Ambient AI-assisted clinical documentation in surgical outpatient care: a preliminary study of usability, workflow, and patient experience

Abstract

Ambient artificial intelligence (AI) scribes offer promise for reducing documentation burden, yet their effects on surgical practice have not been well defined. We conducted a pilot study of an ambient AI scribe across 79 ambulatory providers (three surgeons) in a multihospital system from December 2024 to February 2025. Surgeon adoption of the AI scribe ranged from 58% to 90% of visits. We evaluated workload via pre- and post-intervention surveys (NASA-TLX mental demand and perceived rush), burnout rates, scheduling capacity, and Epic Signal metrics (note length, time per note) and compared billing data for high utilizers between August and October 2024 and the pilot period. Average "pajama time" did not change significantly (<i>p</i>=0.55). NASA-TLX mental demand decreased from 14 to 5 (<i>p</i>=0.08) and perceived rush from 15 to 5 (<i>p</i>=0.06). Burnout declined from 67% to 33%. Two surgeons reported the capacity to add three patients per clinic. The billing metric showed no significant changes. Undivided attention scores improved from 3.5 to 4.1 (<i>p</i><0.0001). This preliminary data shows promise that ambient AI scribes in surgical clinics may reduce documentation burden and burnout, with potential gains in efficiency and throughput. Larger studies are warranted to further confirm these findings.

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