Noah Stanton, Aadam Aziz, Salim Jakhra, Solomon Wong, Louise Morganstein, Paul Bassett, Mark Brewerton, Sirous Golchinheydari, D Brogan, Denusha Pushparajah
Aims and method Artificial intelligence ambient voice technology (AI AVT), which uses a large language model to summarise clinical dialogue into electronic notes and GP letters, has emerged. We conducted a mixed-methods, pre–post (manual versus AVT-assisted documentation) service development pilot to evaluate its use in a child and adolescent out-patient clinic. Results The median administration time per clinical encounter reduced from 27 min (manual) to 10 min (AVT) ( P < 0.001). On average, AVT-assisted documentation required only 45% of the time for manual documentation ( P < 0.001). Clinician-rated accuracy, quality and efficiency were significantly higher for AVT-assisted documentation. Patient acceptance was high, with 97% reporting that clinicians were not distracted by note-taking. Thematic analysis from focus groups identified positive effects derived from AVT (improved productivity and clinician well-being), but was balanced by barriers (technological limitations). Clinical implications Integration of AVT into clinical workflows can significantly alleviate documentation burden, reduce cognitive strain and free up clinical capacity.