Zhao Heng, Liu Zixian, Li Mei, Liang Lijun
College of Management and Economics, Tianjin University, Tianjin 300072, China.
School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Healthcare (Basel). 2021 Aug 23;9(8):1088. doi: 10.3390/healthcare9081088.
Warranties for healthcare can be greatly beneficial for cost reductions and improvements in patient satisfaction. Under healthcare warranties, healthcare providers receive a lump sum payment for the entire care episode, which covers a bundle of healthcare services, including treatment decisions during initial hospitalization and subsequent readmissions, as well as disease-monitoring plans composed of periodic follow-ups. Higher treatment intensities and more radical monitoring strategies result in higher medical costs, but high treatment intensities reduce the baseline readmission rates. This study intends to provide a systematic optimization framework for healthcare warranty policies. In this paper, the proposed model allows healthcare providers to determine the optimal combination of treatment decisions and disease-monitoring policies to minimize the total expected healthcare warranty cost over the prespecified period. Given the nature of the disease progression, we introduced a delay time model to simulate the progression of chronic diseases. Based on this, we formulated an accumulated age model to measure the effect of follow-up on the patient's readmission risk. By means of the proposed model, the optimal treatment intensity and the monitoring policy can be derived. A case study of pediatric type 1 diabetes mellitus is presented to illustrate the applicability of the proposed model. The findings could form the basis of developing effective healthcare warranty policies for patients with chronic diseases.
医疗保健担保对于降低成本和提高患者满意度可能非常有益。在医疗保健担保制度下,医疗服务提供者会因整个护理过程获得一笔一次性付款,该护理过程涵盖一系列医疗服务,包括初次住院期间及后续再次入院时的治疗决策,以及由定期随访组成的疾病监测计划。更高的治疗强度和更激进的监测策略会导致更高的医疗成本,但高治疗强度会降低基线再入院率。本研究旨在为医疗保健担保政策提供一个系统的优化框架。在本文中,所提出的模型使医疗服务提供者能够确定治疗决策和疾病监测政策的最佳组合,以在预定期间内将预期的医疗保健担保总成本降至最低。鉴于疾病进展的性质,我们引入了一个延迟时间模型来模拟慢性病的进展。在此基础上,我们制定了一个累积年龄模型来衡量随访对患者再入院风险的影响。通过所提出的模型,可以得出最佳治疗强度和监测政策。本文给出了一个1型儿童糖尿病的案例研究,以说明所提出模型的适用性。这些研究结果可为为慢性病患者制定有效的医疗保健担保政策奠定基础。