Why OHDSI's R Packages Don't Just Work: Lessons from Building a Production HADES Runtime
· 9 min read
The OHDSI HADES ecosystem is remarkable. CohortMethod, PatientLevelPrediction, SelfControlledCaseSeries — these R packages encode decades of pharmacoepidemiology methodology into reusable software. In theory, you point them at an OMOP CDM database, call a few functions, and get publication-ready causal inference results.
In practice, getting these packages to run correctly in a modern production environment required solving problems that no documentation warned us about.
This is the story of what we encountered building Parthenon's R runtime — a Plumber API sidecar that executes HADES analyses against a 1-million-patient CDM — and the specific, reproducible bugs we had to fix before a single analysis could complete.