Changed or missing medication and allergy facts compared with the supplied transcript and encounter context.
What stays with clinicians
Clinical interpretation, treatment decisions, final note review and sign-off.
Source-to-draft agreement does not establish that the transcript or patient’s reported history is correct.
Working together
Start with one note type.
01 / Scope one task
Choose one workflow.
Agree the setting, errors and review process with your clinical partners.
02 / Compare on your evidence
Compare against current checks.
Measure error risk, extra checks, audits and clinician time.
03 / Evaluate in the workflow
Test within your product.
Agree activation, monitoring and fallback. Clinicians keep final sign-off.
The walkthrough illustrates a proposed evaluation, not a validated clinical deployment.
Who supplies what?
EyeTrustAI
Assess evidence and scorer suitability. Report supported error limits, checking effort and reassessment requirements.
Your product team
Own integration, model and template versions, activation, monitoring and the review experience.
Clinical partners
Provide qualified reviews and resolve disagreements. Retain clinical corrections and final sign-off.
Agree access to original notes and sources, and who supplies reviews and ongoing audits.
The evaluation reports errors, checking effort, costs and assumptions. Proceed only if the evidence supports a worthwhile improvement.
Where EyeTrustAI fits
Source + original draftEncounter ID, transcript snapshot, relevant context, timestamps and model/template versions.
Assessment + review instructionVersioned score and applicable policy; original evidence stays traceable.
Your product’s review experienceA separate working copy, source checks where needed, and explicit clinician sign-off.
We assess a completed draft with its source. Agree latency, cost, hosting, data handling and EHR integration before deployment. Real-time audio processing is not demonstrated here.
Missing source, unsupported language, changed versions or unavailable assessment must retain a defined review path. EyeTrustAI does not write a signed record or replace the clinician’s treatment decisions.
Can existing reviews be reused? How much evidence is needed?
Existing reviews may help if they retain the original draft, the source available at drafting, compatible versions, the agreed error definition and traceable reviewer decisions. Corrected or signed notes alone do not reveal the original error.
Assess source quality, missing cases, selection bias, related visits and separation from scorer development before deciding how evidence can be used. Do not silently treat prior labels as fresh calibration evidence. Changed languages, specialties, note formats or encounter mixes need a scope review; evidence does not automatically transfer.
There is no universal label count or deployment time. Requirements depend on error prevalence, the chosen limit, scorer quality, dependence, reference quality and intended use. In the demo, archived labels are not counted toward a new round.
What remains after activation?
Your product team monitors versions, language, source quality and encounter mix. Assigned clinical reviewers carry out audits and investigate findings. Unchanged models can still face changed populations.
Audit findings arrive after the affected work. A score shift is a prompt to investigate, not proof of an error rate; missed or delayed signals are possible. Agree when reduced checking must stop, who reviews potentially affected notes and what evidence is required to resume.
On suspension, new work returns to additional checking in the existing clinical workflow. Original sources, drafts, review decisions and signed records remain available under the agreed retention policy. A clinical owner decides whether earlier records need review or amendment; the demo does not recall, overwrite or silently correct them.
EyeTrustAI