Camarena Health returns 12,800 clinician hours with Freed AI scribe across 24 sites
Camarena Health's providers across 24 clinical sites relied on human scribes, but high turnover and callouts meant providers were working with a new scribe almost every week. Retraining was a recurring burden, and the resulting documentation gaps caused billing delays as providers tried to close over 22 daily notes each.
Camarena tested several AI scribe competitors, including Athena's native AI scribe built directly into their existing EHR, but it did not pass—competitor notes were less concise and accurate than Freed's.
Over 50 clinicians across 24 sites adopted Freed with no heavy training or IT implementation cycle.
Documentation time dropped from roughly 10 minutes to about 2 minutes per visit, returning approximately 12,800 hours to clinicians in a single year—the equivalent of roughly 6 full-time clinicians—while also accelerating the billing cycle.
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Frequently asked questions
What did this team achieve with this AI workflow?
Over 50 clinicians across 24 sites adopted Freed with no heavy training or IT implementation cycle.
What tools did this team use?
Freed, EHR.
What results were reported?
documentation time per visit before Freed: roughly 10 minutes per visit; documentation time per visit after Freed: about 2 minutes; Time saved per visit: 8-minute differential; Total visits analyzed: 96,067 visits (source-reported, not independently verified).
What failed first in this deployment?
Camarena tested several AI scribe competitors, including Athena's native AI scribe built directly into their existing EHR, but it did not pass—competitor notes were less concise and accurate than Freed's.
How is this clinical documentation AI workflow structured?
Providers deliver patient care → Freed AI generates clinical note → Clinician reviews and finalizes note → Ready note signed by clinician → Billing cycle accelerated.