Department of Industrial and Manufacturing Systems Engineering, College of Engineering, University of Missouri, Columbia, MO, 65211, USA.
Department of Marketing, Trulaske College of Business, University of Missouri, Columbia, MO, 65211, USA.
Health Care Manag Sci. 2020 Sep;23(3):360-386. doi: 10.1007/s10729-019-09501-4. Epub 2020 Feb 20.
Even though several clinics serve patients in more than one stage (e.g., visit nurse and then visit doctor) and employ multiple providers in each stage, most of the previous work on appointment system design considers a simplified single-stage single-server clinic. Motivated by a real-life clinic setting, this paper aims to determine the schedule configuration of a hybrid appointment system (i.e., the number of pre-booking and same-day time slots reserved for a physician along with their positions in the schedule) for a two-stage multi-server clinic. A stochastic optimization model is developed to obtain a schedule configuration that minimizes the expected total cost - a weighted sum of excessive patient waiting time, resource idle time, resource overtime, and denied appointment requests. Owing to its computational complexity, we estimate the expected total cost using the sample average approximation method. The proposed model is verified and validated using small test instances and subject matter experts. A case study of a family medicine clinic in Pennsylvania is used to illustrate the proposed approach. The schedule generated by the proposed model results in a significantly lower expected cost compared to the approximated single-stage system's best schedule configuration and clinic's existing configuration. Further, sensitivity analysis is conducted to assess the impacts of no-show rate, service time variation, and cost ratios on the schedule configuration. Our findings demonstrate that the schedule configuration is sensitive to changes in the average no-show rate and cost ratios but is not significantly impacted by service time variation. Several managerial insights are also drawn from our analysis. Finally, we provide directions for future research that also highlights the potential to use the revenue management approach to address the problem under study.
尽管有几家诊所为多个阶段的患者提供服务（例如，访视护士，然后访视医生），并在每个阶段雇用多个提供者，但之前关于预约系统设计的大部分工作都考虑了简化的单阶段单服务器诊所。受现实生活中的诊所环境的启发，本文旨在确定混合预约系统（即，为医师预留的预购和当天时段的数量以及其在时间表中的位置）的时间表配置，适用于两阶段多服务器诊所。开发了一个随机优化模型，以获得一种时间表配置，该配置可将预期的总成本（即过度的患者等待时间，资源空闲时间，资源加班时间和拒绝预约请求的加权总和）最小化。由于其计算复杂性，我们使用样本平均逼近方法来估计预期总成本。使用小型测试实例和主题专家对所提出的模型进行了验证和验证。宾夕法尼亚州的一家家庭医学诊所的案例研究用于说明所提出的方法。与近似的单阶段系统的最佳时间表配置和诊所的现有配置相比，所提出的模型生成的时间表可显着降低预期成本。此外，还进行了敏感性分析，以评估未到率，服务时间变化和成本比对时间表配置的影响。我们的研究结果表明，时间表配置对平均未到率和成本比的变化敏感，但不受服务时间变化的显着影响。我们还从分析中得出了一些管理见解。最后，我们提供了未来研究的方向，同时还强调了使用收益管理方法来解决研究中问题的潜力。
