Afshar ambient AI (well-being)

A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being

Paciente / Población Intervención / Exposición Comparación Desenlace

In 66 health care practitioners at ambulatory clinics in two states, an ambient AI scribe drafting visit notes reduced work exhaustion and interpersonal disengagement (professional fulfilment did not significantly improve) compared with documentation without ambient AI before each practitioner's activation.

N
66
Diseño
Stepped-wedge, individually randomised pragmatic trial (24 weeks)
Desenlace
Professional fulfilment and work exhaustion/interpersonal disengagement (Stanford PFI; co-primary)
Relevancia
2
ResultadoWork exhaustion/interpersonal disengagement −0.44 points (95% CI −0.62 to −0.25; P<0.001); professional fulfilment +0.14 points (95% CI 0.004–0.28; P=0.04), reported as non-significant. Time on notes −0.36 h/day (95% CI −0.55 to −0.17); 38% of 71,487 notes drafted with ambient AI.
Afshar M, et al. NEJM AI. 2025;2(12). 10.1056/aioa2500945
Discusión y crítica

A randomised implementation showing that ambient AI eases the exhaustion half of burnout and shortens documentation time without degrading note quality, billing codes or diagnosis capture — the safety question that matters to health systems. Small, unblinded and survey-based for its primary outcomes; the professional-fulfilment co-primary was null, the work-outside-work saving vanished once extreme days were trimmed, and 24 weeks is short for a well-being endpoint.