Clinic / Healthcare
aicm.dk
A privacy-sensitive reference pattern for clinic operations and patient education
- 1Enterprise demands
- 2Solution design
- 3PoC / pilot
- 4Delivery & rollout
Answer patients faster without exposing health data
Patient inquiries were consuming clinical staff time, yet every question involved sensitive health context.
Public chatbots were ruled out: they would violate the clinic’s data-residency and privacy principles.
Off-the-shelf tools could not reference AICM’s own treatment guidelines, intake forms and FAQs.
Hard requirement: GDPR-aligned audit logging and role-based access to clinical data.
A clinic knowledge assistant with controlled boundaries
- Designed a private-model option for workloads that require a tighter data boundary.
- Structured approved clinic information for knowledge-supported answers.
- Included escalation so clinical staff remain responsible for non-routine questions.
- Mapped role-based access, logging and review needs for privacy-conscious operation.
Contained clinic workflow prototype
- Mapped intake flows, information sensitivity and human handoffs.
- Evaluated model and deployment options against the intended workload.
- Tested the workflow without claiming a generic integration to clinical record systems.
Human-governed delivery pattern
Staff preparation and prompt refinement before any patient-facing use.
Human oversight remains the governing principle for consequential output.
Results
Sensitive workloads can be designed for an approved private or local environment.
Approved information can be made easier to retrieve for routine guidance.
Staff retain final say on every patient-facing answer.
Tech stack
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