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孟加拉国特定疾病困扰、医疗保健融资以及住院灾难性自付支出

Disease-specific distress healthcare financing and catastrophic out-of-pocket expenditure for hospitalization in Bangladesh.

机构信息

Department of Management Science, Strathclyde Business School, University of Strathclyde, Glasgow, UK.

Population Studies Division, Bangladesh Institute of Development Studies (BIDS), Dhaka, Bangladesh.

出版信息

Int J Equity Health. 2022 Aug 20;21(1):114. doi: 10.1186/s12939-022-01712-6.

DOI:10.1186/s12939-022-01712-6
PMID:35987656
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9392951/
Abstract

BACKGROUND

Financial risk protection and equity are two fundamental components of the global commitment to achieve Universal Health Coverage (UHC), which mandates health system reform based on population needs, disease incidence, and economic burden to ensure that everyone has access to health services without any financial hardship. We estimated disease-specific incidences of catastrophic out-of-pocket health expenditure and distress financing to investigate progress toward UHC financial risk indicators and investigated inequalities in financial risk protection indicators by wealth quintiles. In addition, we explored the determinants of financial hardship indicators as a result of hospitalization costs.

METHODS

In order to conduct this research, data were extracted from the latest Bangladesh Household Income and Expenditure Survey (HIES), conducted by the Bangladesh Bureau of Statistics in 2016-2017. Financial hardship indicators in UHC were measured by catastrophic health expenditure and distress financing (sale/mortgage, borrowing, and family support). Concentration curves (CC) and indices (CI) were estimated to measure the pattern and severity of inequalities across socio-economic classes. Binary logistic regression models were used to assess the determinants of catastrophic health expenditure and distress financing.

RESULTS

We found that about 26% of households incurred catastrophic health expenditure (CHE) and 58% faced distress financing on hospitalization in Bangladesh. The highest incidence of CHE was for cancer (50%), followed by liver diseases (49.2%), and paralysis (43.6%). The financial hardship indicators in terms of CHE (CI = -0.109) and distress financing (CI = -0.087) were more concentrated among low-income households. Hospital admission to private health facilities, non-communicable diseases, and the presence of chronic patients in households significantly increases the likelihood of higher UHC financial hardship indicators.

CONCLUSIONS

The study findings strongly suggest the need for national-level social health security schemes with a particular focus on low-income households, since we identified greater inequalities between low- and high-income households in UHC financial hardship indicators. Regulating the private sector and implementing subsidized healthcare programmes for diseases with high treatment costs, such as cancer, heart disease, liver disease, and kidney disease are also expected to be effective to protect households from financial hardship. Finally, in order to reduce reliance on OOPE, the government should consider increasing its allocations to the health sector.

摘要

背景

财务风险保护和公平性是实现全民健康覆盖(UHC)的全球承诺的两个基本组成部分,全民健康覆盖要求根据人口需求、疾病发病率和经济负担进行卫生系统改革,以确保每个人都能获得医疗服务,而不会面临任何经济困难。我们估计了特定疾病的灾难性自付医疗支出和应急筹资的发生率,以调查 UHC 财务风险指标的进展情况,并按财富五分位数调查了财务风险保护指标的不平等情况。此外,我们还探讨了因住院费用而导致经济困难的决定因素。

方法

为了进行这项研究,我们从孟加拉国统计局于 2016-2017 年进行的最新孟加拉国家庭收入和支出调查(HIES)中提取了数据。UHC 中的财务困难指标通过灾难性医疗支出和应急筹资(出售/抵押、借款和家庭支持)来衡量。我们使用集中曲线(CC)和指数(CI)来衡量社会经济阶层之间不平等的模式和严重程度。我们使用二元逻辑回归模型来评估灾难性医疗支出和应急筹资的决定因素。

结果

我们发现,孟加拉国约有 26%的家庭因住院而发生灾难性医疗支出(CHE),58%的家庭因住院而面临应急筹资。CHE 发生率最高的疾病是癌症(50%),其次是肝病(49.2%)和瘫痪(43.6%)。就 CHE(CI=-0.109)和应急筹资(CI=-0.087)而言,财务困难指标在低收入家庭中更为集中。住院到私立医疗机构、非传染性疾病以及家庭中有慢性病患者会显著增加 UHC 财务困难指标较高的可能性。

结论

研究结果强烈表明,需要建立国家级的社会健康保障计划,特别是针对低收入家庭,因为我们发现 UHC 财务困难指标在低收入和高收入家庭之间存在更大的不平等。监管私营部门并为癌症、心脏病、肝病和肾病等治疗费用较高的疾病实施补贴医疗计划,也有望保护家庭免受经济困难。最后,为了减少对自付费用的依赖,政府应考虑增加对卫生部门的拨款。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0309/9392951/6c830efde88d/12939_2022_1712_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0309/9392951/3654a25eb91d/12939_2022_1712_Fig1_HTML.jpg
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