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. 2024 Jan-Dec:61:469580241309903.
doi: 10.1177/00469580241309903.

Out-of-Pocket Health Expenditure and Associated Factors: Insights From National Health Accounts (NHA) Using Panel Data Analysis

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Out-of-Pocket Health Expenditure and Associated Factors: Insights From National Health Accounts (NHA) Using Panel Data Analysis

Sameer A Sofi et al. Inquiry. 2024 Jan-Dec.

Abstract

This study investigates the relationship between out-of-pocket (OOP) healthcare spending, economic growth, population growth, and government health expenditure as a proportion of general government expenditure using National Health Accounts (NHA) estimates. Out-of-Pocket (OOP) healthcare spending imposes a substantial financial burden on households, especially in developing economies such as India. Understanding the factors that influence OOP payments is crucial for policymakers seeking to enhance healthcare systems and achieve Universal Health Coverage (UHC). High OOP expenditures often lead to impoverishment and inequitable access to healthcare, making it a critical area for reform. Despite the well-known negative economic and social consequences of high OOP spending, there is limited research that thoroughly examines the interplay between key economic variables such as economic growth, population growth, and government healthcare expenditure (GHE) as a proportion of general government expenditure (GGE) in shaping OOP healthcare spending. Furthermore, although the National Health Accounts (NHA) offers comprehensive data across Indian states, few studies have leveraged this data to explore the dynamics of these factors. This study aims to fill this gap by providing empirical insights into how these economic and demographic elements influence OOP healthcare spending in India. The analysis employed fixed and random effects models on data from 19 Indian states spanning the years 2013-14 and 2019-20. Fixed effects models were selected based on the results of the Hausman test, which indicated that these models were more effective for controlling unobserved heterogeneity across states.The results indicate that a 1% increase in Gross State Domestic Product is associated with a 0.5% reduction in OOP payments. No significant relationship was identified between population growth or GHE/GGE ratio and OOP healthcare spending. These results imply that while economic growth can contribute to lowering healthcare costs, other factors, such as public health spending, may not be as effective unless they are more strategically targeted. The study underscores the vital role of economic growth in reducing OOP healthcare spending, especially in states facing significant financial burdens. Policymakers should consider aligning economic growth strategies with healthcare reforms to ensure that the benefits of development lead to reduced OOP expenditures. As the findings also suggest that GHE/GGE does not significantly affect OOP costs, policymakers should enhance the targeting and efficiency of public health expenditures while expanding health insurance coverage, and strengthening primary healthcare systems to mitigate OOP costs.

Keywords: Government Health Expenditure (GHE); NHA estimates; economic growth; out-of-pocket (OOP) expenditure; panel data.

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Conflict of interest statement

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Panel line plots of the variables. State-wise trends of Out-of-Pocket Expenditure (OOP) as a proportion of Total Health Expenditure, Gross State Domestic Product (GSDP), Government Health Expenditure as a ratio of General Government Expenditure, and Population Growth (2014-15 to 2019-20). The figure displays state-level trends across key variables affecting out-of-pocket health spending. log_oopthe represents the log of OOP expenditure as a proportion of total health expenditure; log_gsdp is the log of Gross State Domestic Product; log_ghgg refers to the log of Government Health Expenditure as a ratio of General Government Expenditure; and log_pop is the log of population growth. The graphs illustrate data trends for each state over time (years 2014-15 to 2019-20). Source. National Health Accounts (NHA) Estimates of India from 2014-15 to 2019-20 (https://main.mohfw.gov.in).

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