Readmission risk model in production
Build a readmission model and deploy it with de-identified data, audit logs and monitoring suitable for a hospital.
The brief
A hospital wants readmission risk on every discharge, but its IT team needs privacy, audit trails and proof the model still works next year. Build the model and deploy it with de-identification, audit logs, versioned models and monitoring. Good looks like: a reproducible pipeline, a deployed API with audit logs, a release gate on model quality, and a drift and fairness report.
What you will build
- Build and evaluate the readmission model
- De-identify data and document what is stored
- Register models and serve them from an API in Docker
- Log every prediction with model version for audit
- Monitor drift and performance across patient groups
- Write a model card for the hospital
Free, open data to build it with
- Diabetes 130-US hospitals for years 1999–2008 ↗ UCI Machine Learning Repository
Check each dataset's licence before you publish your work. Your mentor gives your team its own version of the brief (data, scope or region), so every team's project is its own.

