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Impact of Unrestricted Artificial Intelligence Scribe Deployment in a Single Health System on Clinician Workload and
Sara E Booth1, Ryan Gould1, Nancy Cibotti2
1Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts (S.E.B., R.G., S.L.).
Background:
Ambient artificial intelligence (AI) medical scribes may reduce documentation burden and clinician burnout. Whether use intensity drives benefits remains uncertain.
Objective:
To evaluate the association between AI scribe (Heidi) enrollment and documentation burden and whether changes differ by use intensity.
Design:
Retrospective quality improvement study using an interrupted time series (ITS) indexed on each clinician's enrollment month adjusted for patient demographics and visit complexity. A secondary 3-group ITS compared enrolled nonusers, low users, and high users.
Setting:
14-hospital health system in Boston, Massachusetts.
Participants:
902 outpatient clinicians enrolled in Heidi; 605 users and 297 enrolled nonusers.
Intervention:
Heidi enrollment after system-wide implementation beginning January 2025.
Measurements:
The primary outcome was note-active time. Secondary outcomes included same-day and after-hours note closures, note length, and work relative value units (wRVUs).
Results:
1 637 227 encounters had notes authored by enrolled clinicians between 1 July 2024 and 31 January 2026. Enrollment was associated with an immediate reduction in note-active time (-1.21 minutes [95% CI, -1.74 to -0.68 minutes]), with larger reductions among high users (-2.50 minutes [CI, -3.55 to -1.45 minutes]) than nonusers (difference, -2.20 minutes [CI, -3.46 to -0.95 minutes]) and low users (difference, -1.72 minutes [CI, -3.03 to -0.40 minutes]). High users had greater increases in note length than nonusers (difference, +170.90 characters [CI, 21.07 to 320.70 characters]) and low users (difference, +270.70 characters [CI, 131.04 to 410.36 characters]). No differences were observed in same-day closure, after-hours closure, or wRVUs.
Limitation:
Observational design with potential unmeasured confounding; inability to distinguish AI-scribed from clinician-authored notes postenrollment.
Conclusion:
Heidi enrollment was associated with reductions in documentation time and increases in note length, concentrated among high users. Enrollment was not associated with improvements in same-day, after-hours note closures, or wRVUs.
Primary Funding Source:
None.
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