Healthcare — AIDF Blueprint
Executive Summary
Operationalize safe, compliant AI for clinical decision support, imaging, and operations. AIDF provides PHI controls, validation harnesses, and runtime oversight aligned with HIPAA, ONC, and FDA AI/ML guidance.
Industry Context
- Safety critical: zero‑tolerance for harmful recommendations
- Compliance: HIPAA privacy/security, breach notification, auditability
- Integration: EHR (FHIR/HL7), device data, imaging pipelines
Reference Architecture (AIDF)
- Governance: consent, approvals, audit sinks, change control
- Ethics: bias checks by cohort, explainability methods, audit cadence
- Memory: PHI segmentation, retention windows, vector/RAG for clinical notes
- Orchestrator: validated workflows, fallback paths, resource guardrails
- Monitoring: incident SLAs, anomaly detection, CDS safety dashboards
Controls Mapping (excerpt)
- HIPAA Security Rule → encryption, access controls, key rotation evidence
- Privacy Rule → minimum necessary + consent logs
- FDA CDS → validation suites, post‑market surveillance metrics
Deliverables
- Control matrix, validation harness, evidence templates
- Canonical AIDF config tuned for clinical use cases
- Breach playbooks and CDS change‑control procedures
90‑Day Plan
- Diagnostic and PHI data‑flow mapping
- Pilot (single CDS) with validation and runtime monitoring
- EHR integration hardening and safety dashboards
KPIs
- Alert precision/recall, privacy incidents, time‑to‑evidence, mean time to detect
Next Steps
- Run the AIDF Diagnostic (select “Healthcare”)
- Receive a canonical config and schedule Clinical Architecture Review