EHDS mandates secondary use of health data across the EU. OMOP CDM is the recommended semantic standard. Your pipeline needs the vocabularies - reliably, programmatically, now.
The problem
Building an EHDS-ready pipeline means solving vocabulary access before anything else.
01 -
5 GB+ compressed. Millions of rows. Local PostgreSQL required. Every team does it separately. Every 6-months you do it again.
02 -
SNOMED CT bindings are standard in openEHR. Translating them to OMOP standard concepts programmatically, at scale - is where pipelines stall.
03 -
Health Data Access Bodies (HDABs) have the power to issue fines when data isn't made available on time. Vocabulary infrastructure that blocks your ETL doesn't just slow you down - it creates direct regulatory exposure.
How OMOPHub helps
One REST API. 100+ OMOP vocabularies. No setup, no local database, no 6-months download cycle.
The OHDSI community defines a five-step process for EHDS-compliant studies: Exploration → Initiation → Implementation → Execution → Dissemination. OMOPHub is active in steps 1 and 3 - vocabulary validation before a study begins, and consistent concept resolution during analysis.
Query SNOMED CT, ICD-10, LOINC, RxNorm, and 100+ vocabularies via a single endpoint. Your ETL pipeline calls the API instead of querying a local database that may be months out of date.
openEHR archetypes are bound to SNOMED. OMOPHub returns the corresponding OMOP standard concept with domain, class, and relationship data - so your pipeline never guesses.
BioLORD-powered semantic search understands clinical language. Map free text or ambiguous terms to the correct OMOP concept, ready for EHDS-compliant secondary use analytics.
Python SDK on PyPI, R package on CRAN, and an MCP Server for AI-assisted workflows. pip install omophub and your EHDS pipeline has vocabulary access on the next deploy.
Used alongside the tools that power EHDS implementation
EHDS operational models
The EHDS framework supports two ways research gets done. OMOPHub is prerequisite infrastructure for both.
Data is uploaded to a Secure Processing Environment for analysis. This model works only if your data is correctly mapped to OMOP CDM - wrong vocabulary mappings may corrupt the entire study. OMOPHub validates your mappings before upload.
Data stays local; only aggregated results are shared back to the SPE. Consistent vocabulary mappings across sites are required for results to be comparable. OMOPHub provides that consistency via API.
Both models require OMOP CDM semantic interoperability. Vocabulary errors discovered post-submission mean re-running the study.
Built for European healthcare
Healthcare data pipelines run on schedules. Vocabulary lookups need to work when your ETL runs at 2 AM.
OMOPHub serves vocabulary metadata only - no patient data flows through our infrastructure. GDPR Article 5 considerations are built into the architecture.
Vocabularies are updated quarterly in line with OHDSI ATHENA releases. No manual downloads. Your pipeline uses the same version as the OHDSI community.
Built on Google Cloud Run with Redis caching. Response times under 50ms for concept lookups. Uptime SLAs available on Pro, Scale and Enterprise plans.
API key scoping, usage logs, and per-key rate limits. Scale and Enterprise plans include access audit logs. Ready for EHDS data governance requirements.
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Used by EHDS implementation teams across Europe. Free tier available. No credit card.