Callaghan Hannah J, Potgieter Linke, Le Roux Nadia
Department of Logistics, Stellenbosch University, Stellenbosch, South Africa.
Department of Health and Wellness, Cape Winelands District, Ceres, South Africa.
PLoS One. 2025 Jan 7;20(1):e0310086. doi: 10.1371/journal.pone.0310086. eCollection 2025.
Despite much literature on operations research applied to various healthcare problems, impactful implementation in public healthcare is limited, which often results in allocative inefficiency. This article uses a mobile clinic routing and scheduling problem in the Witzenberg region of South Africa as a case study to demonstrate the improvement of implementation success through cross-disciplinary collaboration, and also to propose a new three-stage approach for modelling a mobile clinic problem that incorporates continuity of care, fairness, and minimisation of distance travelled. Mobile clinics are used in many countries to improve access to healthcare for rural communities. Decision makers must assign farms or villages to mobile clinics, and determine their monthly visit schedules. To improve implementation success, we follow a collaborative three-phased mixed-methods approach with healthcare professionals to improve workload balance, fairness, and transportation cost. During phase 1, qualitative and quantitative data are gathered through qualitative research methods. In phase 2, fairly distributed optimal routes and schedules are designed using a three-stage model that incorporates a multi-vehicle routing problem to determine daily routes, a knapsack problem to establish a fair allocation of these daily routes between different clinics, and another variation on the vehicle routing problem to determine the monthly visit schedule that minimises the distance between the last farm visited on each consecutive day in the case of having to return to a farm the next day. Different input parameter estimations result in different routes and schedules. In phase 3, AHP is performed with main decision makers to determine their preferred solution. Final routes and schedules are designed based on model results, AHP results, and contextual input from decision makers. In our case study, an improved workload balance, a 23% reduction in total distance travelled, and buy-in to implement the changes, were obtained.
尽管有大量关于运筹学应用于各种医疗保健问题的文献,但在公共医疗保健中的有效实施却很有限,这往往导致分配效率低下。本文以南非维滕贝格地区的移动诊所路线规划和调度问题为例,展示通过跨学科合作提高实施成功率,并提出一种新的三阶段方法来对移动诊所问题进行建模,该方法纳入了医疗连续性、公平性以及最小化行程距离。许多国家都使用移动诊所来改善农村社区获得医疗保健的机会。决策者必须将农场或村庄分配给移动诊所,并确定它们的月度访问时间表。为了提高实施成功率,我们与医疗专业人员采用协作式三阶段混合方法,以改善工作量平衡、公平性和运输成本。在第一阶段,通过定性研究方法收集定性和定量数据。在第二阶段,使用一个三阶段模型设计公平分配的最优路线和时间表,该模型包括一个多车辆路线问题以确定每日路线,一个背包问题以在不同诊所之间公平分配这些每日路线,以及车辆路线问题的另一种变体,以确定月度访问时间表,在必须第二天返回农场的情况下,该时间表能使连续几天中最后访问的农场之间的距离最小化。不同的输入参数估计会导致不同的路线和时间表。在第三阶段,与主要决策者进行层次分析法(AHP)以确定他们偏好的解决方案。最终的路线和时间表是根据模型结果、层次分析法结果以及决策者的背景输入来设计的。在我们的案例研究中,实现了工作量平衡的改善、总行程距离减少23%以及对实施这些变化的认可。