Journal

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

Practical scripts for explaining AI scribes, clinical reference searches and digital triage without claiming infallibility or complete security.

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.

Practical digital hygiene for clinical AI covers copying, screenshots, attachments, extensions and account confusion without blaming staff for poorly designed workflows.

Healthcare AI retention should distinguish raw audio, transcripts, approved records and safety evidence, with justified purposes rather than one universal deletion period.

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

UK hosting is one part of a healthcare AI assessment, not proof of safety: map processing, remote access, subprocessors, logs and the applicable transfer arrangements.

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

Clinical AI prompts can remain identifiable after names are removed: learn to distinguish anonymisation from pseudonymisation and minimise a fictional case safely.

Document the material clinical reasoning, verification and final plan when AI contributes to care, without replacing the record with chatbot transcripts.

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