Abstract

Telemedicine involves remote delivery of healthcare and virtual meetings between patients and doctors. However, its implementation in a traditional hospital can incur extra costs stemming from additional staffing, training, and IT infrastructure requirements. The effort needed by a doctor to treat a patient can be different depending on the mode of treatment. A principal-agent model is developed to find the optimal policy for both the agent (service provider, such as doctors) and the principal (platform, such as a hospital). We assume there are two types of service options, and the doctor prefers the service type with the lower effort cost. If the doctor’s policy is to accept both types of service options, her revenue may increase or decrease with an increase in the arrival rate of the less preferred service option. Offering only the service option with the higher average revenue is preferred if the service model is under the full control of the hospital. More importantly, the doctor and the hospital may not choose the same optimal strategies for certain values of effort costs. We show that this incentive misalignment issue can be solved by offering extra compensation for the less preferred service type of the doctor, which in turn affects the doctor’s strategy as well as the hospital’s rewards. Our study contributes to the literature on service queues with heterogeneous demands, as well as research on implementing telemedicine applications in healthcare systems.

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