Hydrog7n: The Most Important Element in Healthcare AI Strategy

Governance Tiers

Board → Model level

Total Controls

Across all tiers

Frameworks

NIST, ISO, OECD +

Lifecycle Gates

Initiation → Production

Filter by framework

NIST RMF

ISO/IEC 42001

OECD AI Principles

IBM Auto AI Gov

HIPAA / FDA / HL7

No results found.

Tier 1

Board of Directors / Governing Body

Ultimate accountability: strategic mandate & ethical tone

4 controls ▶

Core Responsibilities

AI Strategy Charter

Approve the organisation's AI vision, risk appetite statement, and investment thresholds. Establish AI as a board-level agenda item, minimum monthly.

ISO 42001 §4OECD P1

Ethical Principles Resolution

Pass a formal resolution encoding safety, transparency, fairness, and human oversight as non-negotiable principles for all AI systems deployed by the organisation.

OECD P2NIST Map 1.1

Risk Appetite Declaration

Define categorical risk tolerances: which AI use cases are prohibited (e.g., autonomous life-critical decisions without human override), high-risk, and permissible.

NIST GovernISO §6.1

Accountability & Fiduciary Duty

Designate the C-suite officer accountable for AI governance (typically CTO or CMIO). Ensure D&O insurance covers AI-related liabilities. Annual board AI literacy briefing required.

ISO §5.1HIPAA §164

Key Outputs / Artefacts

AI Governance PolicyRisk Appetite Statement Ethics ResolutionBoard AI Scorecard (annual) Accountability Matrix (RACI)

Tier 2

Executive Leadership (C-Suite)

Strategy execution: AI governance program ownership

6 controls ▶

Roles & Ownership

Chief AI Officer / CMIO

Program owner for AI governance. Chairs the AI Governance Committee. Reports directly to CEO with board visibility. Owns the AI system inventory and risk register.

ISO §5.3IBM Auto Gov

Chief Risk Officer

Integrates AI risk into enterprise risk management (ERM). Owns the organisation-level AI risk register. Escalation path for Tier 4 risk exceptions.

NIST GovernISO §6.1

Chief Compliance Officer

Ensures AI programs comply with HIPAA, FDA SaMD regulations, state AI laws, and emerging EU AI Act obligations. Owns regulatory horizon scanning.

HIPAAFDA 21 CFR

Chief Information Security Officer

AI-specific cybersecurity: model supply chain security, adversarial attack protection, PHI leakage prevention in LLMs, and AI vendor security assessments.

NIST AI RMFHIPAA §164.312

Executive Decisions

AI Investment & Portfolio

Approve AI project portfolio, allocate resources, set go/no-go criteria for AI program initiation. Minimum monthly portfolio review.

IBM Auto Gov

Incident Response Authority

Authority to suspend or terminate any AI system. Own the AI-specific incident response plan. Define escalation thresholds that trigger board notification.

NIST RespondISO §10.2

Tier 3

AI Governance Committee

Cross-functional oversight body: policy, standards & portfolio review

6 controls ▶

Committee Composition

CAIO / CMIO (Chair)Legal Counsel Clinical LeadershipIT / Data Engineering CompliancePatient Safety Officer Privacy OfficerEthics Board Rep Cybersecurity

Governance Functions

AI Use Case Registry

Maintain a central inventory of all AI systems: intended use, risk tier, data sources, clinical context, vendor, deployment status. Based on IBM OpenScale asset catalog concept.

IBM Auto GovISO §8.4

Risk Classification & Triage

Apply a 4-tier risk classification (Critical, High, Medium, Low) to every AI use case. Map to FDA SaMD risk framework for clinical systems. Drives depth of review required.

NIST MapFDA SaMD

Policy & Standards Ownership

Author and maintain AI-specific policies: algorithmic fairness, explainability requirements, human oversight minimums, training data governance, and model retirement.

ISO §8.1OECD P3

Vendor & Procurement Review

Third-party AI vendor assessment: model cards, bias audits, explainability support, HIPAA BAA compliance, contractual AI-specific SLAs and audit rights.

