What is a validation queue?
The mechanism that keeps low-confidence AI outputs out of the chart until a clinician approves.
In plain language
A validation queue is a list of AI-drafted outputs that need clinician review before they enter the chart. Outputs that fall below a confidence threshold are routed automatically into the queue.
Why it matters
Without a queue, AI safety is binary: either every output is reviewed (slow) or no output is reviewed (unsafe). A queue lets the clinic set a meaningful threshold and review only the items that need it.
Faurenis's approach
Each AI output gets a confidence score that combines model-internal probability with grounding (does every claim point to a source?). Outputs below the clinic threshold are flagged. The admin role sees clearance time as an operational metric — long-lingering items are visible.
Risks & safeguards
- Queue neglect — mitigated by daily admin notifications and dashboard surfacing.
- False-confidence drift — mitigated by held-out evaluation that re-calibrates the threshold quarterly.