Blog
Notes on FHIR data quality.
Essays from MedVertical on continuous validation, interoperability, and the evidence layer healthcare data needs.
ePA für alle: What Germany's National Health Record Means for Your FHIR Data
Since October 2025, Germany's ePA has entered mandatory everyday use for healthcare providers. It's the largest FHIR deployment the country has attempted — and it moves German healthcare from documents to structured data, at a scale where conformance stops being optional.
How to Add a FHIR Validation Gate to GitHub Actions
A FHIR validation gate should be boring: run on every pull request, fail clearly, produce machine-readable output, and leave a path from local checks to audit-grade Records evidence.
§373 SGB V and ISiK: What German Hospitals Are Actually Required to Deliver
§373 SGB V makes ISiK conformance mandatory for German hospital information systems. What the Bestätigungsverfahren actually tests, why a one-time certification isn't enough, and what happens between stages.
The German FHIR Landscape: ISiK, MII, gematik, and Why It's More Complex Than It Looks
Germany has one of the densest and most overlapping FHIR landscapes in Europe. ISiK, MII, DiGA, KHZG — they're not the same thing, they don't share the same profiles, and hospitals may need to work with several of them simultaneously.
Terminology Drift: The Silent Killer of FHIR Data Quality
Your FHIR data was valid when it was created. It may not be valid today. Terminology drift is a common — and often under-monitored — source of FHIR data quality failures.
Three Questions Every FHIR Team Should Be Able to Answer
FHIR teams rarely fail because they lack a validator. They fail when they cannot answer whether production data is valid now, when errors first appeared, and what the conformance state was in the past.
Why We Built Records
Records didn't start as a data quality layer. It started while I was designing clinical research systems and ran into a problem many healthcare UX teams face: interfaces are only as reliable as the FHIR constraints behind them.
Records
Turn FHIR validation into operational evidence.
Records continuously validates FHIR data, tracks drift over time, and keeps reproducible evidence for audits, releases, and partner integrations.