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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.

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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) section.

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Use Cases

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Structured EMR Data

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

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Lab Report Standardisation

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

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Interoperability and FHIR

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

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Analytics and Population Health

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

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Claims and Coding Workflows

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

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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.

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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

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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) section.