Managing Appointment-Based Services in the Presence of Walk-in Customers
研究了同时接受预约和无预约患者的医疗机构如何通过数据分析和优化模型制定最优预约安排，发现无预约患者会带来新的不确定性，而优化安排可显著降低成本。
Despite the prevalence and significance of walk-ins in healthcare, we know relatively little about how to plan and manage the daily operations of a healthcare facility that accepts both scheduled and walk-in patients. In this paper, we take a data-analytics approach and develop an optimization model to determine the optimal appointment schedule in the presence of potential walk-ins. Our model is the first known approach that can jointly handle general walk-in processes and heterogeneous, time-dependent no-show behaviors. We demonstrate that, with walk-ins, the optimal schedules are fundamentally different from those without. Our numerical study reveals that walk-ins introduce a new source of uncertainties to the system and cannot be viewed as a simple solution to compensate for patient no-shows. Scheduling, however, is an effective way to counter some of the negative impact from uncertain patient behaviors. Using data from practice, we predict a significant cost reduction (42%–73% on average) if the providers were to switch from current practice (which tends to overlook walk-ins in planning) to our proposed schedules. Although our work is motivated by healthcare, our models and insights can also be applied to general appointment-based services with walk-ins. This paper was accepted by Gad Allon, operations management.