Triage and Referral Behavior Across Patient-Facing Medical AI Products
Year: 2026
Type: preprint
Abstract: ABSTRACT We evaluated nine patient-facing artificial intelligence products using 60 physician-developed standardized clinical cases and 540 multi-turn simulated patient encounters. Although overall triage accuracy showed no statistically significant difference across product categories, referral behavior differed substantially. Branded health AI products more frequently over-triaged low-acuity cases (28% vs 3% vs 2%) and recommended affiliated, fee-requiring clinical services. These findings suggest evaluation of patient-facing medical AI should assess referral behavior alongside overall triage accuracy.
Source: medRxiv
Institution: University of California, Los Angeles
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7203610420