Department of Pediatric Anesthesiology, Intensive Care and Neonatology, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Technology Management and Economics, Chalmers University of Technology, 412 96 Gothenburg, Sweden.
Int J Environ Res Public Health. 2021 Jan 14;18(2):659. doi: 10.3390/ijerph18020659.
Healthcare systems worldwide are faced with continuously increasing demand for care, while simultaneously experiencing insufficient capacity and unacceptably long patient waiting times. To improve healthcare access and availability, it is thus necessary to improve capacity utilization and increase the efficiency of existing resource usage. For this, variations in healthcare systems must be managed judiciously, and one solution is to apply a capacity pooling approach. A capacity pool is a general, collaborative capacity that can be allocated to parts of the system where the existing workload and demand for capacity are unusually high. In this study, we investigate how basic mean-variance methodology from portfolio theory can be applied as a capacity pooling approach to healthcare systems. A numerical example based on fictitious data is used to illustrate the theoretical value of using a portfolio approach in a capacity pooling context. The example shows that there are opportunities to use capacity more efficiently and increase service levels, given the same capacity, and that a mean-variance analysis could be performed to theoretically dimension the most efficient pooling organization. The study concludes with a discussion regarding the practical usefulness of this methodology in the healthcare context.
全球的医疗体系都面临着医疗需求不断增长的问题，同时也面临着能力不足和患者等待时间过长的问题。为了改善医疗服务的可及性和可用性，有必要提高能力利用率并提高现有资源使用的效率。为此，必须谨慎管理医疗体系的差异，一种解决方案是应用能力池化方法。能力池是一种通用的、协作的能力，可以分配给系统中现有工作量和能力需求异常高的部分。在这项研究中，我们探讨了如何将投资组合理论中的基本均值-方差方法应用于医疗体系的能力池化方法。我们使用基于虚构数据的数值示例来说明在能力池化背景下使用投资组合方法的理论价值。该示例表明，在给定相同能力的情况下，可以更有效地利用能力并提高服务水平，并且可以进行均值-方差分析来理论上确定最有效的池化组织。最后，本文讨论了这种方法在医疗保健背景下的实际有用性。
