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The Effect of Ambient Artificial Intelligence Scribes on Trainee Documentation Burden
Donald S Wright1,2,3, Naga Kanaparthy1,2,3, Edward R Melnick1,2
1Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, United States.
Applied Clinical Informatics
|July 2, 2025
Summary
Resident physicians using ambient artificial intelligence scribes experienced reduced documentation burden and improved cognitive load. This study highlights the potential of AI scribes to enhance trainee experience, though further research into learning effects is recommended.
Area of Science:
- Medical Informatics
- Artificial Intelligence in Healthcare
- Physician Training
Background:
- Ambient artificial intelligence (AI) scribes are emerging commercial tools in generative AI.
- Limited research exists on AI scribe impact on resident physician trainees compared to attending physicians.
Purpose of the Study:
- To evaluate trainee experience with ambient AI scribes.
- Key measures included usability, acceptability, and documentation burden.
Main Methods:
- Prospective observational study with 47 resident trainees over 2 months.
- Utilized NASA Task Load Index (NASA-TLX), System Usability Scale, Net Promoter Score, and AMIA TrendBurden Survey.
- Collected electronic health record (EHR) utilization data.
Main Results:
- High adoption rate: 91.5% of participants used the AI scribe.
- Significant improvement in cognitive load (NASA-TLX scores decreased from 56.3 to 43.3, p < 0.001).
- Improved documentation burden and high acceptability reported; no significant change in time per note.
Conclusions:
- Ambient AI scribes show promise in reducing documentation burden for trainees.
- Further investigation is needed on the impact of AI scribes on trainee learning and expertise development.
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