Hardship Financing in Healthcare among Rural Residents in the Gaibandha District: An Application of Binary Logistic Regression
DOI:
https://doi.org/10.54536/ajebi.v4i2.5387Keywords:
Bangladesh, Binary Logistic Regression, Gaibandha District, Hardship Financing, Out-of-PocketAbstract
High out-of-pocket expenditures lead to financial hardship in the absence of health insurance coverage, which is prevalent in low- and middle-income countries, including Bangladesh. Households often incur “hardship financing” when they face additional losses by borrowing from a bank, microfinance, or moneylender (with interest) and selling assets, which was 31.4% of 516 sampled respondents in the rural areas of the Gaibandha district in Bangladesh, selected as the study area. In contrast, financing in healthcare by current income or savings, and borrowing from relatives or friends (without interest), is termed “no hardship financing”, which was 68.6%. To investigate the factors affecting the risk of “hardship financing” as the outcome variable with “Yes or No” category, a binary logistic regression was applied, including six independent variables that made statistically significant contributions to the model, such as age, education, family size, the distance to the hospital, outpatient expenditures, and chronic illness. Subsidized healthcare services or health insurance schemes, and accessing to a wealthier social network were suggested, which may protect against the risk of hardship financing. Besides, establishing more healthcare facilities in remote areas with assured quality has been emphasized. Hence, to achieve universal health coverage, policymakers should consider the significant factors associated with hardship financing.
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