Assessment of out-of-pocket (OOP) expenditures on essential medicines for acute and chronic illness: a comparative study across regional and socioeconomic groups in India.

backgroundSubstantial out-of-pocket (OOP) expenditures push a large portion of the population below the poverty line, especially those residing in rural areas having low incomes. Individuals from economically disadvantaged states in India incur higher healthcare costs for hospitalization in public health centers than do those from more developed states. Economically poorer households in states such as Bihar and Odisha face significantly higher OOP expenditures for hospitalization in public health centers than do those in economically developed states such as Tamil Nadu.

objectiveThis study aims to compare households by using the wealth index and demographic factors concerning OOP expenditures on medicines for acute and chronic illnesses in Odisha, India. METHODOLOGY: A cross-sectional household survey was adopted to conduct the research. Access to medicines focused on OOP expenditures in Odisha is being studied by purposively selecting six districts: Rayagada, Kalahandi, Angul, Keonjhar, Khordha, and Kendrapara. A total of 902 households were surveyed. A stratified random sampling procedure was adopted to select the locations and households. The survey took place from October 2021 to February 2022. The sampled respondents were investigated for acute and chronic illnesses. The software SPSS version 25 was used to analyze the data. The details of the expenditures for the past four weeks were compared with those of medicines and healthcare expenses. Households were categorized into wealthy, middle, and poor classes. The prevalence of acute and chronic illnesses was analyzed in light of the share of medicine expenditures to total household expenditures.

resultsOut of 902 surveyed households, 173 (19.2%) spent out-of-pocket (OOP) money on medicines due to acute and chronic illnesses. Among the studied population, 23.7% were affected by acute illness, whereas 10.9% suffered from chronic illness. Wealthy households constituted most of the OOP expenditure (81 wealthy households), whereas 33 poor households also contributed to the OOP expenditure. According to the unadjusted odds ratio (UOR) analysis, wealthy households were 0.25 times less likely to spend more than 50% of their total monthly household budget on medicine than poor households (UOR = 0.25, 95% CI = 0.09-0.65). Similarly, ST households were 0.18 times less likely to spend more than 50% of their money on medicine from their budgets than SC households (UOR = 0.18, 95% CI = 0.04-0.72).

conclusionThe present study again reveals that capital regions (metropolitan regions) are well protected against OOP expenditures on medicines, but tribal areas are still underserved. The odds ratio reveals a critical positive association between high OOP and poor economic status in households in Odisha. That association must be minimized or nullified for equitable economic and social development.