RATSe-Health (Resilient AI Trust Score - Health)

Governance for Clinical AI - Sectoral Governance

Author: Dr. Sharad Maheshwari MD

Institute for Responsible Healthcare AI

Operationalizing trust at the high-impact bedside. Binding global standards to clinical liability and patient outcomes.

Disclaimer: This artifact is for research and governance synthesis purposes. It is not backed by any government organization or regulatory body. The content is an independent sectoral binding profile based on the RATSe framework of BeResponsibleAI & the Institute for Responsible Healthcare AI.

Architecture Stack

1. RATSe Spine

Global Spine

2. RATSe-Health Binding

Sectoral Profile

3. The Patient

Immutable Foundation

RATSe Spine

Foundational Infrastructure

Pillar	NIST RMF 1.0	EU AI Act	India DPDP Act	GDPR

IRHAI Policy Spine

The constitutional alignment required at clinical scale.

Understanding Impact Metrics

Click a mode below to see how governance maturity directly changes the safety profile of an AI system.

Governance Theatre

Safety as Documentation. Compliance via checklists and meetings. Low technical control.

Governance Competence

Safety as Infrastructure. Technical enforcement via code and sidecar monitoring.

Concept 1: Governance Maturity

In Theatre mode, maturity is "performative." You have an Ethics Board, but the AI is a black box that engineers cannot stop in real-time.

Concept 2: Detection Latency

This is the "Awareness Gap." In Theatre, you realize a model has failed weeks later after a patient is harmed. Latency = Months.

Maturity Radar

Detection Speed (Awareness)

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