Extending health insurance to the poor in India: An impact evaluation of Rashtriya Swasthya Bima Yojana on out of pocket spending for healthcare

Incentivizing primary care utilization in China: the impact of health insurance coverage on health-seeking behaviour

China's healthcare system faces significant challenges, notably the underutilization of primary healthcare resources and the inefficient distribution of healthcare services. In response, this article explores the effectiveness of the New Rural Cooperative Medical System (NRCMS) in improving healthcare accessibility and primary care utilization. Employing a multi-period difference-in-differences model and using data from the China Family Panel Studies spanning 2012-20, it aims to empirically examine how health insurance policy incentivizing primary care influences rural residents' health-seeking behaviour and enhances the efficiency of resource utilization. Results indicate that NRCMS significantly improves the probability of rural residents seeking healthcare services at primary healthcare centres (PHCs), especially for outpatient services. This effect can be attributed to the substantially higher outpatient reimbursement rates at PHCs compared to higher-level medical institutions. Conversely, the Urban Resident Basic Medical Insurance fails to increase urban residents' engagement with primary care, reinforcing the role of price sensitivity in healthcare choices among insured lower-income rural population. Furthermore, the study reveals a stronger preference for PHCs among younger, less-educated insured residents and highlights a synergistic effect between the availability of primary healthcare resources and insurance coverage on primary care utilization. These findings offer crucial implications for refining health insurance policies to improve healthcare service accessibility and efficiency.

Impact of the targeted poverty alleviation policy on older adults' healthcare utilization: A quasi-experimental analysis from China

China implemented the Targeted Poverty Alleviation (TPA) policy in 2015 to fight against poverty. In order to assess the health performance of the TPA policy, this study aims to evaluate the impact of the TPA policy on healthcare utilization among older adults who normally have higher vulnerability to poverty and diseases. Drawing on data from four waves of the China Health and Retirement Longitudinal Study (CHARLS), we investigated the impact of the TPA policy on older individuals' outpatient and inpatient utilization using the difference-in-differences (DID) approach. In total, 5285 older respondents were incorporated into a final sample. The results indicated that the implementation of the TPA policy had a significantly positive impact on increasing inpatient care utilization for poor older adults. However, its impact on outpatient service utilization was not significant. To ensure that the increased level of inpatient care utilization was not caused by deteriorating health status, we further analyzed the impact of the TPA policy on poor older adults' health outcomes. Results indicated that the TPA policy improved self-rated health and reduced the number of ADL limitations among older adults in registered poor households. The positive impact of the TPA policy on inpatient care utilization was found to be most beneficial for older adults in poor households who were female, coupled, and aged 70 years and above. The TPA policy in China improved healthcare access for economically disadvantaged older adults and contributed to the enhancement of their health outcomes. This evidence may have broad implications for other low- and middle-income countries aiming to reduce poverty and achieve health equity.

Impact of Government-Funded Health Insurance on Out-of-Pocket Expenditure and Quality of Hospital-Based Care in Indian States of Madhya Pradesh and Maharashtra

BACKGROUND

With its clear focus on financial protection, government-funded health insurance (GFHI) stands out among the strategies for universal health coverage (UHC) implemented by low-to-middle income countries globally. Since 2018, India has implemented a GFHI programme called the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), which covers 500 million individuals. The current study aims to evaluate the performance of GFHI in meeting its key objectives of improving access, quality and financial protection for hospital-based care in two large central Indian states: Madhya Pradesh and Maharashtra.

METHODS

The study measures access in terms of utilisation of inpatient care. Financial protection was measured in terms of catastrophic health expenditure which was defined as the incidence of out-of-pocket expenditure (OOPE) above thresholds of 10% and 25% of annual household expenditure. Patient-satisfaction with care was taken as an indicator of quality. A household survey was conducted in 2023, covering a multi-stage sample of 11,569 and 12,384 individuals in Madhya Pradesh and Maharashtra, respectively. Multi-variate analyses were conducted to find the effect of GFHI-enrolment on the desired outcomes. The instrumental variable method was applied to address potential endogeneity in insurance enrolment. Additionally, propensity score matching was done to ensure robustness.

RESULTS

Around 71% and 63% of surveyed individuals were enrolled under GFHI in Madhya Pradesh and Maharashtra, respectively. The hospitalisation rate did not differ much between the GFHI-enrolled and non-enrolled population. The average OOPE on hospitalisation was similar for the GFHI-enrolled and non-enrolled patients. The OOPE and catastrophic health expenditure in private hospitals remained very high, irrespective of GFHI enrolment. The pattern was similar in both states. Multi-variate adjusted models showed that GFHI had no significant effect on utilisation, quality, OOPE and catastrophic health expenditure. The above results were confirmed by propensity score matching.

