Phase A · Governance Validation Pilot
Governance-first medication safety, ready for clinical review.
A clean production trial matching the Overview and Phase A documents: deterministic medication checks, allergy conflict detection, explainable outcomes, controlled escalation, and immutable audit evidence.
Reference-linked allergy profile snapshots.
Centrally governed medication safety constraints.
Append-only traceability with immutable hashes.
Escalated before unsafe execution.
PDF clinical decision flowchart
Rebuilt from “AI Healthcare Governance System Architecture — Phase A”: patient admission to immutable audit.
Work steps from the PDF
Translation of the source document into the live website workflow.
Doctor submits patient information, allergy history, medication recommendation, and dosage.
The governance engine detects drug-allergy or drug-interaction conflicts and blocks unsafe continuation.
Risk is classified using allergy severity, compatibility, reaction history, policy, and confidence score.
High-risk prescriptions require supervisor review and mandatory clinical justification.
The system shows triggered rule, severity, decision source, timestamp, and required reviewing authority.
Supervisor receives escalation, reviews justification, approves/rejects, and logs all participants.
Doctor, supervisor, timestamp, risk evaluation, rule version, final outcome, and reasoning are preserved.
Years later, the platform can reconstruct the full timeline with verifiable integrity and accountability.
Phase A API system architecture
Reusable REST/JSON governance API for any hospital portal, EMR/EHR, mobile app, admin console, or audit system, backed by MySQL operational data and Laravel-managed cache/queue runtime.
Phase A capability map
Built to mirror the supplied PDF governance requirements.
Drug interaction checks
Evaluates prescribed medication against current medications using centrally controlled governance rules.
Allergy conflict checks
Compares prescription input with patient allergy snapshots and escalates unsafe conflicts.
Decision explanation layer
Shows triggered rule, risk level, clinical impact, and required action instead of black-box alerts.
Override governance
High-risk decisions require authorized Supervisor/Admin override with mandatory reason and audit trail.
Recent prescription decisions
Last eight evaluations across all actors and risk levels.
| ID | Patient | Risk | Status | Actor | Action |
|---|---|---|---|---|---|
| #10 | Live API Verify PatientPT-API-LIVE-VERIFY | high | escalation required | External API DoctorDoctor | View |
| #9 | AI Status Highlight VerificationPT-AI-STATUS-1778410012 | high | escalation required | Verification DoctorDoctor | View |
| #8 | AI Integration VerificationPT-AI-VERIFY-1778409993 | none | allowed | Verification DoctorDoctor | View |
| #7 | Demo PatientPT-181901 | high | escalation required | Dr. Trial UserDoctor | View |
| #6 | Demo PatientPT-181754 | high | escalation required | Dr. Trial UserDoctor | View |
| #5 | Demo PatientPT-181754 | high | escalation required | Dr. Trial UserDoctor | View |
| #4 | Demo PatientPT-172658 | high | escalation required | Dr. Trial UserDoctor | View |
| #3 | Demo PatientPT-171633 | high | escalation required | Dr. Trial UserDoctor | View |
Verification Doctor · Doctor
View decisionGovernance guarantees
Phase A's non-negotiable promises to clinicians and auditors.
- Deterministic rule engine remains the safety floor; guardrailed AI assist can escalate but not downgrade risk.
- Every critical action writes an immutable hash-backed event.
- Rule changes are admin-controlled, versioned, and audited.
- OpenAI/Claude settings can enable model-assisted prescription review with XML governance context.