NIST Govern 6.1HIPAA BAA

Ethical Review Panel

High-risk use case ethical review: patient autonomy impacts, equity analysis, community representation in training data, and marginalised population impacts.

OECD P2, P4ISO §4.4

Escalation & Exception Management

Defined escalation paths from Tier 5 model teams. Authority to approve risk exceptions, require additional controls, or block deployment pending remediation.

NIST RespondIBM Auto Gov

Meeting Cadence

Full committee

Monthly

Risk subcommittee

Bi-weekly

Use case intake SLA

10 business days

Executive report

Quarterly

Tier 4

AI Program Management Office (AI PMO)

Operationalising governance: lifecycle gates & standards enforcement

8 controls ▶

AI Lifecycle Gate Framework

Every AI system passes through mandatory governance gates. The AI PMO owns gate criteria, evidence collection, and go/no-go authority for Tiers 4–5. Critical-risk systems require Tier 3 sign-off.

Gate 1: Initiation

Use case registration, clinical need validation, risk pre-classification, data availability assessment, regulatory pathway identification (FDA, CE Mark).

ISO §8.2NIST Map

Gate 2: Design & Data

Data governance plan, bias risk assessment for training data, privacy impact assessment (PIA), model architecture review, explainability approach selection.

NIST MeasureIBM AI Facts

Gate 3: Validation

Independent technical validation, clinical validation (for SaMD), fairness testing across demographic subgroups, adversarial robustness testing, performance benchmarks.

FDA §510(k)NIST Measure 2

Gate 4: Pre-Deployment

Final risk sign-off, clinical workflow integration review, staff training completion, human override mechanism verified, monitoring plan activated, rollback plan confirmed.

ISO §8.6OECD P5

Gate 5: In-Production Review

Scheduled post-deployment reviews (30/90/180 day), drift detection triggers, incident review integration, model lifecycle decision (maintain/retrain/retire).

IBM OpenScaleNIST Monitor

PMO Standards & Tools

AI Risk Register Template

Standardised risk register format: hazard, likelihood, severity, current controls, residual risk, owner, and review date. Required for all High and Critical systems.

NIST RMFISO §6.1.2

Model Card Standard

Mandatory model documentation: intended use, out-of-scope uses, training data summary, performance metrics by demographic group, known limitations, and contact.

IBM AI FactsOECD P3

Algorithmic Impact Assessment

Structured template evaluating fairness, safety, privacy, explainability, and environmental impact. Required at Gate 2. Severity-scaled depth of assessment.

OECD P2NIST Measure

Tier 5

Clinical & Operational AI Teams

Domain ownership: responsible deployment within clinical context

7 controls ▶

Team Roles

Clinical AI Product Owner

Clinician who owns the AI tool within their service line. Accountable for clinical workflow integration, staff training, and escalating adverse outcomes. Named on model card.

OECD P5ISO §5.3

AI Champion (Clinical)

Senior clinician embedded in the team who bridges AI outputs and clinical decision-making. Runs pre-deployment simulations and post-deployment case reviews.

NIST Govern 4

Operational AI Lead (IT / Data)

Technical owner for integration, infrastructure, monitoring pipelines. Manages EHR/FHIR integration, alert thresholds, and model version management.

IBM Auto GovHL7 FHIR

Operational Controls

Human-in-the-Loop Protocol

Document the minimum required human review step for every AI-generated output before it influences a clinical decision. Critical systems: clinician must affirmatively accept, not just dismiss.

OECD P5FDA AI/ML Action Plan

Staff Competency & Training

Role-based AI literacy training: what the model does, what it doesn't do, how to interpret outputs, when to override, and how to report issues. Annual recertification required.

ISO §7.2OECD P3

Near-Miss & Incident Reporting

Integrate AI incidents into existing patient safety reporting systems. Track AI-specific event types: false positives causing harm, missed diagnoses, alert fatigue, automation bias.

NIST RespondISO §10.1

Patient Communication Standard

When and how to disclose AI involvement in care. Consent workflows where required. Patient right to request human-only review. Plain-language AI disclosure templates.

