ArticleJAMIA open2025
Artificial intelligence-generated draft replies to patient messages in pediatrics.
Article in JAMIA open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study describes the utilization and experiences of artificial intelligence (AI)-generated draft responses to patient messages in pediatric ambulatory clinicians and contextualizes their experiences in relation to those of adult specialty clinicians. Materials and Methods: A prospective pilot was conducted from September 2023 to August 2024 in 2 pediatric clinics (General Pediatric and Adolescent Medicine) and 2 obstetric clinics (Reproductive Endocrinology and Infertility and General Obstetrics) within an academic health system in Northern California. Participants included physician, nurse, and medical assistant volunteers. The intervention involved a feature utilizing large language models embedded in the electronic health record to generate draft responses. Proportion of AI-generated draft used was collected, as were prepilot and follow-up surveys. Results: A total of 61 clinicians (26 pediatric, 35 obstetric) enrolled, with 46 (75%) completing both surveys. Pediatric clinicians utilized 13.3% (95% CI, 12.3%-14.4%) of AI-generated drafts, and usage rates when responding to patients vs their proxies was similar (15% vs 12.9%, Discussion and Conclusion: 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.
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