Medical records processing · Production
86% of Lee Health clinicians do less after-hours work with Abridge AI documentation
The problem
Lee Health clinicians faced burnout from excessive time spent on paperwork and EMR management, cutting into patient care and personal time.
Workflow diagram · grounded in source
1
Pilot framework launch
trigger
“We started our work with Abridge using a pilot framework, and expanded within the first month due to overwhelmingly positive feedback”
2
AI documentation support
ai_action
“equitable access to this AI technology”
3
Same-day note completion
output
“57% more clinicians complete notes the same day”
Reported outcome
After deploying Abridge, 86% of clinicians do less after-hours work, 76% feel they have enough time to document, and 57% more clinicians complete notes the same day, with clinicians reporting enhanced productivity and satisfaction.
Reported metrics
Clinicians doing less after-hours work86%
Clinicians with enough time to document76%
Clinicians completing notes same day57% more
Reported stack
AbridgeAbridge Inside
Frequently asked questions
What did this team achieve with this AI workflow?
After deploying Abridge, 86% of clinicians do less after-hours work, 76% feel they have enough time to document, and 57% more clinicians complete notes the same day, with clinicians reporting enhanced productivity and…
What tools did this team use?
Abridge, Abridge Inside.
What results were reported?
Clinicians doing less after-hours work: 86%; Clinicians with enough time to document: 76%; Clinicians completing notes same day: 57% more (source-reported, not independently verified).
How is this medical records processing AI workflow structured?
Pilot framework launch → AI documentation support → Same-day note completion.