Documentation Index
Fetch the complete documentation index at: https://developer.eka.care/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Medical Entity Codification is Eka Care’s named entity linking (NEL) technology. It maps a free-text medical entity — a symptom, diagnosis, lab test or drug — to the matching code in a standardised clinical ontology. Free text is how clinicians naturally record information, but it is hard for machines to aggregate, compare or exchange. Codification bridges that gap:"chest pain" becomes SNOMED CT 29857009, "hemoglobin" becomes LOINC
718-7, and "type 2 diabetes mellitus" becomes ICD-10-CM E11. The result is
structured, interoperable health data.
Supported ontologies
| Ontology | Domain | Guide |
|---|---|---|
| SNOMED CT | Symptoms, findings, disorders, procedures | SNOMED CT |
| LOINC | Lab tests and observations | LOINC |
| Medication | Branded and generic drugs | Medication |
| ICD-10-CM | Diagnoses from clinical text | ICD-10-CM |
How the pipeline works
Each codification request runs through three stages:- Query understanding — the input text is parsed for the target ontology. For LOINC this extracts the test name, unit and specimen; for medication, the brand, salt, form and volume; for ICD-10-CM Comprehend, the clinical entity and its attributes.
- Retrieval — candidate terms are fetched from the ontology index, using semantic vector search, a curated knowledge base, or AWS Comprehend Medical depending on the ontology.
- Linking — candidates are scored and the best single match is flagged
with
is_linked: truewhen the pipeline is confident.
The role of context
Some ontologies need more than a name to resolve correctly. A lab test likehemoglobin is ambiguous until you know the unit and specimen — blood and urine
hemoglobin are different LOINC codes. The API accepts an optional metadata
field to carry this context, which materially improves accuracy for LOINC and
medication. The per-ontology guides explain exactly what to send.
Use Cases
- Structured EMRs — code symptoms, diagnoses and prescriptions consistently.
- Lab standardisation — link extracted test names to LOINC for longitudinal tracking.
- Interoperability — produce the coded entities required for FHIR resources.
- Analytics — normalise clinical entities for reliable population-level insights.
- Medical coding — map free-text diagnoses to ICD-10-CM for claims workflows.
Try it out
- Explore the API Reference to get started.
- Call List Registry to see the live ontologies and versions.
- Link your first entity with Link Entity.