Modeling dependent demand arrivals within an open-access scheduling system

Within an open-access scheduling system, there is an associated risk of managing the clinic's capacity with the expected daily demand. This involves a process of limiting the likelihood of no-shows with prescheduled appointments, while ensuring there are enough available slots for same-day appointment requests. A preliminary discrete-time, discrete-space, stationary infinite-horizon Markov decision process (MDP) model is used to study the impact that batch arrivals have on an open-access scheduling system. The model will assist pediatric dental care providers in determining whether or not to accept batch appointments, where patient demand is dependent on one another. The underlying assumption is that the number of patients within the batch appointment is equal to half of the clinic's total capacity. The objective is to maximize clinic's revenue, while also maintaining timely access to care for patients.