Effects of an ambient AI scribe used to document patient encounters in hospital: a prospective, multisite, multidisciplinary before-and-after cohort study

Abstract

Assess effects of an ambient artificial intelligence (AI) scribe on documentation time, note quality, clinician and patient experience in clinician–patient encounters. Prospective, multisite, mixed-methods, before-and-after cohort study of an ambient voice to text AI scribe generating clinical notes conducted in four Australian hospitals involving 58 clinicians comprising doctors (n=39), allied health professionals (n=14) and nurses (n=5) with 621 and 338 patients undergoing non-scribe and scribe encounters, respectively. Median total encounter time per encounter overall significantly reduced by 2.0 min (p<0.001); larger reductions for mental health (8.5 min; p=0.001) and allied health (11.8 min; p<0.001) encounters. Note quality averaged ≥3.8 on 5-point Likert scale (1=not at all; 5=extremely good) across 9 quality axes. Scribe use significantly improved 14 of 16 dimensions of professional fulfilment and burnout, with most clinicians reporting the scribe improved documentation efficiency (80.0%) and note quality (57.2%). Most patients reported better encounter quality (64.1%), clinicians listening more (75.2%), providing more explanation (74.5%) and being more empathetic (71.2%). Using an ambient AI scribe for clinician-patient encounters reduces documentation burden, enhances clinician fulfilment and satisfaction and improves quality of interactions for patients. Effects of longer-term scribe use on professional efficiency and well-being, and patient care and outcomes warrant investigation.