> ## 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.

# Medical Entity Codification

> Map free-text medical entities to standardised ontology codes for structured, interoperable health data

## Medical Entity Codification

The **Medical Entity Codification API** converts free-text medical entities —
symptoms, diagnoses, lab tests and drugs — into standardised clinical codes.
It turns unstructured clinical text into structured, interoperable data that
downstream systems, analytics and decision-support tools can rely on.

It links text to four ontologies:

* **SNOMED CT** — symptoms, findings, disorders and procedures
* **LOINC** — lab tests and observations
* **ICD-10-CM** — diagnoses, from natural-language clinical text
* **Medication** — branded and generic drugs from Eka's medication database

Read more: ([API Reference - Medical Entity Codification](/api-reference/health-ai/medical-entity-codification/overview)) section.

***

## Use Cases

### Structured EMR Data

Code symptoms, diagnoses and prescriptions captured during a consultation so
records stay consistent and machine-readable across systems.

### Lab Report Standardisation

Link extracted lab test names to LOINC codes — with unit and specimen context —
for accurate longitudinal tracking of diagnostic results.

### Interoperability and FHIR

Generate ontology-coded entities required for FHIR resources and health
information exchange.

### Analytics and Population Health

Normalise clinical entities across cohorts to support reliable aggregation,
risk stratification and reporting.

### Claims and Coding Workflows

Map free-text diagnoses to ICD-10-CM codes to support medical coding and
insurance claim processing.

***

## How It Works

1. **Discover** available ontologies and versions via the registry endpoint.
2. **Send** a free-text entity with the target `ontology` and `version`.
3. **Receive** ranked candidate codes, each with a confidence signal and
   ontology-specific metadata.

For LOINC and medication, an optional `metadata` field carries hints (such as a
test's unit or a drug's form) that materially improve linking accuracy.

***

## Key Characteristics

* Four clinical ontologies from a single API
* Single and batch (up to 5 entities) linking
* Ontology-aware result metadata and confidence signals
* Designed for interoperability, analytics and decision support

***

## Scope & Limitations

* Provides candidate codes; clinical validation remains with the integrator
* Not a substitute for professional medical coding judgment
* Linking accuracy for LOINC and medication depends on the context supplied

Read more: ([API Reference - Medical Entity Codification](/api-reference/health-ai/medical-entity-codification/overview)) section.