CONCLUSIONS

Coverage by GFHI enrolment was ineffective in improving access, quality or financial protection for inpatient hospital care despite 5 years of implementation of the programme. Long-standing supply-side gaps and poor regulation of private providers continue to hamper the effectiveness of GFHI in India.

The Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) after four years of implementation - is it making an impact on quality of inpatient care and financial protection in India?

BACKGROUND

India launched a national health insurance scheme named Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) in 2018 as a key policy for universal health coverage. The ambitious scheme covers 100 million poor households. None of the studies have examined its impact on the quality of care. The existing studies on the impact of AB-PMJAY on financial protection have been limited to early experiences of its implementation. Since then, the government has improved the scheme's design. The current study was aimed at evaluating the impact of AB-PMJAY on improving utilisation, quality, and financial protection for inpatient care after four years of its implementation.

METHODS

Two annual waves of household surveys were conducted for years 2021 and 2022 in Chhattisgarh state. The surveys had a sample representative of the state's population, covering around 15,000 individuals. Quality was measured in terms of patient satisfaction and length of stay. Financial protection was measured through indicators of catastrophic health expenditure at different thresholds. Multivariate adjusted models and propensity score matching were applied to examine the impacts of AB-PMJAY. In addition, the instrumental variable method was used to address the selection problem.

RESULTS

Enrollment under AB-PMJAY was not associated with increased utilisation of inpatient care. Among individuals enrolled under AB-PMJAY who utilised private hospitals, the proportion incurring catastrophic health expenditure at the threshold of 10% of annual consumption expenditure was 78.1% and 70.9% in 2021 and 2022, respectively. The utilisation of private hospitals was associated with greater catastrophic expenditure irrespective of AB-PMJAY coverage. Enrollment under AB-PMJAY was not associated with reduced out-of-pocket expenditure or catastrophic health expenditure.

CONCLUSIONS

AB-PMJAY has achieved a large coverage of the population but after four years of implementation and an evidence-based increase in reimbursement prices for hospitals, it has not made an impact on improving utilisation, quality, or financial protection. The private hospitals contracted under the scheme continued to overcharge patients, and purchasing was ineffective in regulating provider behaviour. Further research is recommended to assess the impact of publicly funded health insurance schemes on financial protection in other low- and middle-income countries.

Factors influencing the utilisation of National health insurance program in urban areas of Nepal: Insights from qualitative study

Health insurance has been recognised as a crucial policy measure to enhance citizens' well-being by reducing the financial burden globally. Nepal has also adopted this scheme to support achieving universal health coverage. Various factors influence the overall performance of the program in Nepal. However, there is a lack of evidence on how different factors have influenced the insurance program in the Nepalese context. Therefore, this study aims to explore facilitators and barriers to the utilisation of national health insurance services among service users and other stakeholders. A qualitative study was conducted by interviewing both demand-side participants and supply-side participants in the Bhaktapur District of Nepal. Thematic network analysis was used to analyse data using RQDA software. The socio-ecological model guides the presentation of the identified factors. The study followed the COREQ guidelines to ensure standard reporting of the results. Factors that encourage the use of health insurance services involve individual, community, and policy-related factors. These factors encompass changes in seeking treatment, assistance during enrollment and renewal by enrollment assistant, proximity to the initial point of contact for care, and policy features like individual cards, contribution amount and cashless treatment system. Likewise, lack of physical infrastructure, poor staff management, long waiting times, poor medicine availability, and delays in budget reimbursement were perceived as organisational barriers. At the interpersonal level, obstacles encompass challenges related to staff behaviour, interpersonal relationships, and the information provided by service providers. Identified health services delivery barriers at different levels emphasised the critical need for improving the quality of healthcare and services delivery mechanisms. Overcoming these obstacles is essential for realising health insurance scheme objectives and progressing toward Universal Health Coverage (UHC).

An Examination of Inter-State Variation in Utilization of Healthcare Services, Associated Financial Burden and Inequality: Evidence from Nationally Representative Survey in India

This study examines the health care utilization pattern, associated financial catastrophes, and inequality across Indian states to understand the subnational variations and aid the policy makers in this regard. Data from recent National Sample Survey (2017-2018), titled, "Household Social Consumption: Health," covering 113,823 households, was employed in the study. Descriptive statistics, Erreygers concentration index (CI), and recentered influence function decomposition were applied in the study. We found that, in India, 7 percent of households experienced catastrophic health expenditure (CHE) and 1.9 percent of households were pushed below poverty line due to out-of-pocket expenditure on hospitalization. Notably, outpatient care was more burdensome (CHE: 12.1%; impoverishment: 4%). Substantial interstate variations were observed, with high financial burden in poorer states. Utilization of health care services from private health care providers was pro-rich (hospitalization CI 0.31; outpatient CI 0.10), while the occurrence of CHE incidence was pro-poor (hospitalization CI -0.10; outpatient CI -0.14). Education level, economic status, health insurance, and area of residence contributed significantly to inequalities in utilization of health care services from private providers and financial burden. The high financial burden of seeking health care necessitates the need to increase public health spending and strengthen public health infrastructure. Also, concerted efforts directed towards increasing awareness about health insurance and introducing comprehensive health insurance products (covering both inpatient and outpatient services) are imperative to augment financial risk protection in India.

