Sahoo Pragyan Monalisa, Rout Himanshu Sekhar
HTA-RH, Indian Institute of Public Health, Gandhinagar, India.
Department of Analytical & Applied Economics, Utkal University, Bhubaneswar, India.
Int J Health Plann Manage. 2025 Jul 11. doi: 10.1002/hpm.70008.
Persistent inequality in financial protection mechanisms in healthcare continues to be a major challenge within India's pluralistic health insurance system, disproportionately disadvantaging marginalised groups.
Our study uses NFHS 4 and 5 household data to investigate inequality in health insurance coverage prevalence and transition across socioeconomic and demographic strata. It categorises health insurance coverage based on the number and type of coverage, considering factors such as the provider, pooling mechanism, and target population. We employ descriptive statistics and the concentration index to assess the prevalence of health insurance coverage. To delve deeper into the factors influencing enrolment in different types of coverage, we created 24 mutually exclusive groups at the intersection of sex-income-marriage-caste. These categories, along with other explanatory variables, are analysed for their influence on the enrolment of coverage using multinomial logistic regression models.
Although the proportion of health insurance coverage increased from NFHS 4 to NFHS 5, 59.01% of the sample population still lacked coverage, indicating insufficient progress. Both surveys reveal significant disparities in coverage based on state-level, social, economic, and demographic factors. While the role of social and demographic determinants remains relatively modest, the distributional gradient of insurance prevalence across economic strata and state categories was high. India's pluralistic health insurance system has resulted in the population being covered under different coverage mechanisms. However, among these various types of coverage, the majority of sample households were only single, predominantly under SHI.
The study investigated disparities in health insurance coverage across various social, economic, and demographic segments in India, revealing that inequalities are influenced by a combination of state-level, socioeconomic, and demographic factors. These findings call for a unified and inclusive health financing framework that can address systemic fragmentation. Moving towards a 'One Nation, One Insurance' model offers a transformative pathway to ensure equitable, efficient, and universal health coverage for all Indians. Addressing these determinants presents potential policy tools for improving coverage imbalances, thereby offering opportunities for targeted interventions to mitigate disparities.
在印度多元化的健康保险体系中，医疗保健财务保护机制方面持续存在的不平等仍是一项重大挑战，边缘化群体处于极为不利的地位。
我们的研究使用了全国家庭健康调查（NFHS）4和5的家庭数据，以调查健康保险覆盖普及率以及社会经济和人口阶层之间转变的不平等情况。它根据覆盖范围的数量和类型对健康保险覆盖情况进行分类，同时考虑诸如提供者、统筹机制和目标人群等因素。我们运用描述性统计和集中指数来评估健康保险覆盖的普及率。为了更深入地探究影响不同类型保险参保情况的因素，我们在性别 - 收入 - 婚姻 - 种姓的交叉点创建了24个相互排斥的群体。使用多项逻辑回归模型分析这些类别以及其他解释变量对保险参保情况的影响。
尽管从全国家庭健康调查4到全国家庭健康调查5，健康保险覆盖比例有所增加，但仍有59.01%的样本人口缺乏保险覆盖，这表明进展不足。两项调查均显示，基于州级、社会、经济和人口因素，保险覆盖存在显著差异。虽然社会和人口决定因素的作用相对较小，但保险普及率在经济阶层和州类别之间的分布梯度较高。印度多元化的健康保险体系导致人口被不同的覆盖机制所覆盖。然而，在这些不同类型的保险中，大多数样本家庭仅有一种保险，主要是参加了社会健康保险。
该研究调查了印度不同社会、经济和人口群体在健康保险覆盖方面的差异，表明不平等受到州级、社会经济和人口因素的综合影响。这些发现呼吁建立一个统一且包容的健康融资框架，以解决系统性碎片化问题。朝着“一个国家，一种保险”模式迈进提供了一条变革性途径，以确保所有印度人都能获得公平、高效和全民健康覆盖。解决这些决定因素为改善覆盖不平衡提供了潜在的政策工具，从而为有针对性的干预措施提供机会，以减少差距。
