Inequalities in financial risk protection in Bangladesh: an assessment of universal health coverage

• Main Authors: Md. Rashedul Islam (Author), Md. Shafiur Rahman (Author), Zobida Islam (Author), Cherri Zhang B. Nurs (Author), Papia Sultana (Author), Md. Mizanur Rahman (Author)
• Format: Book
• Published: BMC, 2017-04-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12939-017-0556-4; 1475-9276
• Keywords: OOP payment; Catastrophic expenditure; Impoverishment; Hardship financing; Universal health coverage; Inequalities; Public aspects of medicine; RA1-1270
• Source: International Journal for Equity in Health, Vol 16, Iss 1, Pp 1-8 (2017)

Abstract Background Financial risk protection and equity are major components of universal health coverage (UHC), which is defined as ensuring access to health services for all citizens without any undue financial burden. We investigated progress towards UHC financial risk indicators and assessed variability of inequalities in financial risk protection indicators by wealth quintile. We further examined the determinants of different financial hardship indicators related to healthcare costs. Methods A cross-sectional, three-stage probability survey was conducted in Bangladesh, which collected information from 1600 households from August to November 2011. Catastrophic health payments, impoverishment, and distress financing (borrowing or selling assets) were treated as financial hardship indicators in UHC. Poisson regression models were used to identify the determinants of catastrophic payment, impoverishment and distress financing separately. Slope, relative and concentration indices of inequalities were used to assess wealth-based inequalities in financial hardship indicators. Results The study found that around 9% of households incurred catastrophic payments, 7% faced distress financing, and 6% experienced impoverishing health payments in Bangladesh. Slope index of inequality indicated that the incidence of catastrophic health payment and distress financing among the richest households were 12 and 9 percentage points lower than the poorest households respectively. Multivariable Poisson regression models revealed that all UHC financial hardship indicators were significantly higher among household that had members who received inpatient care or were in the poorest quintile. The presence of a member with chronic illness in a household increased the risk of impoverishment by nearly double. Conclusion This study identified a greater inequality in UHC financial hardship indicators. Rich households in Bangladesh were facing disproportionately less financial hardship than the poor ones. Households can be protected from financial hardship associated with healthcare costs by implementing risk pooling mechanism, increasing GDP spending on health, and properly monitoring subsidized programs in public health facilities.