Product design question

Design a medical transcription feature (Nova-3 Medical) that clinicians trust.

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Tests product design for a high stakes specialized use case where clinical accuracy and trust are non negotiable.

Define the user precisely: a clinician dictating notes during or after a patient visit, who needs accurate transcription of medical terminology under real time pressure.
Identify the core trust barrier: clinicians will not adopt a tool that silently mistranscribes a drug name, dosage, or diagnosis, since the cost of an error is patient safety, not convenience.
Prioritize accuracy on high risk terms specifically: medication names, dosages, and clinical abbreviations need higher confidence thresholds than general conversational speech.
Design a verification step: flag low confidence transcriptions inline for the clinician to quickly confirm or correct, rather than presenting a single, unverified final note.
Integrate into existing clinical workflow: output formatted to fit directly into the EHR system's note structure, since a tool that creates extra manual work will not be adopted.
Confirm with the interviewer whether the priority is ambient transcription during the visit or dictation after it, since the interface and risk profile differ.

Prioritizes accuracy specifically on high risk terms like medication names and dosages, since a general word error rate improvement does not address the specific failure modes that matter clinically.
Proposes inline confidence flagging for uncertain segments, giving clinicians a fast way to verify exactly the parts most likely to be wrong.
Designs for direct EHR integration, recognizing that clinicians will reject any tool that adds friction to their existing charting workflow.
Frames trust as earned through visible accuracy and easy verification, not through a claim of perfection the clinician cannot check.

Treating this as a general transcription accuracy problem without addressing the specific high risk terms that matter most clinically.
Designing a standalone tool that does not integrate with existing EHR workflows, which clinicians will not adopt.
No verification mechanism, asking clinicians to blindly trust a fully automated note with no way to catch errors.

How would you measure accuracy specifically on medication and dosage terms?
What would you do if a clinician consistently ignored the low confidence flags?
How would this differ for a specialty like radiology versus general primary care?