Healthcare AI governance consultant

Clinical AI needs governance
before it touches workflow.

I help NHS-facing teams set up healthcare AI governance that connects intended use, validation evidence, clinical safety, DTAC, DCB 0129, data protection alignment, change control and post-go-live review.

Discuss AI governance → AI validation
AccountabilityNamed owners and boundaries
EvidenceClaims matched to use
ChangeGovernance after go-live
Short answer

Who can help with healthcare AI governance?

For suitable NHS-facing clinical AI work, I can support healthcare AI governance as a clinician-led advisor, Clinical Safety Officer and healthcare AI consultant. The work is to make the AI deployment accountable, clinically safe, evidence-aligned and governable after launch.

Useful governance defines what the product is intended to do, what evidence supports that use, who is accountable, how risks are controlled and what happens when the system changes.

Governance scope

What healthcare AI governance should cover.

Governance is the operating system around the AI product: accountability, evidence, safety, privacy, monitoring and change control.

1

Accountability

Define who owns the clinical decision, product release, clinical safety decision, data protection route and post-go-live review.

2

Intended use

Write the supported decision, target users, patient group, setting, excluded uses and claim boundaries before evidence is interpreted.

3

Validation evidence

Check whether evidence supports the intended claim, including limitations, subgroup issues and what the evidence does not prove.

4

Clinical safety

Connect AI hazards, workflow controls, DCB 0129, DCB 0160 and Clinical Safety Officer review into one accountable safety route.

5

Data and privacy

Align the governance route with data protection, information governance, access controls and responsible handling of clinical data.

6

Post-go-live change

Define monitoring, incident review, model updates, workflow changes and triggers for refreshed evidence or safety review.

Where I help

Clinical governance that connects the streams.

Governance review intended use, owners, evidence route and deployment scope Validation alignment claims, reference standard, limitations and evidence refresh triggers Clinical safety AI hazards, DCB 0129, DTAC clinical safety and CSO review Operating model responsibilities before pilot, go-live and post-go-live change Privacy alignment data protection and information governance questions for the right specialist input Communication clear claims, evidence limits and appropriate handling of confidential information
Related routes

Use the specific page for the specific blocker.

Evidence

Clinical AI validation

Use when the blocker is whether the validation evidence supports the intended claim.

Read → Safety case

AI clinical safety

Use when the blocker is AI hazards, DCB 0129, DTAC clinical safety evidence or CSO review.

Read → AI / SaMD route

AI medical-device consultant

Use when intended purpose, validation, SaMD questions, DCB 0129 and DTAC need one route.

Read → Implementation

NHS AI consultant

Use when the blocker is workflow, adoption, procurement readiness or NHS implementation planning.

Read →

Need AI governance reviewed?

Send the intended use, users, patient group, target NHS setting, evidence so far, governance questions and what decision needs unblocking.

Discuss AI governance → Email the details

Primary sources