Governing AI in healthcare requires balancing patient safety, regulatory compliance, and clinical efficiency.
┌─────────────────────────────────────────────────────────────────────────────┐
│ HEALTHCARE AI GOVERNANCE LANDSCAPE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ AI USE CASES REGULATORY REQUIREMENTS │
│ ───────────── ───────────────────────── │
│ • Clinical Decision Support • HIPAA Privacy Rule │
│ • Diagnostic Imaging AI • HIPAA Security Rule │
│ • Drug Discovery • FDA 21 CFR Part 11 │
│ • Patient Monitoring • HITECH Act │
│ • EHR Data Analysis • State Privacy Laws │
│ • Treatment Recommendations • Clinical Trial Regulations │
│ │
│ ┌────────────────────────┐ │
│ │ PATIENT SAFETY │ │
│ │ ─────────────── │ │
│ │ SCBE ensures AI │ │
│ │ decisions are │ │
│ │ explainable and │ │
│ │ auditable │ │
│ └────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
AI-powered clinical decision support (CDS) can recommend treatments, flag risks, and assist diagnosis. But these recommendations affect patient lives and must be governed.
┌─────────────────────────────────────────────────────────────────┐
│ CLINICAL DECISION SUPPORT GOVERNANCE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ Patient Data │
│ │ │
│ ▼ │
│ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │
│ │ CDS Engine │────▶│ SCBE │────▶│ Clinician │ │
│ │ │ │ Platform │ │ Review │ │
│ └───────────────┘ └───────────────┘ └───────────────┘ │
│ │ │
│ ┌──────────┼──────────┐ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌────────┐ ┌────────┐ ┌────────┐ │
│ │ ALLOW │ │ESCALATE│ │ BLOCK │ │
│ │ │ │ │ │ │ │
│ │Display │ │Require │ │Suppress│ │
│ │to MD │ │Senior │ │& Alert │ │
│ │ │ │Review │ │ │ │
│ └────────┘ └────────┘ └────────┘ │
│ │
│ Example Decision Flow: │
│ ────────────────────── │
│ AI Recommendation: "Consider antibiotic X for infection" │
│ │
│ SCBE Checks: │
│ ✓ Recommendation matches clinical guidelines │
│ ✓ No contraindications in patient record │
│ ✓ Dosage within safe range │
│ ✗ Patient has documented allergy to drug class │
│ │
│ Decision: BLOCK + Alert clinician of allergy conflict │
│ │
└─────────────────────────────────────────────────────────────────┘
# healthcare-cds-policy.yaml
policy :
name : " Clinical Decision Support Governance"
version : " 1.0"
trust_thresholds :
allow : 0.75
quarantine : 0.35
deny : 0.35
clinical_rules :
require_guideline_match : true
check_contraindications : true
verify_dosage_range : true
allergy_check : mandatory
escalation :
life_threatening : always_escalate
controlled_substances : senior_physician
experimental_treatment : ethics_committee
audit :
retention_days : 3650 # 10 years
include_patient_context : anonymized
hipaa_compliant : true
AI can analyze medical images (X-rays, MRIs, CT scans) but decisions must be explainable and approved by radiologists.
┌─────────────────────────────────────────────────────────────────┐
│ DIAGNOSTIC IMAGING AI GOVERNANCE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ Medical Image (DICOM) │
│ │ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ Imaging AI │ │
│ │ ──────────── │ │
│ │ Finding: │ │
│ │ "Mass detected │ │
│ │ in left lung, │ │
│ │ 85% confidence │ │
│ │ malignancy" │ │
│ └────────┬─────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────┐ │
│ │ SCBE Evaluation │ │
│ ├──────────────────────────────────────────────┤ │
│ │ │ │
│ │ Context: │ │
│ │ • AI model version: v2.3.1 (FDA cleared) │ │
│ │ • Image quality score: 0.92 │ │
│ │ • Patient history: Previous lung nodules │ │
│ │ • Confidence level: 0.85 │ │
│ │ │ │
│ │ Trust Score: 0.78 │ │
│ │ Decision: ALLOW with MANDATORY REVIEW │ │
│ │ │ │
│ └──────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────┐ │
│ │ Radiologist Worklist │ │
│ │ ─────────────────────────────── │ │
│ │ PRIORITY: HIGH │ │
│ │ AI Finding: Possible malignancy │ │
│ │ AI Confidence: 85% │ │
│ │ SCBE Trust: 0.78 │ │
│ │ Required Action: Review and confirm │ │
│ └──────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
AI systems accessing Electronic Health Records (EHR) must comply with HIPAA’s minimum necessary rule.