Improving access to cancer care among rural populations in India: Development of a validated tool for health system capacity assessment

BACKGROUND

Cancer burden in India is rapidly growing, with oral, breast, and uterine cervix being the three most commonly affected sites. It has a catastrophic epidemiological and financial impact on rural communities, the vast majority of whom are socio-economically disadvantaged. Strengthening the health system is necessary to address challenges in the access and provision of cancer services, thus improving outcomes among vulnerable populations.

OBJECTIVE

To develop, test, and validate a health system capacity assessment (HSCA) tool that evaluates the capacity and readiness for cancer services provision in rural India.

METHODS

A multi-method process was pursued to develop a cancer-specific HSCA tool. Firstly, item generation entailed both a nominal group technique (to identify the health system dimensions to capture) and a rapid review of published and gray literature (to generate items within each of the selected dimensions). Secondly, tool development included the pre-testing of questionnaires through healthcare facility visits, and item reduction through a series of in-depth interviews (IDIs) with key local stakeholders. Thirdly, tool validation was performed through expert consensus.

RESULTS

A three-step HSCA multi-method tool was developed comprising: (a) desk review template, investigating policies and protocols at the state level, (b) facility assessment protocol and checklist, catering to the Indian public healthcare system, and (c) IDI topic guide, targeting policymakers, healthcare workforce, and other relevant stakeholders.

CONCLUSIONS

The resulting HSCA tool assesses health system capacity, thus contributing to the planning and implementation of context-appropriate, sustainable, equity-focused, and integrated early detection interventions for cancer control, especially toward vulnerable populations in rural India and other low-resource settings.

Cost of Care for Non-communicable Diseases: Which Types of Healthcare Providers are the Most Economical in India's Chhattisgarh State?

BACKGROUND

Non-communicable diseases (NCDs) affect a large number of people globally and their burden has been growing. Healthcare for NCDs often involves high out-of-pocket expenditure and rising costs of providing services. Financing and providing care for NCDs have become a major challenge for health systems. Despite the high burden of NCDs in India, there is little information available on the costs involved in NCD care.

METHODS

The study was aimed at finding out the average monthly cost of outpatient care per NCD patient. The average cost was defined as all resources spent directly by government and citizens to get a month of care for a NCD patient. The cost borne by the government on public facilities was taken into account and activity-based costing was used to apportion it to the function of providing outpatient NCD care. For robustness, time-driven activity-based costing and sensitivity analyses were also performed. The study was conducted in Chhattisgarh State and involved a household survey and a facility survey, conducted simultaneously at the end of 2022. The surveys had a sample representative of the state, covering 3500 individuals above age of 30 years and 108 health facilities.

RESULTS

The average monthly cost per NCD patient was Indian Rupees (INR) 688 for public providers, INR 1389 for formal for-profit providers and INR 408 for informal private providers and they managed 53.5, 34.3 and 12.0% of NCD patients respectively. The disease profile of patients handled by different types of providers was similar. The average cost per patient was lowest for the primary care facilities in the public sector.

CONCLUSIONS

The average direct cost of NCD care for government and citizens put together was substantially higher in case of formal for-profit providers compared with public facilities, even after taking into account the government subsidies to public sector. This has implications for allocative efficiency and the desired public-private provider mix in health systems.

Health insurance and child mortality: Evidence from India

Although less than a third of the population in developing countries is covered by health insurance, the number has been on the rise. Many countries have implemented national insurance policies in the past decade. However, there is limited evidence on their impact on child mortality in low- and middle-income contexts. Here we document the child mortality reducing effects of an at-scale national level health insurance policy in India. The Rashtriya Swasthya Bima Yojana (RSBY), was rolled out across India between 2008 and 2013. Leveraging the temporal and spatial variation in program implementation, we demonstrate that it lowered infant mortality by 6% and child under five mortality by 5%. The effects are largely concentrated among urban poor households. In terms of mechanisms, we find that the program effects seem to be driven by increased usage of reproductive health services by mothers. We also demonstrate a rise in usage of complementary health services that were were not covered under the policy (such as child immunizations), which suggests that RSBY had significant positive spillover effects on health care usage.

