Technical Frameworks
Technical frameworks for demonstrating runtime oversight, decision reconstruction, and operational evidence in regulated AI systems.
The Decision Context Record™ is a structured evidentiary framework for reconstructing AI-assisted healthcare decisions and demonstrating effective human oversight under Article 14 of the EU AI Act.
Executive Summary
Healthcare AI organizations can often demonstrate that a decision occurred. Far fewer can reconstruct the conditions under which that decision was made.
The Decision Context Record™ addresses this evidence gap by capturing the minimum operational context required to reconstruct an AI-assisted decision after it has occurred.
The framework is designed for healthcare AI companies, SaMD providers, quality and regulatory leaders, product teams, and organizations preparing for EU AI Act Article 14 implementation.
Framework Components
Each component captures a discrete category of operational evidence required to reconstruct an AI-assisted decision in full.
AI Output Context
Recommendation, classification, prediction, confidence score, probability estimate, model version, inference timestamp.
Human Context
Reviewer identity, role, authorization level, professional qualifications, organizational responsibility.
Decision Environment
Patient information, supporting clinical evidence, risk indicators, warnings, alerts, explanatory content displayed.
Intervention Context
Available actions, override options, escalation pathways, request for additional review.
Decision Outcome
Accepted, overridden, modified, escalated, or deferred decision outcome.
Interaction Evidence
Timestamps, interaction sequence, response latency, user actions, workflow navigation events.
Reconstruction Test
The framework introduces a practical test for oversight evidence:
“Could an independent reviewer reconstruct this decision six months later?”
Recommendation
Reconstruction
Context
Reconstruction
Intervention
Reconstruction
Responsibility
Reconstruction
Oversight
Reconstruction
Maturity Model
Five levels of operational evidence maturity for AI-assisted decision-making in regulated environments.
Approval Logging
A decision occurred.
Decision Traceability
The organization knows what was decided.
Context Capture
The surrounding decision context is partially captured.
Decision Reconstruction
The full decision event can be reconstructed.
Verifiable Oversight
The organization can independently demonstrate effective oversight.
Regulatory Relevance
The framework is designed to support evidence generation for effective human oversight and decision reconstruction in regulated healthcare AI environments.
The Decision Context Record™ is not a complete compliance solution and does not constitute legal or regulatory advice. It addresses a specific evidential gap: the operational proof required to demonstrate oversight at the point of AI-assisted decision-making. Organizations should seek independent legal and regulatory counsel for specific compliance matters.
Oversight Evidence Readiness
If your AI system supports clinical decisions, the critical question is not only whether a human remains in the loop. It is whether the organization can demonstrate what happened at the point of decision.