Journal

Why AI clinical notes must preserve who spoke, who they meant and what they knew, with practical tests for multi-speaker consultations.

An AI scribe must preserve clinical meaning, uncertainty and attribution, because faithfully captured words can still become a misleading summary.

A freshly generated AI answer may rely on outdated guidance, so assess recommendation versions, source updates and retrieval freshness separately.

Choose clinical AI sources by the decision being made: research effects, guideline recommendations, product information and local pathways answer different questions.

Why patient access to AI-generated notes should complement professional checking, with a practical route for reporting and correcting errors.

A practical test of whether refusing an AI tool leaves patients with a credible alternative, rather than a slower or less accessible route to care.

What patient research shows about AI recording, sensitive disclosures and the practical safeguards that could protect honest consultations.

A patient-centred response to healthcare AI harm needs clinical remediation, clear communication, coordinated investigation and distinct routes for complaints and redress.

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

A proposed NHS stop-use framework connects AI safety signals with proportionate restrictions, continuity of care, investigation and explicit reinstatement criteria.

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

AI licences and logins do not establish patient benefit: a proposed NHS dashboard measures outcomes, correction work, access and sustained value.