Decomposing the inequalities in the catastrophic health expenditures on the hospitalization in India: empirical evidence from national sample survey data

Introduction

Sustainable Development Goal (SDG) Target 3.8.2 entails financial protection against catastrophic health expenditure (CHE) by reducing out-of-pocket expenditure (OOPE) on healthcare. India is characterized by one of the highest OOPE on healthcare, in conjunction with the pervasive socio-economic disparities entrenched in the population. As a corollary, India has embarked on the trajectory of ensuring financial risk protection, particularly for the poor, with the launch of various flagship initiatives. Overall, the evidence on wealth-related inequities in the incidence of CHE in low- and middle-Income countries has been heterogenous. Thus, this study was conducted to estimate the income-related inequalities in the incidence of CHE on hospitalization and glean the individual contributions of wider socio-economic determinants in influencing these inequalities in India.

Methods

The study employed cross-sectional data from the nationally represented survey on morbidity and healthcare (75th round of National Sample Survey Organization) conducted during 2017-2018, which circumscribed a sample size of 1,13,823 households and 5,57,887 individuals. The inequalities and need-adjusted inequities in the incidence of CHE on hospitalization care were assessed via the Erreygers corrected concentration index. Need-standardized concentration indices were further used to unravel the inter- and intra-regional income-related inequities in the outcome of interest. The factors associated with the incidence of CHE were explored using multivariate logistic regression within the framework of Andersen's model of behavioral health. Additionally, regression-based decomposition was performed to delineate the individual contributions of legitimate and illegitimate factors in the measured inequalities of CHE.

Results

Our findings revealed pervasive wealth-related inequalities in the CHE for hospitalization care in India, with a profound gap between the poorest and richest income quintiles. The negative value of the concentration index (EI: -0.19) indicated that the inequalities were significantly concentrated among the poor. Furthermore, the need-adjusted inequalities also demonstrated the pro-poor concentration (EI: -0.26), denoting the unfair systemic inequalities in the CHE, which are disadvantageous to the poor. Multivariate logistic results indicated that households with older adult, smaller size, vulnerable caste affiliation, poorest income quintile, no insurance cover, hospitalization in a private facility, longer stay duration in the hospital, and residence in the region at a lower level of epidemiological transition level were associated with increased likelihood of incurring CHE on hospitalization. The decomposition analysis unraveled that the contribution of non-need/illegitimate factors (127.1%) in driving the inequality was positive and relatively high vis-à-vis negative low contribution of need/legitimate factors (35.3%). However, most of the unfair inequalities were accounted for by socio-structural factors such as the size of the household and enabling factors such as income group and utilization pattern.

Conclusion

The study underscored the skewed distribution of CHE as the poor were found to incur more CHE on hospitalization care despite the targeted programs by the government. Concomitantly, most of the inequality was driven by illegitimate factors amenable to policy change. Thus, policy interventions such as increasing the awareness, enrollment, and utilization of Publicly Financed Health Insurance schemes, strengthening the public hospitals to provide improved quality of specialized care and referral mechanisms, and increasing the overall budgetary share of healthcare to improve the institutional capacities are suggested.

The relationship between health insurance and economic performance: an empirical study based on meta-analysis

Health insurance stands as a pivotal facet of social wellbeing, with profound implications for the overarching landscape of economic development. The existing research, however, lacks consensus on the relationship between health insurance and economic performance and provides no evidence about the magnitude of the correlation. This lack of information seriously impedes the high-quality development of the healthcare system. Therefore, to scientifically elucidate the relationship between the two, this study involved a meta-analysis, analyzing 479 effect values derived from 34 independent research samples. The results reveal a strongly positive correlation between health insurance and economic performance [r = 0.429, 95% CI = (0.381, 0.475)]. Findings show that health insurance in developed countries more effectively fosters economic performance than in developing countries. Moreover, public health insurance exerts a stronger promoting effect on economic performance than commercial health insurance. The relationship between health insurance and economic performance is moderated by data type, research method, country of sample origin, literature type, journal impact factor, publication year, type of health insurance, and the research populations. Based on meta-analysis, this study not only scientifically responds to the controversy of the relationship between health insurance and economic performance, and the magnitude of a correlation, but also further reveals the inner conduction mechanism between the two. Our research findings are meaningful for policymakers to choose an appropriate healthcare strategy according to their unique attributes, propelling sustainable economic development.

