Ambient Artificial Intelligence Scribes in Pediatric Hematology-Oncology: Early Implementation of DAX Copilot

Abstract

BACKGROUND: Ambient artificial intelligence scribes are increasingly integrated into electronic health records to reduce documentation burden, but limited data describe their performance in high-complexity pediatric subspecialties. OBJECTIVES: To describe early implementation of Dragon Ambient Experience (DAX) Copilot in a pediatric hematology-oncology division and evaluate patterns of use, documentation time, and workflow effect among providers who adopted the tool. METHODS: We reviewed outpatient encounters from January to July 2025 and identified those using DAX. Analyses focused on providers who used DAX more than twice, given low overall adoption. Documentation time (minutes spent in active editing sessions) and note-closure timeliness were compared between DAX and non-DAX encounters. Implementation processes, barriers, and accuracy concerns were qualitatively summarized. RESULTS: Of 11,544 outpatient encounters, 427 (3.7%) involved DAX; 10 of 29 providers used DAX at least once, while 6 (20.7%) used it more than twice. Among repeat users, for shorter encounters (≤40 minutes), median documentation time was lower for DAX vs. non-DAX (11 [IQR 13] vs 24 [IQR 30] minutes), corresponding to an approximately 30% lower documentation time (95% CI, 19.9%-38.4%; p < 0.001). For longer encounters (>40 minutes), documentation time did not differ significantly. Although unadjusted analyses showed lower rates of same-day and 7-day note closure with DAX, these differences were not significant after adjustment in mixed-effects logistic regression models. Providers reported improved engagement with families and narrative drafting; limitations were related to workflow alignment rather than transcription accuracy. CONCLUSIONS: For repeat users, DAX reduced active documentation time in shorter visits but showed limited benefit for longer encounters and did not improve timeliness of note closure. Adoption remained modest, underscoring the importance of workflow fit and usability considerations in AI-scribe deployment.

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