Q: What are the main risks of AI medical scribes in clinical documentation? A: AI scribes commonly omit key symptoms, time course, and safety red flags, pull wrong medication names or doses from messy EHR lists, confuse who said what, and sometimes fabricate links between complaints, diagnoses, or plans. These kinds of errors are central to the risks of AI medical scribes because they can affect follow-up care and patient safety. Q: How can clinics reduce omissions and hallucinations in AI-generated notes? A: Require that every AI draft be line-by-line reviewed by the ordering clinician and use structured templates with clear visit prompts to improve input quality. Track edits by category, spot-check a sample of notes (for example, 10% monthly), and send weekly error dashboards to vendors to demand measurable fixes. Q: What specific review rules should be set inside the EHR for AI scribes? A: Make clear that every AI draft remains a draft and that the ordering clinician owns the final note, with required line-by-line review for history, medications, allergies, assessment, and plan. Block copying AI text directly into orders, e-prescribing, or referrals and enable diff views so clinicians can see what changed from draft to final. Q: How can EHRs make AI authorship and confidence transparent? A: Tag AI-generated sections and show the editing clinician and timestamp, keep the audio snippet linked to each sentence for quick verification, and add a one-click “AI confidence” view if the vendor provides scores. These measures help later readers know what the system produced and reduce version confusion that can lead to errors. Q: What privacy and security measures should be required when implementing AI scribes? A: Require a Business Associate Agreement, verify encryption in transit and at rest, and clarify audio retention policies including where audio is stored, how long it is kept, who can access it, and how it is deleted. Obtain patient consent when required, post clear disclosures in rooms and portals, and offer an opt-out path. Q: For which visits should clinics avoid using AI scribes or use a human-only path? A: Turn off AI capture for severe background noise, mask-muffled speech, or multi-speaker overlap, and for interpreter-mediated visits without compatible capture. Also use a human-only path for high-stakes discussions such as surgical consent or bad‑news conversations, acutely unstable patients, and active psychiatric crises. Q: What vendor information and safety data should procurement teams demand before buying an AI scribe? A: Ask for peer-reviewed evidence or rigorous pilots in your specialty, documented rates of omissions, hallucinations, and bias, and transparency about training data sources, update cadence, and model change logs. Require controls such as on‑prem or region-limited hosting, data deletion options, uptime and response SLAs, and a named clinical liaison for support. Q: How should organizations measure the effectiveness and safety of AI scribes over time? A: Measure time saved per visit and after-hours charting alongside note completeness and accuracy by section, clinician satisfaction and burnout scores, and downstream outcomes such as callbacks, addenda, medication errors, and near misses. Also track equity performance across languages, accents, and assistive devices to detect disparities.