Xie Xiaolei, Fan Zhenghao, Li Yan, Kang Jian, Zhang Donglan
Center for Healthcare Service Research, Department of Industrial Engineering, Tsinghua University, Beijing, China.
Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Prev Med Rep. 2021 Oct 6;24:101586. doi: 10.1016/j.pmedr.2021.101586. eCollection 2021 Dec.
Population-based health policies play an important role in preventing and controlling chronic disease. Policymakers need to understand both the short- and long-term impacts of different policies to optimize resource allocation. The objective of this study is to develop a framework that combines econometric analysis and simulation modeling for a comprehensive evaluation of population-based health policies.
Both econometric analysis and simulation modeling were used to evaluate the impact of a population-based health policy.
We identified a cohort of hypertensive patients from the 2011-2013 China Health and Retirement Longitudinal Study and fitted the data into our framework to evaluate the effectiveness of a community-based hypertension-screening program under the Essential Public Health Services (EPHS) policy on the future burden of cardiovascular disease in China.
Using an econometric approach, we identified that the community-based hypertension screening program would lead to a 7.9% improvement in the rate of hypertension control. Using a validated simulation model, we further estimated that if the policy was fully implemented nationwide, it could avert 97,100 cases of myocardial infarction and 215,600 cases of stroke. The policy would cost $2131 on average to save 1 quality-adjusted life year over 10 years.
This study proposed a framework integrating two different methods and assessing both short- and long-term impact of a population-based health policy. Through a case study, we demonstrated that combining econometric analysis and simulation modeling could provide policymakers with a more powerful tool to evaluate health policies for controlling chronic disease.
基于人群的健康政策在慢性病防控中发挥着重要作用。政策制定者需要了解不同政策的短期和长期影响，以优化资源配置。本研究的目的是开发一个框架，将计量经济学分析和模拟建模相结合，以全面评估基于人群的健康政策。
采用计量经济学分析和模拟建模来评估基于人群的健康政策的影响。
我们从2011 - 2013年中国健康与养老追踪调查中确定了一组高血压患者，并将数据纳入我们的框架，以评估基本公共卫生服务（EPHS）政策下基于社区的高血压筛查项目对中国未来心血管疾病负担的有效性。
使用计量经济学方法，我们发现基于社区的高血压筛查项目将使高血压控制率提高7.9%。使用经过验证的模拟模型，我们进一步估计，如果该政策在全国全面实施，可避免97100例心肌梗死和215600例中风。该政策在10年内平均花费2131美元可挽救1个质量调整生命年。
本研究提出了一个整合两种不同方法并评估基于人群的健康政策短期和长期影响的框架。通过案例研究，我们证明将计量经济学分析和模拟建模相结合可以为政策制定者提供一个更强大的工具来评估控制慢性病的健康政策。
