Tao LLM (care transitions)

An LLM Chatbot to Facilitate Primary-to-Specialist Care Transitions: A Randomized Controlled Trial

Paciente / Población Intervención / Exposición Comparación Desenlace

In 2,069 patients attending 111 specialists across 24 disciplines at two health centres, a co-designed LLM chatbot (PreA) performing pre-consultation history-taking, preliminary diagnosis, test ordering and referral reports reduced specialist consultation duration compared with no chatbot before the specialist visit, and improved perceived care coordination and communication.

N
2069
Diseño
Three-arm RCT (PreA alone, PreA with staff support, no PreA), two health centres, China
Desenlace
Physician consultation duration, physician-perceived care coordination and patient-reported communication ease (co-primary)
Relevancia
2
ResultadoConsultation 3.14 ± 2.25 vs 4.41 ± 2.77 min (28.7% reduction; P<0.001); physician-perceived care coordination 3.69 ± 0.90 vs 1.73 ± 0.95 (P<0.001); patient-reported communication ease 3.99 ± 0.62 vs 3.44 ± 0.97 (P<0.001). PreA-only and PreA-human arms were equivalent.
Tao X, et al. Nat Med. 2026;32(3):934-942. 10.1038/s41591-025-04176-7
Discusión y crítica

One of the first patient-randomised trials of a patient-facing LLM in routine care, showing an autonomously operating chatbot can shorten specialist visits and that co-design with local stakeholders beat fine-tuning on local dialogue data. Endpoints are process and perception measures rather than clinical outcomes, and the trial ran at two centres.