For months I've been quietly building a pipeline that takes raw HL7 v2 messages and C-CDA documents, repairs them, maps their codes to standard vocabularies, and turns them into FHIR and OMOP. Why healthcare interop data is so messy, and the approach that's working.
Healthcare · Interoperability · Data · AI8 min read
Performance work on a data pipeline is only safe if it can't change the answers. Here's how golden files and output-equivalence gates let me speed up a clinical pipeline without moving a single score.
Data · Architecture · Delivery · Healthcare6 min read
In the healthcare platform I'm building, patient data lives in its own database and nothing else does. That one rule shapes auth, sync, queries and how I think about risk.
Healthcare · Architecture · Security · Data6 min read
The clinical data pipeline I've been building shows records to four very different kinds of user. Instead of four tables, there's one pattern: server-side pagination, state in the URL and a single scoping rule applied on the server. Here's how it fits together.
React · State management · Healthcare · Front-end5 min read
Parsing clinical documents is the easy half. The hard half is working out what every code inside them actually means. Here's how one bad crosswalk dragged my lab mapping down to about 20%, and what fixed it.
Healthcare · Interoperability · Data7 min read