Clinicians lost hours typing patient charts. Now, an AI assistant listens to visits and auto-drafts clinical notes in the EHR.
The largest nonprofit health system in the Intermountain West operates 34 hospitals and over 400 clinics, employing more than 68,000 caregivers who handle nearly a million emergency visits annually.
Clinicians relied on a mix of legacy speech tools, dictation, and templates that failed to reduce the administrative burden of complex documentation...
“Our people love it. I have so many people coming to me saying, ‘Wow, I was going to retire with this EHR shift, now with Dragon Copilot, and my ambient dictation, I'm going to hang around. I think I can serve my patients for a few more years.’”
Nonprofit health system providing medical services and hospital care in the Western US.
Designed and executed a comprehensive adoption strategy and provided training for Intermountain.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Intermountain Health's Clinical documentation is part of this use case:
Related implementations across industries and use cases
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Manual charting bottlenecked rural clinicians. Now, they use a mobile AI scribe to capture visits and instantly draft EMR records.
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Manual scheduling took 3 days, slowing hiring. An AI agent now screens and books interviews in 29 minutes, doubling scheduled volume.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.
Clinicians lost hours typing patient charts. Now, an AI assistant listens to visits and auto-drafts clinical notes in the EHR.
The largest nonprofit health system in the Intermountain West operates 34 hospitals and over 400 clinics, employing more than 68,000 caregivers who handle nearly a million emergency visits annually.
Clinicians relied on a mix of legacy speech tools, dictation, and templates that failed to reduce the administrative burden of complex documentation...
“Our people love it. I have so many people coming to me saying, ‘Wow, I was going to retire with this EHR shift, now with Dragon Copilot, and my ambient dictation, I'm going to hang around. I think I can serve my patients for a few more years.’”
Nonprofit health system providing medical services and hospital care in the Western US.
Designed and executed a comprehensive adoption strategy and provided training for Intermountain.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Intermountain Health's Clinical documentation is part of this use case:
Related implementations across industries and use cases
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Manual charting bottlenecked rural clinicians. Now, they use a mobile AI scribe to capture visits and instantly draft EMR records.
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Manual scheduling took 3 days, slowing hiring. An AI agent now screens and books interviews in 29 minutes, doubling scheduled volume.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.