Health and health system effects on poverty: A narrative review of global evidence

Ill-health causes poverty. The effect runs through multiple mechanisms that span lifetimes and cross generations. Health systems can reduce poverty by improving health and weakening links from ill-health to poverty. This paper maps routes through which ill-health can cause poverty and identifies those that are potentially amenable to health policy. The review confirms that ill-health is an important contributor to poverty and it finds that the effect through health-related loss of earnings is often larger than that through medical expenses. Both effects are smaller in countries that are closer to universal health coverage and have higher social safety nets. The paper also reviews evidence from low- and middle-income countries (LMICs) and the United States (US) on the poverty-reduction effectiveness of public health insurance (PubHI) for low-income households. This reveals that PubHI does not always deliver financial protection to its targeted population in LMICs. Countries that have succeeded in achieving this goal often combine extension of coverage with supply-side interventions to build capacity and avoid perverse provider incentives in response to insurance. In the US, PubHI is effective in reducing poverty by shielding low-income households with children from healthcare costs and, consequently, generating long-run improvements in health that increase lifetime earnings. Poverty reduction is a potentially important co-benefit of health systems.

The effectiveness of a government-sponsored health protection scheme in reducing financial risks for the below-poverty-line population in Bangladesh

The Government of Bangladesh is piloting a non-contributory health protection scheme called Shasthyo Surokhsha Karmasuchi (SSK) to increase access to quality essential healthcare services for the below-poverty-line (BPL) population. This paper assesses the effect of the SSK scheme on out-of-pocket expenditure (OOPE) for healthcare, catastrophic health expenditure (CHE) and economic impoverishment of the enrolled population. A comparative cross-sectional study was conducted in Tangail District, where the SSK was implemented. From August 2019 to March 2020, a total of 2315 BPL households (HHs) (1170 intervention and 1145 comparison) that had at least one individual with inpatient care experience in the last 12 months were surveyed. A household is said to have incurred CHE if their OOPE for healthcare exceeds the total (or non-food) HH's expenditure threshold. Multiple regression analysis was performed using OOPE, incidence of CHE and impoverishment as dependent variables and SSK membership status, actual BPL status and benefits use status as the main explanatory variables. Overall, the OOPE was significantly lower (P < 0.01) in the intervention areas (Bangladeshi Taka (BDT) 23 366) compared with the comparison areas (BDT 24 757). Regression analysis revealed that the OOPE, CHE incidence at threshold of 10% of total expenditure and 40% of non-food expenditure and impoverishment were 33% (P < 0.01), 46% (P < 0.01), 42% (P < 0.01) and 30% (P < 0.01) lower, respectively, in the intervention areas than in the comparison areas. Additionally, HHs that utilized SSK benefits experienced even lower OOPE by 92% (P < 0.01), CHE incidence at 10% and 40% threshold levels by 72% (P < 0.01) and 59% (P < 0.01), respectively, and impoverishment by 27% at 10% level of significance. These findings demonstrated the significant positive effect of the SSK in reducing financial burdens associated with healthcare utilization among the enrolled HHs. This illustrates the importance of the nationwide scaling up of the scheme in Bangladesh to reduce the undue financial risk of healthcare utilization for those in poverty.

Is health insurance really benefitting Indian population? Evidence from a nationally representative sample survey

BACKGROUND

Universal health coverage (UHC) is the centrepiece of the sustainable development goals and aims to ensure access to essential and quality healthcare services to all without facing financial hardships. Several health insurance programmes have been launched in India to progress towards UHC.

OBJECTIVE

This study aims to assess the impact of health insurance (overall health insurance, government sponsored health insurance (GSHI), and private voluntary health insurance) on accessibility and utilization of inpatient care, out-of-pocket health expenditure (OOPE), catastrophic health expenditure (CHE), and impoverishment in India.

DATA AND METHODOLOGY

The 75th round of National Sample Survey Office was used in the study, which covered 555,115 individuals, 113,823 households, and 91,445 hospitalization incidence all over India. Descriptive statistics, multivariable logistic regression, and propensity score matching (PSM) methods were employed.

RESULTS

Enrolment under health insurance has impacted the accessibility and utilization pattern of hospitalization to some extent for the insured. PSM showed that enrolment under GSHI schemes reduced OOPE by INR 3314 (USD 49) and CHE incidence by 1%-4% at various thresholds. Among poor persons, there was a marginal but statistically significant reduction of OOPE among those enrolled under GSHI schemes (p < 0.05). However, GSHI schemes did not statistically significantly reduce the CHE burden for poor persons enrolled (p > 0.05). Furthermore, enrolment under private voluntary health insurance reduced OOPE by INR 13,511 (USD 198) and CHE by 13.47% at 10% threshold, 4.61% at 25% threshold, and 2.65% at 40% threshold. However, its uptake was primarily confined to richer economic quintiles and urban areas that exacerbates equity concerns. All the results were confirmed through robustness measures employed.

CONCLUSIONS

There is a necessity to increase awareness and uptake of health insurance, along with introducing comprehensive insurance packages covering both inpatient and outpatient care. Also, increasing public health spending, strengthening public healthcare facilities, and improving regulatory implementation of private healthcare providers are imperative to augment financial protection.

