背景:灾难性卫生支出(CHE)中社会经济不平等的加剧不成比例地影响了弱势群体,使他们陷入财务困境,限制他们获得医疗保健,并加剧他们对发病率的脆弱性。
目的:本研究调查了与CHE相关的社会经济不平等的变化,并分析了2010-11至2018-19年间巴基斯坦这些变化的影响因素。
方法:本文从2009-10年和2017-18年的国民健康账户中提取了自付医疗支出的数据。社会人口统计信息来自2010-11年和2018-19年的家庭综合经济调查。CHE是使用预算份额和支付能力方法计算的。为了评估2010-11年和2018-19年CHE的社会经济不平等,使用了广义和标准集中指数,并采用Wagstaff不平等分解分析方法探讨了各年社会经济不平等的原因。Further,Oaxaca型分解用于评估CHE社会经济不平等随时间的变化。
结果:集中指数显示,与巴基斯坦的2010-11相比,2018-19年CHE的社会经济不平等有所下降。尽管不平等现象有所减少,CHE在2010-11年和2018-19年集中在巴基斯坦的穷人中。不平等分解分析表明,随着时间的推移,财富状况是CHE不平等的主要原因。较高的财富分位数表明了积极的贡献,而较低的分位数对CHE的不平等有负面影响。此外,城市居住导致了亲富人的不平等,而就业的户主,私人医疗保健提供者,住院医疗服务的利用导致了有利于穷人的不平等。在2010年至2018年期间,CHE的社会经济不平等现象显着下降。然而,不平等仍然主要集中在较低的社会经济阶层。
结论:这些结果强调了改善补贴医疗服务的推广和扩大社会安全网的必要性。
BACKGROUND: The increased socioeconomic inequality in catastrophic health expenditure (CHE) disproportionately affects disadvantaged populations, subjecting them to financial hardships, limiting their access to healthcare, and exacerbating their vulnerability to morbidity.
OBJECTIVE: This study examines changes in socioeconomic inequality related to CHE and analyzes the contributing factors responsible for these changes in Pakistan between 2010-11 and 2018-19.
METHODS: This paper extracted the data on out-of-pocket health expenditures from the National Health Accounts for 2009-10 and 2017-18. Sociodemographic information was gathered from the Household Integrated Economic Surveys of 2010-11 and 2018-19. CHE was calculated using budget share and the ability-to-pay approaches. To assess socioeconomic inequality in CHE in 2010-11 and 2018-19, both generalized and standard concentration indices were used, and Wagstaff inequality decomposition analysis was employed to explore the causes of socioeconomic inequality in each year. Further, an Oaxaca-type decomposition was applied to assess changes in socioeconomic inequality in CHE over time.
RESULTS: The concentration index reveals that socioeconomic inequality in CHE decreased in 2018-19 compared to 2010-11 in Pakistan. Despite the reduction in inequality, CHE was concentrated among the poor in Pakistan in 2010-11 and 2018-19. The inequality decomposition analysis revealed that wealth status was the main cause of inequality in CHE over time. The upper wealth quantiles indicated a positive contribution, whereas lower quantiles showed a negative contribution to inequality in CHE. Furthermore, urban residence contributed to pro-rich inequality, whereas employed household heads, private healthcare provider, and inpatient healthcare utilization contributed to pro-poor inequality. A noticeable decline in socioeconomic inequality in CHE was observed between 2010 and 2018. However, inequality remained predominantly concentrated among the lower socio-economic strata.
CONCLUSIONS: These results underscore the need to improve the outreach of subsidized healthcare and expand social safety nets.