Ambient AI has made outpatient documentation easier. But no solution has addressed the far more complex documentation of an inpatient stay in a way that serves both clinicians and downstream revenue cycle teams.
One multi-hospital health system found a different answer. Its hospitalists and inpatient specialists now use a tool that reasons through the entire clinical record the way a clinician would, recommends diagnoses with the supporting evidence attached and drafts diagnosis-complete documentation for the full inpatient stay.
This session walks through how the program was scoped across the admission history and physical, progress notes and discharge summaries; how governance was set at the system and specialty level; how physician adoption was earned; and the impact on quality and financial metrics once the right diagnosis was captured at the point of care.
You’ll learn:
- Why AI scribes fall short on inpatient documentation
- How the health system earned physician trust in AI-recommended diagnoses through cited evidence and clinician-controlled note styles
- How to set documentation governance across provider groups and specialties without flattening physician autonomy
- What shifts downstream for mid-revenue cycle teams when the diagnosis is complete before the note is signed