Assessing the impact of public insurance on healthcare utilization and mortality: A nationwide study in China

We investigate the effects of a significant health insurance expansion in rural China known as the New Cooperative Medical Scheme (NCMS). Our analysis is based on a nationwide dataset spanning from 2004 to 2011. We find that the NCMS effectively increases healthcare utilization, particularly inpatient admissions, and reduces the incidence for infectious diseases. In addition to the increased healthcare utilization, the reduction in the incidence for infectious diseases can be attributed to improved health knowledge and health behavior, both of which are associated with the expansion of insurance coverage. Our findings affirm the importance of insurance coverage in safeguarding low-income individuals from the adverse health consequences linked to infectious diseases.

A step closer towards achieving universal health coverage: the role of gender in enrolment in health insurance in India

BACKGROUND

There is limited understanding of how universal health coverage (UHC) schemes such as publicly-funded health insurance (PFHI) benefit women as compared to men. Many of these schemes are gender-neutral in design but given the existing gender inequalities in many societies, their benefits may not be similar for women and men. We contribute to the evidence by conducting a gender analysis of the enrolment of individuals and households in India's national PFHI scheme, Rashtriya Swasthya Bima Yojana (RSBY).

METHODS

We used data from a cross-sectional household survey on RSBY eligible families across eight Indian states and studied different outcome variables at both the individual and household levels to compare enrolment among women and men. We applied multivariate logistic regressions and controlled for several demographic and socio-economic characteristics.

RESULTS

At the individual level, the analysis revealed no substantial differences in enrolment between men and women. Only in one state were women more likely to be enrolled in RSBY than men (AOR: 2.66, 95% CI: 1.32-5.38), and this pattern was linked to their status in the household. At the household level, analyses revealed that female-headed households had a higher likelihood to be enrolled (AOR: 1.36, 95% CI: 1.14-1.62), but not necessarily to have all household members enrolled.

CONCLUSION

Findings are surprising in light of India's well-documented gender bias, permeating different aspects of society, and are most likely an indication of success in designing a policy that did not favour participation by men above women, by mandating spouse enrolment and securing enrolment of up to five family members. Higher enrolment rates among female-headed households are also an indication of women's preferences for investments in health, in the context of a conducive policy environment. Further analyses are needed to examine if once enrolled, women also make use of the scheme benefits to the same extent as men do. India is called upon to capitalise on the achievements of RSBY and apply them to newer schemes such as PM-JAY.

The moderating effect of mental health and health insurance ownership on the relationships between physical multimorbidity and healthcare utilisation and catastrophic health expenditure in India

BACKGROUND

The current demographic transition has resulted in the growth of the older population in India, a population group which has a higher chance of being affected by multimorbidity and its subsequent healthcare and economic consequences. However, little attention has been paid to the dual effect of mental health conditions and physical multimorbidity in India. The present study, therefore, aimed to analyse the moderating effects of mental health and health insurance ownership in the association between physical multimorbidity and healthcare utilisation and catastrophic health expenditure (CHE).

METHODS

We analysed the Longitudinal Aging Study in India, wave 1 (2017-2018). We determined physical multimorbidity by assessing the number of physical conditions. We built multivariable logistic regression models to determine the moderating effect of mental health and health insurance ownership in the association between the number of physical conditions and healthcare utilisation and CHE. Wald tests were used to evaluate if the estimated effects differ across groups defined by the moderating variables.

RESULTS

Overall, around one-quarter of adults aged 45 and above had physical multimorbidity, one-third had a mental health condition and 20.5% owned health insurance. Irrespective of having a mental condition and health insurance, physical multimorbidity was associated with increased utilisation of healthcare and CHE. Having an additional mental condition strengthened the adverse effect of physical multimorbidity on increased inpatient service use and experience of CHE. Having health insurance, on the other hand, attenuated the effect of experiencing CHE, indicating a protective effect.

CONCLUSIONS

The coexistence of mental health conditions in people with physical multimorbidity increases the demands of healthcare service utilisation and can lead to CHE. The findings point to the need for multidisciplinary interventions for individuals with physical multimorbidity, ensuring their mental health needs are also addressed. Our results urge enhancing health insurance schemes for individuals with mental and physical multimorbidity.

Examining the Effectiveness of Financial Protection Schemes in Reducing Health Inequality

Health protection schemes such as health insurance and financial assistance provide immense help and support to access health care services, especially to the poor and marginalized section of society. India is witness to low health-related expenditure, and the society's socioeconomic and demographic structure further drops health care access to the new bottom. Consequently, inequality in health care access is highly observed across many socioeconomic attributes. The condition of Bihar, the poorest state of India, is more alarming. The analysis suggests that financial support in terms of universal health insurance coverage considerably reduces out-of-pocket expenditure and thus health inequality. Further, the low health insurance coverage is not solely due to a lack of institutional commitment and implementation process; the cognitive behavior and attitude of people are equally responsible for low health care access. An intensive awareness program to show the benefit of the health insurance scheme and sensitization of people against the social stigma is important to provide better health care access and reduce health inequality.

