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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.