Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, Dearborn, MI, 48128, USA.
Health Care Manag Sci. 2021 Dec;24(4):742-767. doi: 10.1007/s10729-021-09546-4. Epub 2021 Mar 24.
Patients living with a chronic disease often require regular appointments and treatments. Due to the constraints on the availability of office appointments and the capacity of physicians, access to chronic care can be limited; consequently, patients may fail to receive the recommended care suggested by clinical guidelines. Virtual appointments can provide a cost-effective alternative to traditional office appointments for managing chronic conditions. Advances in information technology infrastructure, communication, and connected medical devices are enabling providers to evaluate, diagnose, and treat patients remotely. In this study, we build a capacity allocation model to study the use of virtual appointments in a chronic care setting. We consider a cohort of patients receiving chronic care and model the flow of the patients between office and virtual appointments using an open migration network. We formulate the planning of capacity needed for office and virtual appointments with a newsvendor model to maximize long-run average earnings. We consider differences in treatment and diagnosis effectiveness for office and virtual appointments. We derive optimal capacity allocation policies and implement numerical experiments. With the model developed, capacity decisions for office and virtual appointments can be made more systematically with the consideration of patient disease progressions.
患有慢性病的患者通常需要定期预约和治疗。由于办公预约和医生能力的限制,获得慢性护理的机会可能有限;因此,患者可能无法接受临床指南建议的护理。虚拟预约可以为管理慢性病提供一种具有成本效益的替代传统办公预约的方式。信息技术基础设施、通信和互联医疗设备的进步使提供者能够远程评估、诊断和治疗患者。在这项研究中,我们构建了一个能力分配模型来研究在慢性病护理环境中使用虚拟预约。我们考虑了一组接受慢性病护理的患者,并使用开放迁移网络对患者在办公和虚拟预约之间的流动进行建模。我们使用报童模型制定办公和虚拟预约所需能力的规划,以最大化长期平均收益。我们考虑了办公和虚拟预约在治疗和诊断效果上的差异。我们推导出最优的能力分配策略并进行数值实验。通过开发的模型,可以更系统地做出办公和虚拟预约的能力决策,同时考虑患者的疾病进展。