How AI-powered consultation services in internet hospitals influence patient satisfaction: A structural analysis

This study explores how AI-powered consultation services in internet hospitals influence patient satisfaction through perceived value and emotions. A dual-path analytical framework was developed: the technical path uses the E-S-QUAL model to assess the quality of intelligent consultation guidance services in terms of efficiency, system availability, privacy, and fulfillment; the experiential path is based on the Patient Experience-Driven Model, which integrates service encounter theory (focusing on patient-system interactions) and the Stimulus-Organism-Response theory (explaining how external stimuli trigger psychological and behavioral responses).

The dual-path framework includes two submodels. The technical path examines how service quality dimensions affect patient satisfaction through perceived value (i.e., patients' subjective evaluation of the service's usefulness and reliability). The experiential path investigates how service encounters-including interaction, recommendation, and security-indirectly influence satisfaction via perceived value and patient emotions. A structural equation model was applied to analyze data from 1113 valid survey responses.

Both paths significantly influenced satisfaction. Fulfillment and privacy had the most significant effects in the technical path. In the experiential path, service encounters impacted satisfaction through perceived value and emotions. Emotions acted as psychological amplifiers, with positive emotions enhancing the positive effect of perceived value on satisfaction, while negative emotions weakened this effect. Notably, service encounters suppressed negative emotions more strongly than they enhanced positive ones.

This study clarifies the dual role of technical service quality and emotional experience in shaping patient satisfaction, providing theoretical and practical insights for optimizing AI-powered healthcare consultations.