Fleming Rosie, Gartner Daniel, Padman Rema, James Dafydd
School of Mathematics, Cardiff University, Cardiff, Wales, United Kingdom.
National Health Service (NHS), Aneurin Bevan Continuous Improvement Unit (ABCi), Caerleon, United Kingdom.
AMIA Annu Symp Proc. 2020 Mar 4;2019:418-427. eCollection 2019.
In this paper, we report on the development of an analytical model and a decision support tool for meeting the complex challenge of scheduling dialysis patients. The tool has two optimization objectives: First, waiting times for the start of the dialysis after the patients' arrivals must be minimized. Second, the minimization of lateness after the scheduled finish time, which is relevant for transport services, are pursued. We model the problem as a mathematical program considering clinical pathways, a limited number of nurses managing the patients, and dialysis stations. Furthermore, information about patients' drop-off and pick-up time windows at/from the dialysis unit are considered. We develop a platform in Microsoft Excel and implement the analytical model using an Open Source optimization solver. A case study from a dialysis unit in the UK shows that a user can compute a schedule efficiently and the results provide useful information for patients, caregivers, clinicians and transport services.
在本文中，我们报告了一种分析模型和决策支持工具的开发情况，以应对安排透析患者这一复杂挑战。该工具具有两个优化目标：第一，患者到达后开始透析的等待时间必须最小化。第二，追求使预定结束时间后的延迟最小化，这对运输服务很重要。我们将该问题建模为一个数学规划，考虑临床路径、管理患者的护士数量有限以及透析站。此外，还考虑了患者在透析单元的下车和上车时间窗口信息。我们在Microsoft Excel中开发了一个平台，并使用开源优化求解器实现了分析模型。来自英国一家透析单元的案例研究表明，用户可以高效地计算出一份时间表，并且结果为患者、护理人员、临床医生和运输服务提供了有用信息。
