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. (C) 2018 Elsevier Ltd. All rights reserved.
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HPRN Community Advisory Council, Sterling, CO USAHPRN Community Advisory Council, Sterling, CO USA
Felzien, Maret
Zittleman, Linda
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High Plains Res Network, Aurora, CO USAHPRN Community Advisory Council, Sterling, CO USA
Zittleman, Linda
Westfall, John M.
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High Plains Res Network, Aurora, CO USA
Univ Colorado, Dept Family Med, Aschutz Med Campus,F496,Acad Off 1, Aurora, CO 80045 USAHPRN Community Advisory Council, Sterling, CO USA