Clinical documentation · Production

UVM Health Network improves professional fulfillment by 53% with Abridge ambient documentation

The problem

UVM Health Network sought to improve clinician wellbeing and reduce documentation burden that was requiring significant after-hours work and imposing cognitive load on clinicians.

Workflow diagram · grounded in source
1
Natural clinical conversation
Trigger
A natural conversation between clinician and patient initiates the ambient documentation workflow.
source quote
“ability to have a natural conversation”
2
AI note draft generation
Ai action
Abridge generates AI note drafts from the clinical encounter.
source quote
“superior quality of Abridge's AI-generated note drafts”
3
Documentation delivered to clinician
Output
Completed note drafts reduce after-hours documentation burden for clinicians.
source quote
“60% decrease in after-hours documentation”
Reported outcome

Following enterprise-wide rollout of Abridge, UVM Health Network achieved a 53% improvement in professional fulfillment, 60% decrease in after-hours documentation, and 51% decrease in cognitive load.

Reported metrics
Professional fulfillment53%
After-hours documentation60%
Cognitive load51%
Reported stack
Abridge
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Source
https://www.abridge.com/case-study/uvm-health-network
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Frequently asked questions

What did this team achieve with this AI workflow?

Following enterprise-wide rollout of Abridge, UVM Health Network achieved a 53% improvement in professional fulfillment, 60% decrease in after-hours documentation, and 51% decrease in cognitive load.

What tools did this team use?

Abridge.

What results were reported?

Professional fulfillment: 53%; After-hours documentation: 60%; Cognitive load: 51% (source-reported, not independently verified).

How is this clinical documentation AI workflow structured?

Natural clinical conversation → AI note draft generation → Documentation delivered to clinician.

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