AI At The Bedside: What Clinicians Actually Notice

Show Notes

• 02:10 — Why the pilot unit was chosen wrong on purpose
• 14:35 — The documentation quality data nobody expected
• 27:50 — Governance: who signs an AI-drafted note
• 41:05 — What Dr. Osei would do differently

Key Takeaways

1. 01Time savings are the wrong first metric — measure cognitive load and note completeness in the first 90 days.
2. 02Every unit needs a clinician champion; centralized rollouts stall at roughly 40% adoption.
3. 03Ambient tools change what clinicians say out loud in the room, which changes the patient relationship.
4. 04Governance must define who owns an AI-drafted note before go-live, not after the first incident.
5. 05The best predictor of sustained use is whether the tool survives a bad night shift.

Transcript Excerpt

YEM: You said something in our prep call that stuck with me — that the pilot unit was chosen wrong on purpose. DR. OSEI: Deliberately. Everyone pilots on their highest performing unit and then wonders why the results don't generalize. We went to the unit with the worst documentation backlog in the system. If it worked there, we'd believe it.