Telemedicine versus In-Person Outpatient Care: Equilibrium, Capacity, and Quality Differentiation

Abstract: Telemedicine has experienced a significant rise in adoption, emerging as a widely utilized mode of healthcare delivery, particularly in the wake of the COVID-19 pandemic. However, its operational impact on traditional in-person visits and its effectiveness in improving overall system performance and social welfare are not well understood. This study explores how telemedicine influences patient behavior, identifies the conditions under which its adoption is beneficial, and examines its potential to enhance system performance and social welfare. We develop a queueing game model with a healthcare provider who is offering both in-person and telemedicine visits. The provider, seeking to optimize system performance, allocates capacity between in-person and telemedicine visits. Patients, acting strategically, decide between in-person visits, telemedicine visits, or balking based on their expected utilities. The model incorporates an in-person follow-up probability after a telemedicine visit to quantify the quality gap between telemedicine and in-person services. We establish the existence of a symmetric Nash equilibrium for patient behavior and determine the provider's optimal capacity allocation. Our findings reveal that the impact of telemedicine adoption on in-clinic system performance and social welfare is influenced by the quality gap and the alignment of provider capacity with patient demand. Specifically, when capacity is sufficient relative to patient demand, telemedicine adoption enhances in-clinic operational efficiency and social welfare only if the quality gap is low. Our results provide a framework for healthcare providers and policymakers to evaluate the viability of telemedicine investments. Key insights include conditions under which telemedicine can be integrated optimally, improves social welfare, reduces in-clinic wait times, as well as when it might exacerbate in-clinic congestion. These findings may help providers decide whether or not to introduce telemedicine and how to balance capacity allocation between telemedicine and in-person services to maximize patient benefits and system efficiency.