Patient Preference Scheduling with Dynamic Rate Queues

Abstract

Healthcare systems in the United States have begun to focus on effective outpatient scheduling strategies as an efficient way to mitigate the logistical and financial pressures brought on by recent healthcare reform efforts. One particular strategy of interest is patient preference scheduling, which focuses on providing patient-driven access to care by actively seeking to accommodate the patients' appointment preferences. While several models exist for outpatient appointment scheduling in general, patient preference modeling has not been well-explored and implementation of the strategy remains challenging. This thesis presents a novel, dynamic rate queueing model for patient preference demand, using a Mt/Gt/Infinity queue, where the service time distribution represents the patient preference distribution. Initial results of this model yield estimated capacity targets for each day of the week to inform staffing decisions for a large integrated healthcare provider system.