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Preambient Artificial Intelligence Clinical Documentation Time for Pediatric Residents: A 3-Year Baseline Observational Study
Journal article   Peer reviewed

Preambient Artificial Intelligence Clinical Documentation Time for Pediatric Residents: A 3-Year Baseline Observational Study

Yahya Almodallal, Natalie Ramsy, Lindsey A Knake and Anna Schmitz
Applied clinical informatics, Vol.17(2), pp.288-295
03/2026
DOI: 10.1055/a-2856-4821
PMID: 42015882

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Abstract

The objective of this study is to characterize pediatric resident documentation time using electronic health record (EHR) audit-log-data and to assess interindividual variability in documentation patterns. We conducted a retrospective, longitudinal study at an academic children's hospital, analyzing the EHR audit-log-data between July 1, 2021 and June 30, 2024. All clinical notes to which a pediatric resident contributed were included. Results are shown as descriptive statistics and pairwise comparisons of log-transformed continuous variables were performed using Welch's analysis of variance and Games-Howell post hoc testing. Over 3 years, 79 residents contributed to the documentation of 156,898 clinical notes for an average of 2.1 hours per day. The mean (95% confidence interval) total resident time spent on one note was 12.1 (12.0-12.1) minutes. First-year residents contributed to 51.6% of all notes. More than half of resident note-editing time occurred outside scheduled shift hours (54.4%), including 56.3% of ambulatory note time and 53.0% of inpatient note time. Across the study period, monthly documentation time showed substantial month-to-month fluctuation but only small overall trends, with adjusted time-per-note declining significantly over time for most graduating classes. This single-center study quantified pediatric resident EHR documentation time and found that time was highest among postgraduate year-1 residents, frequently extended into nights and weekends, and varied widely between individuals. The data provide a baseline to inform residency-level workflow optimization and to evaluate interventions that aim to reduce documentation time while preserving quality and educational value.
Electronic Health Records Artificial Intelligence Documentation Humans Internship and Residency Longitudinal Studies Pediatrics - education Retrospective Studies Time Factors

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