Healthcare
Lab results
Patient-linked lab results. Emits FHIR Observation.
Schema
The canonical field set, printed as it ships.
5 fields with multilingual hints (DE / FR / IT / EN / ES) and field-level validators. Any source column that resolves to one of these is mapped by the cascade — most of them on the deterministic layers, with no LLM call.
lab_results_v1FHIR · Observation- fields
- 5
- required
- 4
- validated
- 1
- hints
- 13
| Canonical column | Type | Required | Validators | Header hints the cascade matches |
|---|---|---|---|---|
patient_id | string | yes | — | patientpatient_idpid |
loinc_code | string | yes | loinc_code | loinc |
value | number | yes | — | wertvaleurvalor |
unit | string | — | — | einheitunitéunidad |
taken_at | date | yes | — | entnahmeprélèvementfecha |
Read the same definition as JSON at GET /v1/templates/lab_results_v1. A hint match resolves on layer 2 — no LLM call, no token spend, just the flat per-map fee. Hover a validator id to see what it checks.
- 5 canonical fields
- 4 required
- 1 validated
- 13 header hints
- Healthcare pack
Try it
A real file, a real call, one template id.
15 rows, real LOINC codes, synthetic patient IDs. Fully synthetic — safe to share, commit, and run in CI.
curl -X POST https://api.adaptivmapr.com/v1/uploads \
-H "Authorization: Bearer $ADAPTIVMAPR_API_KEY" \
-F "file=@lab_results_sample.csv" \
-F "template=lab_results_v1"requires_hitl: true so you can gate your own commit. Schema-only mode — headers plus at most three sample rows, each clamped to 80 characters — is a data-minimization mode. Full-data routes the metered layer-5 call in-region under a BAA at a 20% uplift, and stays locked until the workspace accepts the BAA/NDA in-app.adaptivmapr.match_headers({
template_id: "lab_results_v1",
headers: ["patient_id", "loinc_code", "value", "unit"]
})Committed rows can be emitted as FHIR Observation resources — a healthcare-vertical feature on a vertical-agnostic engine.
Ready when you are
Put lab results in production — without shipping raw records.
Schema-only mapping leaves only headers and a handful of clamped samples. Add full-data when you need row-level AI, routed in-region under a BAA.