConcept with OpenMed's builder
cc = codeable_concept(
    [
        coding("snomed", snomed_code, "Diabetes mellitus type 2"),
        coding("icd-10-cm", icd_code, "Type 2 diabetes mellitus without complications"),
    ],
    text=span.text,
)

# 4) Assemble the resource shell yourself
condition = {
    "resourceType": "Condition",
    "id": "cond-1",
    "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",
        }]
    },
    "category": [{
        "coding": [{
            "system": "http://terminology.hl7.org/CodeSystem/condition-category",
            "code": "encounter-diagnosis",
        }]
    }],
    "code": cc,                                  # OpenMed-built CodeableConcept
    "subject": {"reference": "Patient/patient-1"},
    "recordedDate": "2024-03-02",
}

{
  "code": {
    "coding": [
      { "system": "http://snomed.info/sct", "code": "44054006",
        "display": "Diabetes mellitus type 2" },
      { "system": "http://hl7.org/fhir/sid/icd-10-cm", "code": "E11.9",
        "display": "Type 2 diabetes mellitus without complications" }
    ],
    "text": "type 2 diabetes mellitus"
  }
}

med = {
    "resourceType": "MedicationStatement",
    "id": "med-1",
    "status": "active",
    "medicationCodeableConcept": codeable_concept(
        [coding("rxnorm", "860975", "metformin hydrochloride 500 MG Oral Tablet")],
        text="metformin 500 mg",
    ),
    "subject": {"reference": "Patient/patient-1"},
}

obs = {
    "resourceType": "Observation",
    "id": "obs-1",
    "status": "final",
    "category": [{"coding": [{
        "system": "http://terminology.hl7.org/CodeSystem/observation-category",
        "code": "laboratory",
    }]}],
    "code": codeable_concept(
        [coding("loinc", "4548-4", "Hemoglobin A1c/Hemoglobin.total in Blood")],
        text="HbA1c",
    ),
    "valueQuantity": {
        "value": 7.4, "unit": "%",
        "system": "http://unitsofmeasure.org", "code": "%",
    },
    "subject": {"reference": "Patient/patient-1"},
}

© maziyarpanahi, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/exporting-to-fhir of maziyarpanahi/openmed.

Open the folder on GitHubat commit 34d7b8c