OECD P2HIPAA Notice

Tier 6

AI Engineering & Data Science Team

Technical stewardship: build, test, monitor, retrain

6 controls ▶

Technical Governance Controls

Responsible AI Development Standards

Coding standards for ML: reproducible training pipelines, versioned datasets and models (DVC/MLflow), mandatory peer review for model architecture changes, and documented hyperparameters.

IBM Auto GovISO §8.4

Data Governance & Lineage

PHI de-identification protocols (Safe Harbor / Expert Determination). Data lineage tracking from source EHR to training set. Synthetic data generation policy. Data minimisation standard.

HIPAA §164.514NIST Measure 2.5

Bias & Fairness Testing Suite

Mandatory fairness metrics by protected class (race, sex, age, disability status, payer type). Disparate impact ratio, equalized odds, calibration across subgroups. Threshold defined per use case.

NIST Measure 2.2OECD P2

Explainability Implementation

Match explainability method to use case: SHAP/LIME for tabular clinical data, attention visualisation for NLP, saliency maps for imaging AI. Document method and limitations in model card.

OECD P3IBM AI Explainability

Security & Adversarial Testing

Adversarial attack testing (FGSM, PGD for imaging models), membership inference attack testing for PHI leakage, model inversion risk assessment, and prompt injection testing for LLMs.

NIST Measure 2.6HIPAA §164.312

Model Monitoring Pipeline

Automated drift detection (data drift, concept drift, prediction drift). Performance degradation alerts. PSI / KS-test baselines. Retraining triggers and approval workflow integration.

IBM OpenScaleNIST Monitor

Toolchain Standards

MLflow / DVC (versioning) IBM OpenScale (monitoring) SHAP / LIME (explainability) Fairlearn / Aequitas (bias) Weights & Biases (experiment tracking) FHIR R4 (interoperability) DICOM (imaging)

Tier 7

Model-Level Controls & Continuous Monitoring

Embedded safety: the model as a governed artefact

6 controls ▶

Per-Model Governance Requirements

Model Card (mandatory)

Intended use, out-of-scope uses, training data (source, size, date range, demographics), validation performance (overall + subgroup), known failure modes, version, owner, and expiry date.

IBM AI FactsOECD P3

Risk Tier Label

L1 / L2 / L3 / L4, embedded in model registry. Drives required monitoring frequency, human oversight level, retraining frequency, and escalation path.

NIST Map 1.5FDA SaMD Class

Confidence Thresholds & Abstention

Models below a defined confidence threshold must surface an "uncertain" output and escalate to human review rather than returning a low-confidence prediction without a flag.

OECD P5NIST Measure 2.7

Audit Log (tamper-evident)

Every inference logged: timestamp, input hash, output, confidence, version, user context. Retained per HIPAA data retention schedule. Accessible for post-hoc incident analysis.

HIPAA §164.312(b)ISO §9.1

Automated Performance Monitoring

Real-time dashboards: AUC/AUROC, sensitivity/specificity, fairness metrics per subgroup, throughput, latency. Automated alert to Tier 6 team on threshold breach. Weekly performance digest.

IBM OpenScaleNIST Monitor

Model Expiry & Retirement

Every model has an explicit expiry date (max 24 months; less for high-risk). Retirement requires documented handoff, clinical owner notification, and archive in model registry for 7 years.

ISO §8.7NIST Govern 5.2

Monitoring Thresholds by Risk Tier

L4 monitoring

Real-time + daily review

L3 monitoring

Hourly alerts + weekly review

L2 monitoring

Daily alerts + monthly review

L1 monitoring

Weekly digest + quarterly review

Drift detection window

14-day rolling baseline

Retraining trigger

>5% AUC degradation

AI Lifecycle Framework

Lifecycle Gates

Five mandatory governance checkpoints every AI system must clear before advancing. Gates apply across all risk levels (L1 to L4) with depth scaled to risk. No system proceeds without a documented go decision from the gate authority.

Initiation

Design & data

Plan & assess

Validation

Test & verify

Pre-deployment

Final sign-off

In-production

Monitor & review