Appointment overbooking has been commonly adopted for the mitigation of the adverse consequences of patient no-shows, such as reduced resource utilization and revenue. However, if there are more patients showing up than expected, the resource overtime and patient waiting time can increase. Due to the theoretical interest and the practical importance of the problem, there has been much research on the design of appointment schedules for the optimization of various performance measures. The adoption of appointment overbooking can also enhance the accessibility to medical service, by reducing the time between the date of calling for an appointment and the appointment date. Compared with the within-the-session schedule efficiency, the appointment lead time has drawn relatively little attention from researchers. In this research, we propose a framework that utilizes a stochastic mixed-integer linear program, which determines an optimal appointment schedule, for a simulation model for guiding the scheduling decisions. With this framework, we conduct a comprehensive analysis of the tradeoffs between schedule efficiency and accessibility to service. We first derive theoretical properties of our stochastic programming model. Then, we conduct computational experiments to examine the convergence of the stochastic mixed-integer linear programming model, the benefits of optimal appointment scheduling, the effects of two-dimensional uncertainty on the performance of appointment schedules, and the tradeoffs between schedule efficiency and accessibility to service. Our computational experiments suggest that a session capacity approximate to the request rate can balance the multiple conflicting objectives more effectively. We also examine the effects of a dynamic overbooking policy and a non-homogeneous appointment request rate. The computational results suggest that a fixed capacity policy can be as effective as a dynamic overbooking policy under the setting of a constant request rate; but the dynamic overbooking policy leads to a slightly better performance under the setting of a non-homogeneous appointment request rate.

中文翻译：

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预约医疗预约和最佳计划：计划效率与服务可及性之间的权衡

预约超额预订通常已被采用，以减轻患者缺席的不利后果，例如减少资源利用和收入。但是，如果出现的病人比预期多，则资源超时和病人等待时间会增加。由于理论上的兴趣和问题的实际重要性，已经进行了许多用于优化各种绩效指标的任命时间表的研究。通过减少约会的预定日期和约会日期之间的时间，约会超额预定的采用还可以提高获得医疗服务的机会。与会议期间的日程安排效率相比，预约提前期引起了研究人员的较少关注。在这项研究中 我们提出了一个框架，该框架利用随机混合整数线性程序来确定最佳的约会计划，以用于指导计划决策的仿真模型。在此框架下，我们对日程安排效率与服务可及性之间的折衷进行了全面分析。我们首先得出随机规划模型的理论性质。然后，我们进行计算实验，以检验随机混合整数线性规划模型的收敛性，最优约会调度的好处，二维不确定性对约会调度性能的影响以及调度效率与可访问性之间的权衡服务。我们的计算实验表明，接近请求速率的会话容量可以更有效地平衡多个冲突目标。我们还研究了动态超额预订政策和非均匀约会请求率的影响。计算结果表明，在固定请求率的情况下，固定容量策略可以与动态超额预订策略一样有效。但是动态超量预订策略在非均匀约会请求率的设置下会导致更好的性能。计算结果表明，在固定请求率的情况下，固定容量策略可以与动态超额预订策略一样有效。但是动态超量预订策略在非均匀约会请求率的设置下会导致更好的性能。计算结果表明，在固定请求率的情况下，固定容量策略可以与动态超额预订策略一样有效。但是动态超量预订策略在非均匀约会请求率的设置下会导致更好的性能。