Summary
Concept mapping aligns a hospital’s local codes (in-house labels, internal IDs, proprietary vocabularies) with standard vocabularies (SNOMED, LOINC, RxNorm, etc.). It’s the step that makes data interoperable and comparable across institutions.
Client-only
Runs entirely in the browser — no server required.Why map concepts?
A hospital database typically holds codes that are specific to the institution: in-house IDs for lab measurements, local labels for clinical observations and vital signs, internal codes for medications. These codes only make sense inside the hospital’s walls.
To run a multi-centre study or contribute to a network like OHDSI, you need to translate these local codes into a standardised vocabulary. That’s concept mapping.
In practice, it’s about answering questions like:
- Which LOINC concept matches my serum creatinine measurement?
- Which SNOMED concept represents my local “sepsis” definition?
- Which RxNorm concept covers my medication code 4231?
Recommended background reading
Before going further, read the companion resource Speaking the same language: medical terminologies. It explains why each hospital has its own language, why standardised terminologies exist, and which one covers what (ICD-10 for diagnoses, LOINC for lab tests, SNOMED CT for clinical observations, procedures and diagnoses, RxNorm / ATC for medications…). It also covers the distinction between classification, terminology and ontology, useful to understand the relationships between the concepts manipulated here.
Concept mapping is the act of linking your local codes to these standard vocabularies.
How Linkr helps with mapping
Mapping projects
Group mappings by project (local terminology, study…) to split and tame the work.
Target concepts
Pick between ready-made concept dictionaries and the full OHDSI reference vocabularies.
Collaborative review
Approval statuses, comments and multi-reviewer voting.
Standard exports
SSSOM, OMOP source_to_concept_map, Usagi — your mappings are reusable elsewhere.
Linkr builds on recognised standards
Rather than reinventing a new mapping format, Linkr fits into the existing ecosystem of semantic interoperability:
- OMOP
source_to_concept_map— the standard table of OHDSI’s OMOP model for storing mappings toward standard vocabularies. Drops straight into an OMOP ETL. - Usagi — the long-standing OHDSI community format, for interoperability with existing tools.
- SSSOM (Simple Standard for Sharing Ontological Mappings) — the community-driven exchange format for ontology mappings, notably backed by OHDSI.
- SKOS (Simple Knowledge Organization System) — the W3C recommendation that defines the semantic relationships used on every mapping.
AI-assisted pre-mapping
Concept mapping remains an expert task that must be validated by a human. To save time on the first pass, Linkr integrates with Claude Code via a dedicated Skill concept-mapping shipped with the git repository.
You export your project as a ZIP, the agent processes concepts in batches (by category, frequency, etc.) and proposes each mapping with a justified SKOS equivalence. The enriched ZIP imports back into Linkr for final validation in the Mapping Editor.
The human has the final say
No mapping is ever published without review. AI proposes, the expert disposes: the same review pipeline applies (statuses, votes, comments) as for a mapping created by hand.
The home page
When you click Data Warehouse → Concept mapping in the sidebar, you land on two cards:
Map source clinical concepts to standard OMOP vocabularies.
Mapping projects
3 projectsWork on individual mapping projects. Each project maps source concepts from one database or file to standard OMOP vocabularies.
Overview
Aggregated statistics and coverage across all mapping projects. Compare progress, group by badge or project, export consolidated results.
- Mapping projects — your project list, where you work on a specific alignment.
- Overview — aggregated stats and
source_concept_idassignment, useful for tracking overall coverage and preparing an ETL.
What’s in this section
The pages below cover each step of a mapping workflow:
- Mapping projects — create and organise your projects.
- Target Concepts — prepare the target concept sources (concept sets + ATHENA).
- Mapping Editor — the main alignment screen.
- Evaluation — review, validation, comments.
- Export — produce a usable file (ETL, sharing).
- Progress — track advancement.