Patient Safety Risks from AI Scribes: Signals from End-User Feedback
Dai, Jessica, Huang, Anwen, Nasrallah, Catherine, Croci, Rhiannon, Soleimani, Hossein, Pollet, Sarah J., Adler-Milstein, Julia, Murray, Sara G., Yazdany, Jinoos, Chen, Irene Y.
–arXiv.org Artificial Intelligence
AI scribes are transforming clinical documentation at scale. However, their real-world performance remains understudied, especially regarding their impacts on patient safety. To this end, we initiate a mixed-methods study of patient safety issues raised in feedback submitted by AI scribe users (healthcare providers) in a large U.S. hospital system. Both quantitative and qualitative analysis suggest that AI scribes may induce various patient safety risks due to errors in transcription, most significantly regarding medication and treatment; however, further study is needed to contextualize the absolute degree of risk.
arXiv.org Artificial Intelligence
Dec-5-2025
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