Utilizing Artificial Intelligence-driven Virtual Standardized Pediatric Patients to Enhance Primary Healthcare Doctors' Capabilities for Managing Common Pediatric Diseases in China: A Randomized Controlled Trial

What this Trial Is About

Researchers are evaluating the use of artificial intelligence-driven virtual standardized patients (VSPs) to improve the ability of primary care doctors in China to manage common pediatric diseases. The study addresses challenges in China's pediatric healthcare system, including limited capacity in primary care and a lack of effective training tools. It involves a randomized controlled trial with over 459 doctors from various specialties across more than 10 provinces, aiming to enhance pediatric care through innovative training methods. The trial involves three groups: one using a virtual patient platform where doctors interact with AI-driven simulated patients covering diseases like pneumococcal pneumonia, rotavirus enteritis with hypovolemic shock, hand-foot-and-mouth disease, acute appendicitis, and respiratory failure; another group uses case teaching manuals, and the third group uses case teaching videos. Participants engage in a two-week learning period with their assigned training method. During the study, doctors' management skills will be assessed through clinical vignettes to measure adherence to best clinical practice guidelines. Researchers will monitor diagnosis accuracy, examination scores relevant to disease handling, and doctors' focus on patient needs. The study runs for about six months and includes over 300 primary healthcare institutions to ensure wide representation. The trial also evaluates the acceptance and costs of the training methods used.

Artificial Intelligence-driven Virtual Standardized Pediatric Patients Trial