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Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: A Randomized Trial.

Jaideep S Talwalkar1, David Chartash1, Lisa Zhang1

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Summary
This summary is machine-generated.

Ambient artificial intelligence (AI) scribes improved medical education feedback quality without increasing instructor effort. This AI scribe-assisted workflow shows potential for transforming feedback documentation in medical training.

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Area of Science:

  • Medical Education Technology
  • Artificial Intelligence in Healthcare
  • Clinical Competence Development

Background:

  • High-quality observation and feedback are crucial for medical trainees' clinical competence and professional growth.
  • Faculty face challenges in providing timely written feedback due to documentation burden and competing demands.
  • Ambient AI scribes offer a potential solution by capturing verbal exchanges and generating structured clinical notes.

Purpose of the Study:

  • To evaluate the efficacy of ambient AI scribes in generating educational feedback notes.
  • To assess AI scribe impact during a formative medical interviewing workshop for first-year medical students.

Main Methods:

  • Thirteen instructors were randomized into control (human-only) and intervention (AI scribe-assisted) groups.
  • AI scribe group used AI to transcribe and summarize student-instructor encounters into feedback notes, followed by instructor editing.
  • Feedback quality (EFeCT), task load (NASA-TLX), and usability (SUS) were assessed; factual accuracy of AI summaries was reviewed.

Main Results:

  • AI scribe-assisted feedback (human-edited and unedited) received significantly higher quality scores (median 3.00) than human-only feedback (median 2.00).
  • AI-assisted outputs were longer than human-only narratives, with a 6.8% mischaracterization and 1.7% hallucination rate in unedited summaries, largely corrected by instructors.
  • Task load and usability were comparable between groups, indicating no significant increase in instructor effort with AI assistance.

Conclusions:

  • Ambient AI scribe-assisted workflows enhance the quality of written narrative feedback in medical education.
  • This approach offers a potential solution to documentation burden without increasing instructor workload.
  • AI scribes represent a promising innovation for improving feedback documentation in medical training.