Journal

Clinical AI data collected for individual care cannot be assumed available for every later purpose: assess quality improvement, research, training and product development separatel...

An AI-recorded consultation can contain information about relatives, carers and interpreters as well as the patient, requiring careful capture, attribution and review.

A practical guide to asking about medical indemnity for AI workflows, distinguishing negligence cover from complaints, regulatory support and other liabilities.

Before mandatory clinical AI use, staff need clear scope, training, review time, escalation and indemnity arrangements, not a vague instruction to approve outputs.

A practical governance approach for small GP practices distinguishes reusable supplier assurance from the local decisions needed for safe AI deployment.

How incremental feature changes can outgrow an AI scribe's original approval, and what NHS teams should reassess before drafting becomes action.

Why AI suggestions must remain separate from records of advice and consent that actually occurred, with practical review and correction examples.

Clinical AI can omit an exception, uncertainty or follow-up step while every sentence it includes sounds correct: here is how to check completeness.

The July 2026 MHRA clarification separates documentation from medical-device functions, but organisations still need to control clinical deployment risks.

AI that gathers a history needs different evidence from AI that records one, including tests of questions, omissions, escalation and clinical handover.

When healthcare agents hold different versions of a plan, safe coordination requires clear status, provenance, ownership and confirmation of what actually happened.

Understand the separate privacy questions around external AI providers, platform storage, clinical records and internal improvement in TORTUS Health.