Annals of Internal Medicine· 2026Q1
Impact of Unrestricted Artificial Intelligence Scribe Deployment in a Single Health System on Clinician Workload and Productivity
- 1citations
- Q1SCImago
- 2026year
Short summary
Deployment of the AI scribe 'Heidi' in a health system reduced clinician note-active time by 1.21 minutes per encounter, with high users seeing a 2.50-minute reduction, but did not improve same-day note closures or work relative value units (wRVUs).
AI-generated from the title and abstract; the full text is not read.
Key points
- AI scribe 'Heidi' enrollment reduced note-active time by 1.21 minutes per encounter.
- High users of the AI scribe saw greater reductions in note-active time (-2.50 minutes).
- Note length increased, especially for high users (+270.70 characters compared to low users).
- No significant improvements were observed in same-day note closures or wRVUs.
- The study included 902 outpatient clinicians over 1.6 million encounters.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. Annals of Internal Medicine, 2026 · DOI ↗
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Field: Health Information Management
Health Information ManagementHealth Professions