Artificial intelligence-generated draft replies to patient messages in pediatrics
Pediatric clinicians used AI-generated drafts at a rate within previously reported ranges in adult specialties and experienced utility. These findings suggest this tool has potential for enhancing efficiency and reducing task load in pediatric care.
Authors
- Joshua A. Villarreal (ORCID: https://orcid.org/0000-0001-6380-4880)
- Nicholas Chen
- Natalie M. Pageler (ORCID: https://orcid.org/0000-0002-5853-289X)
- S. Justin Thomas (ORCID: https://orcid.org/0000-0002-8709-4083)
- Keith Morse (ORCID: https://orcid.org/0000-0002-8307-1642)
- Dong-han Yao (ORCID: https://orcid.org/0000-0002-5468-807X)
- Todd A. Townsend (ORCID: https://orcid.org/0000-0001-9501-0540)
- Alex Dussaq (ORCID: https://orcid.org/0000-0001-9946-9551)
- April S. Liang (ORCID: https://orcid.org/0009-0002-3890-4104)
- Shivam Vedak
Institutions
- Palo Alto University (US)
- Stanford Health Care (US)
- Children's Health Council (US)
- Stanford Medicine (US)
- Stanford University (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf159
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00