Department of Mechanical & Industrial Engineering, University of Massachusetts, Amherst, MA, USA.
Stud Health Technol Inform. 2022 Jun 6;290:957-961. doi: 10.3233/SHTI220222.
In primary care allocating appointments to sequential requests can result in sub-optimal scheduling. Optimal scheduling requires hiring of consultants to analyze historical patterns. Many practices focus their resources on larger problems instead of optimizing appointment schedules. We simulate simple heuristics to compare their performance with optimal schedules uncovered using offline optimization models. We use uncapacitated appointment calendars for a nationally representative heterogeneous primary care panel to meet all patients' requests. The stochastic nature of appointment requests gives a distribution for daily appointments and for the uncovered optimal capacity. The First Minimum heuristic gives near-optimal schedules and can be easily implemented in small practices using pen-and-paper, without any investment in computer-systems.
在初级保健中，按顺序分配预约可能会导致次优的调度。最优调度需要聘请顾问来分析历史模式。许多实践将资源集中在更大的问题上，而不是优化预约时间表。我们模拟简单的启发式方法来比较它们的性能与使用离线优化模型发现的最佳时间表。我们使用无能力的预约日历来满足所有患者的需求，为具有代表性的异质初级保健小组提供服务。预约请求的随机性给出了每日预约和未覆盖的最佳容量的分布。第一个最小启发式算法给出了接近最优的调度，并且可以在小实践中使用纸笔轻松实现，而无需在计算机系统上投资。