Assessing inequalities in publicly funded health insurance scheme coverage and out-of-pocket expenditure for hospitalization: findings from a household survey in Kerala

BACKGROUND

Increasing financial risk protection is a key feature of Universal Health Coverage and the path towards health for all. Publicly Funded Health Insurance Schemes (PFHIS) have been considered as one of the pathways to safeguard against financial shocks and potentially reduce Out-of-Pocket Expenditure (OOPE). The south Indian state of Kerala has roughly a decade-long experience in implementing PFHIS. To date, there have been very few assessments of the coverage of these schemes and their impact on expenditure. Aiming to fill this gap, we explored the extent of and inequalities in insurance coverage, as well as choice of providers, and median cost of hospitalization in Kerala among insured and uninsured individuals.

METHODS

A cross-sectional household survey was conducted in four districts of Kerala as part of a larger health systems research study from July-October 2019. We employed multistage random sampling to collect data from 13,064 individuals covering 3234 households in the catchment area of eight primary health care facilities. We used descriptive statistics, bivariate and multivariate analysis. We evaluated socioeconomic disparities using an absolute measure of inequality-the Slope Index of Inequality (SII) and a relative measure-the Relative Concentration Index (RCI).

RESULTS

A substantial proportion of our study respondents reported that they were covered by PFHIS (45.8%). Respondents belonging to lowest and middle wealth quintiles of household had significantly greater odds of being covered by insurance than respondents belonging to the richest wealth quintile. The negative magnitude of RCI [-16.8% (95%CI: -25.3, -8.4)] and SII [-21.5% (95%CI: -36.1, -7.0)] suggest a higher concentration of PFHIS coverage among the poor. Median OOPE for hospitalisation at private health facilities was INR 9000 (approx. USD 108.70) among those covered by PFHIS, whereas it was INR 10500 (approx. USD 126.82) at private health facilities among those not covered by insurance.

CONCLUSION

While PFHIS seems to be appropriately targeting poorer populations, among the insured, OOPE for hospitalization persists. Among the uninsured, population subgroups with advantage are spending the greatest amount, raising questions about whether those facing relative disadvantage are forgoing care altogether or seeking care using cheaper, public avenues. Further policy action to more effectively reduce financial burden among left behind eligible populations under PFHIS will be essential to UHC progress in the state.

Out-of-pocket expenditure and its correlates for institutional deliveries in private and public healthcare sectors in India: findings from NFHS 5

BACKGROUND

Increased coverage for institutional delivery (ID) is one of the essential factors for improved maternal and child health (MCH). Though, ID increased over time, out-of-pocket expenditure (OOPE) for the care-seeking families had been found to be growing, parallelly. Hence, we estimated OOPE in public and private health centres for ID, along with their sources and attributing factors and compared state and union territory-wise, so that financial risk protection can be improved for MCH related services.

METHODS

We used women's data from the National Family Health Survey, 2019-2021 (NFHS-5). Reproductive aged women (15-49 years) delivering one live child in last 5 years (n = 145,386) in any public or private institutions, were included. Descriptive statistics were presented as frequency and proportions. OOPE, was summarized as median and interquartile range (IQR). To estimate the extent for each covariate's effect, linear regression model was conducted.

RESULTS

Overall median OOPE for ID was Rs. 4066 (median OOPE: private hospitals: Rs.25600, public hospitals: Rs.2067). Health insurance was not sufficient to slash OOPE down at private facilities. Factors associated significantly to high OOPE were mothers' education, elderly pregnancy, complicated delivery, birth order of the latest child etc. CONCLUSION: A standard norm for ID should be implemented as a component of overseeing and controlling inequality. Aiding the needy is probably just one side of the solution, while the focus is required to be shifted towards reducing disparity among the health facilities, so that the beneficiaries do not need to spend on essential services or during emergencies.

Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data

INTRODUCTION

The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)-potentially, the world's largest NPHI programme-has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India.

METHODS

We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015-2016 (pre-PM-JAY) and 2019-2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts.

RESULTS

We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts.

CONCLUSION

The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor.

Socioeconomic and geographic variation in coverage of health insurance across India

Introduction

In India, regular monitoring of health insurance at district levels (the most essential administrative unit) is important for its effective uptake to contain the high out of pocket health expenditures. Given that the last individual data on health insurance coverage at district levels in India was in 2016, we update the evidence using the latest round of the National Family Health Survey conducted in 2019-2021.

