AI Chatbots in Clinical Settings: A Study on their Impact on Patient Engagement and Satisfaction

Abstract

Workforce shortages, uneven access, and escalating demand in the U.S. healthcare system cause long wait times, fragmented communication, and low patient involvement.  This study examines how AI-powered chatbots can improve patient engagement and satisfaction by improving response speed, usability, and trust. Mixed-methods design was utilized.  Response times, System Usability Scale (SUS) usability, and trust ratings were examined in simulated survey data from 200 U.S. medical school–affiliated clinic patients.  Thematically examined qualitative data from patient and medical student focus groups. Chatbots lowered average response times to 2.4 minutes from 12.7 minutes for human workers.  Patients reported 72% more satisfaction with SUS scores of 78/100.  Trust averaged 3.8/5, highest with clinician-supervised chatbots.  Thematic analysis identified trust-building, convenience-accuracy balance, and educational integration. AI chatbots should complement clinicians rather than replace them. Chatbots can improve efficiency, usability, and engagement and prepare future physicians to use digital technologies, advancing patient-centered care in the U.S.