┌─────────────────────────────────────────────────────────────────┐
│ EHR ACCESS GOVERNANCE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ AI Agent Request: "Access patient 12345 full record" │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ SCBE Evaluation │ │
│ ├─────────────────────────────────────────────────────────┤ │
│ │ │ │
│ │ HIPAA Minimum Necessary Check: │ │
│ │ ┌───────────────────────────────────────────────────┐ │ │
│ │ │ Requested: Full patient record │ │ │
│ │ │ AI Purpose: Medication reconciliation │ │ │
│ │ │ Minimum Necessary: Medication list, allergies │ │ │
│ │ │ │ │ │
│ │ │ VIOLATION: Request exceeds minimum necessary │ │ │
│ │ └───────────────────────────────────────────────────┘ │ │
│ │ │ │
│ │ Decision: DENY full access │ │
│ │ Alternative: ALLOW limited access to: │ │
│ │ • Current medications │ │
│ │ • Allergies │ │
│ │ • Active diagnoses (relevant) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ Audit Log Entry: │
│ ───────────────── │
│ Timestamp: 2026-01-23T10:15:32Z │
│ AI Agent: MedReconciliationBot-001 │
│ Request: Full record access │
│ Decision: Partial ALLOW │
│ Reason: HIPAA minimum necessary enforcement │
│ Data Released: medications, allergies │
│ Data Withheld: demographics, notes, imaging │
│ │
└─────────────────────────────────────────────────────────────────┘
HIPAA Requirement SCBE Feature Minimum necessary Data scope enforcement Accounting of disclosures Complete audit trail Patient rights Access request logging Business associates Third-party AI governance
HIPAA Safeguard SCBE Feature Access controls Trust-based authorization Audit controls Immutable logging Integrity controls Cryptographic signatures Transmission security Post-quantum encryption
21 CFR Part 11 SCBE Feature Audit trail Timestamped, immutable logs Electronic signatures ML-DSA-65 signatures Authority checks Multi-signature consensus Record retention Configurable retention (10+ years)
┌─────────────────────────────────────────────────────────────────┐
│ HEALTHCARE SYSTEM INTEGRATION │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌────────────┐ ┌────────────┐ ┌────────────┐ │
│ │ Epic │ │ Cerner │ │ MEDITECH │ │
│ │ EHR │ │ EHR │ │ EHR │ │
│ └─────┬──────┘ └─────┬──────┘ └─────┬──────┘ │
│ │ │ │ │
│ └─────────────────┼─────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────┐ │
│ │ FHIR R4 │ │
│ │ Interface │ │
│ └──────┬───────┘ │
│ │ │
│ ▼ │
│ ┌──────────────┐ │
│ │ SCBE │ │
│ │ Platform │ │
│ └──────┬───────┘ │
│ │ │
│ ┌──────────────┼──────────────┐ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Clinical │ │ Imaging │ │ Research │ │
│ │ AI │ │ AI │ │ AI │ │
│ └──────────┘ └──────────┘ └──────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
DAILY OPERATIONS
────────────────
07:00 Review overnight AI decisions
└── SCBE Dashboard ──▶ Clinical safety check
09:00 QUARANTINE review meeting
└── Clinical Informatics + Security ──▶ Policy adjustments
12:00 New AI model deployment review
└── FDA clearance verification ──▶ SCBE configuration
15:00 Access anomaly investigation
└── Unusual PHI access ──▶ Incident response if needed
17:00 Compliance dashboard review
└── HIPAA metrics ──▶ Leadership report
Failure Mode SCBE Mitigation Incorrect diagnosis Mandatory clinician review Wrong patient data Identity verification layer Outdated model Version control, auto-quarantine old models Bias in AI Fairness monitoring, demographic auditing Hallucination Confidence threshold enforcement
When clinician disagrees with SCBE decision:
1. Clinician initiates override request
2. Override reason documented
3. Secondary approval required (for high-risk)
4. Complete audit trail maintained
5. Feedback loop to improve AI/policy
Week Activities Deliverables 1-2 Discovery HIPAA gap analysis, AI inventory 3-4 Design Policy configuration, FHIR mapping 5-6 Development EHR integration, testing 7-8 Validation Clinical validation, IRB if needed 9-10 Pilot Limited deployment, monitoring 11-12 Rollout Full deployment, training
Metric Before SCBE After SCBE Improvement HIPAA audit prep 4 weeks 2 days 93% PHI breach risk Medium Low Significant AI recommendation accuracy 78% 78% No change* Clinician trust in AI 45% 82% 82% Adverse event attribution 48 hours 30 minutes 99%
*SCBE doesn’t improve AI accuracy, but improves trust and safe deployment.
© 2026 Aethermoore - Issac Davis, Founder | Patent Pending (63/961,403) | Products | Demo