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Artificial intelligence-generated draft replies to patient messages in pediatrics

April S Liang1, Shivam Vedak1, Alex Dussaq2

  • 1Division of Hospital Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA 94304, United States.

JAMIA Open
|November 26, 2025
PubMed

Insights

Pediatric clinicians found artificial intelligence (AI)-generated draft responses useful for reducing perceived task load, despite lower utilization rates compared to obstetric clinicians. This AI tool shows promise for improving efficiency in pediatric care.

Area of Science:

  • Medical Informatics
  • Clinical Practice
  • Artificial Intelligence in Healthcare

Background:

  • Patient messaging systems in healthcare generate significant clinician workload.
  • Artificial intelligence (AI) offers potential solutions for managing communication tasks.
  • Understanding clinician experiences with AI tools is crucial for adoption.

Purpose of the Study:

  • To evaluate the utilization and experiences of AI-generated draft responses among pediatric ambulatory clinicians.
  • To compare pediatric clinician experiences with those of adult specialty clinicians.
  • To assess the impact of AI tools on clinician task load and tool recommendation.

Main Methods:

  • A prospective pilot study was conducted in pediatric and obstetric clinics.
  • Clinicians used an AI feature embedded in the electronic health record to generate draft responses.
  • Data collected included AI draft usage rates and clinician-reported task load via surveys.

Main Results:

  • Pediatric clinicians utilized 13.3% of AI-generated drafts, less than obstetric clinicians (18.3%).
  • Despite lower usage, pediatric clinicians reported a significant reduction in perceived task load.
  • Pediatric clinicians were more likely to recommend the AI tool compared to obstetric clinicians.

Conclusions:

  • AI-generated draft responses are utilized within expected ranges by pediatric clinicians.
  • The AI tool demonstrated utility in reducing perceived task load for pediatric clinicians.
  • AI tools hold potential for enhancing efficiency and mitigating workload in pediatric ambulatory care.
Abstract

Keywords:
artificial intelligenceburnoutlarge language modelspatient communicationprofessional

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