Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique.
Int J Equity Health. 2020 Jan 31;19(1):17. doi: 10.1186/s12939-020-1126-8.
As elsewhere in low- and middle-income countries, due to limited fiscal resources, universal health coverage (UHC) remains a challenge in Cambodia. Since 2016, the National Social Security Fund (NSSF) has implemented a social health insurance scheme with a contributory approach for formal sector workers. However, informal sector workers and dependents of formal sector workers are still not covered by this insurance because it is difficult to set an optimal amount of contribution for such individuals as their income levels are inestimable. The present study aims to develop and validate an efficient household income-level assessment model for Cambodia. We aim to help the country implement a financially sustainable social health insurance system in which the insured can pay contributions according to their ability.
This study will use nationally representative data collected by the Cambodia Socio-Economic Survey (CSES), covering the period from 2009 to 2019, and involving a total of 50,016 households. We will employ elastic net regression analysis, with per capita disposable income based on purchasing power parity as the dependent variable, and individual and community-level socioeconomic and demographic characteristics as independent variables. These analyses aim to create efficient income-level assessment models for health insurance contribution estimation. To fully capture socioeconomic heterogeneity, sub-group analyses will be conducted to develop separate income-level assessment models for urban and rural areas, as well as for each province.
This research will help Cambodia implement a sustainable social health insurance system by collecting optimal amount of contributions from each socioeconomic group of the society. Incorporation of this approach into existing NSSF schemes will enhance the country's current efforts to prevent impoverishing health expenditure and to achieve UHC.
与中低收入国家的其他地区一样,由于财政资源有限,全民健康覆盖(UHC)在柬埔寨仍然是一个挑战。自 2016 年以来,国家社会保障基金(NSSF)已为正规部门工人实施了一种采用缴款方式的社会健康保险计划。然而,由于难以为这些人员确定最佳缴款额(因为他们的收入水平难以估量),因此,非正规部门工人及其正规部门工人的家属仍然没有被该保险所覆盖。本研究旨在为柬埔寨制定和验证一种有效的家庭收入水平评估模型。我们旨在帮助该国实施一种财务可持续的社会健康保险制度,使被保险人能够根据自己的能力缴纳保费。
本研究将使用柬埔寨社会经济调查(CSES)收集的全国代表性数据,涵盖 2009 年至 2019 年期间,共有 50016 户家庭。我们将采用弹性网络回归分析,以基于购买力平价的人均可支配收入为因变量,以个人和社区层面的社会经济和人口统计学特征为自变量。这些分析旨在为健康保险缴费估算创建高效的收入水平评估模型。为了充分捕捉社会经济异质性,我们将进行子组分析,为城市和农村地区以及每个省分别开发收入水平评估模型。
本研究将通过从社会的每个社会经济群体中收取最佳缴款额,帮助柬埔寨实施可持续的社会健康保险制度。将这种方法纳入现有的 NSSF 计划中,将增强该国目前预防贫困性医疗支出和实现全民健康覆盖的努力。