The Bottom Line
- Ask about failure modes and governance before you ask about ‘accuracy’.
- Your key risks are confidentiality, record integrity, and workflow brittleness.
- Look for evidence aligned with NHS expectations (DTAC, clinical safety, audit logging).
Most AI scribe comparisons over-focus on demo performance. In real practice, the differentiators are: where data goes, what gets stored, whether you can audit every change, and whether the system degrades safely when it fails (rather than quietly producing plausible nonsense).
1
Data & privacy
Where is audio processed? Is audio stored? For how long? Can we enforce deletion? What is the default retention? Who has access and how is access logged?
2
Clinical record integrity
Is every note clearly marked as ‘AI draft’? Is there a tamper-evident audit trail of edits? Can you export logs for governance review?
3
Safety & escalation
What happens when the system is unsure? Does it flag uncertainty? Can we switch it off instantly? Is there an incident reporting + vendor response SLA?
4
Operational fit
How does it handle accents, interruptions, multiple speakers, phone calls, and background noise? Is there a ‘pause’ protocol? How do staff learn it safely?
5
Procurement readiness
Do you have DTAC-aligned documentation? Clinical safety artefacts? A clear stance on medical device classification where applicable?
The red-flag answer
If a vendor can’t clearly explain data flow, retention, access controls, and auditability in plain English, treat that as a ‘no’ until proven otherwise.
Practice
Test your knowledge
Apply this concept immediately with a high-yield question block from the iatroX Q-Bank.
SourceNHS England: DTAC (what buyers assess)
Open Link SourceNHS England: Ambient scribing guidance (policy context)
Open Link