Journal

How an inaccurate clinical statement can become established history through repeated summaries, and how to trace and correct the downstream record.

A whole-workflow cost model for clinical AI, separating subscription fees, verification effort, released capacity and genuine cash savings.

Healthcare agents turn information into operational consequences, requiring explicit permissions, completion evidence and shared clinical and organisational accountability.

What meaningful AI-note review requires, how to measure its workload and why a fast approval click is not evidence of accurate documentation.

A no-training promise does not establish zero retention or no external processing: follow clinical information through inference, logs, support and deletion.

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

NHS England supplier-registry inclusion is not endorsement: learn how to distinguish self-certification, regulatory status and local deployment approval.

AMIE's selected US primary-care cohort does not validate unrestricted NHS triage; local testing must address population, workflow, records and escalation.

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

TORTUS Health needs evidence for information gathering, clinician review and the whole care service, not only the quality of generated notes.

Compare TORTUS Health and Heidi II through the patient relationship, clinical work, business model, regional access and responsibility for follow-through.

A dated healthcare-agent tracker separating actual functions, regional access, previews, pilots and clinician approval from broad company announcements.