Adaptive appointment scheduling for patient-centered medical homes

Incorporating patient-centered medical home (PCMH) principles, we develop an adaptive appointment scheduling model for a primary care setting. We propose a simulation optimization approach to sequentially schedule appointments to provide desirable schedules from the perspective of both patients and the medical practices. The objective minimizes the weighted expected cost of patient direct and indirect waiting time, physician idle time, and physician overtime. Our efficient data-driven algorithm considers patient preferences and future appointment requests, while employing overbooking to mitigate patient related uncertainties, such as no-shows and lateness. Benchmarking against myopic and optimal algorithms, computational results show that the adaptive scheduling approach provides significant value. The adaptive method provides considerable cost savings even under conditions of high patient uncertainty. In addition, the method produces high quality solutions in little time, thus providing a viable tool for practice.