{"ID":2834681,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.04118","arxiv_id":"2512.04118","title":"Patient Safety Risks from AI Scribes: Signals from End-User Feedback","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2512.04118","url_pdf":"https://arxiv.org/pdf/2512.04118v1","authors":"[\"Jessica Dai\",\"Anwen Huang\",\"Catherine Nasrallah\",\"Rhiannon Croci\",\"Hossein Soleimani\",\"Sarah J. Pollet\",\"Julia Adler-Milstein\",\"Sara G. Murray\",\"Jinoos Yazdany\",\"Irene Y. Chen\"]","published":"2025-12-01T18:59:54Z","proceeding":"cs.CY","tasks":"[\"cs.CY\",\"cs.LG\"]","methods":"[]","has_code":false}