Health Cloud
Patient data platforms designed to survive an audit.
In healthcare and life sciences, the compliance model is the architecture. Retrofitting it after go-live costs several times more than building it in.
The usual failure
What usually goes wrong.
- Access control is designed for convenience and fails the first serious review.
- Consent is recorded but not enforced across downstream systems.
- Audit trails exist in fragments across systems that cannot be reconciled.
What we deliver
Specifically, this.
Care coordination and patient data model with role-appropriate access throughout
Consent capture and enforcement propagated to every downstream consumer
End-to-end audit trails that reconcile across systems
Data residency and retention designed against the actual obligation
How we work
Four phases, and you can leave after any of them.
Architecture review
A working session with the engineers who would deliver it. We map the current estate, the constraints, and where it will break at the next order of magnitude.
Design
Data model, integration surface, security model, and release strategy — written down, reviewed with your team, and agreed before anyone builds.
Build
Delivered in reviewable increments against automated tests, in environments that predict production.
Run
Handover to your team with the pipeline, the tests, and the documentation. Or we keep running it. Both are fine; being unable to leave is not.
Integration surface
Nothing on this platform lives alone.
Integration architecture is usually the hardest part of these programmes and where we spend the most design time. These are the systems this practice most often connects to.
- EHR and clinical systems
- Laboratory and diagnostics
- Claims and payer systems
- Consent and identity platforms
Where we do this most
Related practices
These usually travel together.
Bring us an architecture problem.
A working session with the people who would actually deliver it. No pitch deck.
Book an architecture review