72 minutes returned per clinician per day at an academic medical center — ambient AI scribe
Clinician documentation was the top-cited driver of burnout at an academic medical center. pronix.ai rolled out an ambient AI scribe integrated with Epic across 2,400 clinicians — 72 minutes returned per clinician per day and a 38% drop in reported burnout scores in six months.
- Client
- Academic medical center, 2,400 clinicians
- Industry
- Healthcare Providers
- Platform
- Epic · Azure OpenAI · Nuance DAX-class ambient scribe
*Representative outcome; results vary by client, scope and platform configuration.
The challenge
Clinicians spent 2 hours after clinic closing charts, and 41% self-reported burnout on the Maslach index. Prior scribe pilots stalled because notes weren't Epic-ready and coders had to rework 30% of encounters.
Our approach
Specialty-tuned templates
Note templates tuned per specialty — primary care, cardiology, orthopedics — matched to E/M coding rules and Epic SmartText slots.
Epic-native ingestion
Notes landed in the encounter draft with structured problem-list and med-rec updates — clinician signed, didn't retyped.
Coder-in-the-loop for E/M
Coders reviewed the top 5% highest-value encounters; feedback re-trained the E/M classifier monthly.
Consent and PHI boundary
Explicit patient consent captured in the workflow; ambient audio never left the session — transcript only.
Adoption as a change program
Peer champions in every service line, weekly office hours, and clinician-visible metrics on time saved.
“For the first time in a decade, I finish clinic when clinic ends.”
Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.
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