Putting AI to work under HIPAA
This workbook is your step by step guide to deciding what AI should take on in your practice or health business, keeping patient data where it belongs and putting it live in stages. By the end you'll have a business case, a HIPAA checklist covering BAAs, access and audit logs, and a rollout plan with clinician sign-off built in.
Casa Maestri
Kamiki
Part 1: Putting AI to work under HIPAA
Turn "I should really get AI doing this" into a plan you can hold any builder to. Three steps, each with worksheets you fill in for your own business.
Map where clinical and admin hours go, and the patients you turn away when clinicians are at capacity.
The BAA, data, access, logging and sign-off questions to ask before patient data goes anywhere.
Go from drafts on test data to clinician sign-off on live data in four stages, each one working before the next.
Worksheets, not theory
We built a telehealth clinic's lab-report pipeline in its own HIPAA-ready cloud for about $100 a month.
a month in extra infrastructure for a HIPAA-ready lab-report pipeline
to build a clinician dashboard with about 450 backend and 250 frontend tests
adversarial prompts used to red-team an in-app AI assistant
Health teams who want AI without the compliance risk
- Telehealth companies, clinics, practices and health services businesses handling patient data.
- Health and medtech companies scaling support, operations or clinical workflows.
- Teams asking "is Claude HIPAA compliant?" or "is ChatGPT HIPAA compliant?" before using it with patient data.
- Clinical leaders who want AI to draft the work while clinicians keep the judgement.