Methods

We use the unit records of households from the latest round (2021) of the nationally representative National Family Health Survey to calculate the weighted percentage (and 95% CI) of households with at least one member covered by any form of health insurance and its types across socio-economic characteristics and geographies of India. Further, we used a random intercept logistic regression to measure the variation in coverage across communities, district and state. Such household level study of coverage is helpful as it represents awareness and outreach for at least one member, which can percolate easily to the entire household with further interventions.

Results

We found that only 2/5th of households in India had insurance coverage for at least one of its members, with vast geographic variation emphasizing need for aggressive expansion. About 15.5% were covered by national schemes, 47.1% by state health scheme, 13.2% by employer provided health insurance, 3.3% had purchased health insurance privately and 25.6% were covered by other health insurance schemes (not covered above). About 30.5% of the total variation in coverage was attributable to state, 2.7% to districts and 9.5% to clusters. Household size, gender, marital status and education of household head show weak gradient for coverage under "any" insurance.

Discussion

Despite substantial increase in population eligible for state sponsored health insurance and rise in private health insurance companies, nearly 60% of families do not have a single person covered under any health insurance scheme. Further, the existing coverage is fragmented, with significant rural/urban and geographic variation within districts. It is essential to consider these disparities and adopt rigorous place-based interventions for improving health insurance coverage.

Evolution of Government-funded health insurance for universal health coverage in India

India has run multiple Government-Funded Health Insurance schemes (GFHIS) over the past decades to ensure affordable healthcare. We assessed GFHIS evolution with a special focus on two national schemes - Rashtriya Swasthya Bima Yojana (RSBY) and Pradhan Mantri Jan Arogya Yojana (PMJAY). RSBY suffered from a static financial coverage cap, low enrollment, inequitable service supply, utilization, etc. PMJAY expanded coverage and mitigated some of RSBY's drawbacks. Investigating equity in PMJAY's supply and utilization across geography, sex, age, social groups, and healthcare sectors depicts several systemic skews. Kerala and Himachal Pradesh with low poverty and disease burden use more services. Males are more likely to seek care under PMJAY than females. Mid-age population (19-50 years) is a common group availing services. Scheduled Caste and Scheduled Tribe people have low service utilization. Most hospitals providing services are private. Such inequities can lead the most vulnerable populations further into deprivation due to healthcare inaccessibility.

Wealth Status and Health Insurance Enrollment in India: An Empirical Analysis

Since 2005, health insurance (HI) coverage in India has significantly increased, largely because of the introduction of government-funded pro-poor insurance programs. As a result, the determinants of HI enrollment and their relative importance may have changed. Using National Family Health Survey (NFHS)-4 data, collected in 2015-2016, and employing a Probit regression model, we re-examine the determinants of household HI enrollment. Then, using a multinomial logistic regression model, we estimate the relative risk ratio for enrollment in different HI schemes. In comparison to the results on the determinants of HI enrollment using the NFHS data collected in 2005-2006, we find a decrease in the wealth gap in public HI enrollment. Nonetheless, disparities in enrollment remain, with some changes in those patterns. Households with low assets have lower enrollments in private and community-based health insurance (CBHI) programs. Households with a higher number of dependents have a higher likelihood of HI enrollment, especially in rural areas. In rural areas, poor Scheduled Caste and Scheduled Tribe households are more likely to be enrolled in public HI than the general Caste households. In urban areas, Muslim households have a lower likelihood of enrollment in any HI. The educational attainment of household heads is positively associated with enrollment in private HI, but it is negatively associated with enrollment in public HI. Since 2005-2006, while HI coverage has improved, disparities across social groups remain.

Incidence, Inequality and Determinants of Catastrophic Health Expenditure in India

This study tries to estimate the incidence, intensity and inequality of Catastrophic Health Expenditure in India and its determinants using unit-level data from the four consecutive surveys of NSSO on ‘Healthcare Consumption and Morbidity’ spread across a 23-year period. For CHE incidence, a 10% threshold level of household consumption expenditure is considered. Additionally, socio-economic determinants of CHE were identified using multivariate logistic regression. Study reveals that the demand for healthcare services has increased gradually during the period 1995–2014 but this demand is primarily financed from out-of-pocket expenditures and hence leading to an increased risk of financial catastrophe, peaking at 23.45% in 2014. But a significant reduction in demand for healthcare is seen in the latest 75th round. Although the incidence of catastrophe has decreased, the inequality of catastrophic burden has increased. The results show that economic and social vulnerability have a significant impact on the likelihood of CHE incidence in households. The findings suggest that a targeted approach is required to alleviate the socially and economically vulnerable households from health expenditure catastrophe.

[Effect of Health Poverty Alleviation Project on the Economic Burden of Disease Among Poor Households: Empirical Evidence from Sichuan Province]

Objective

To evaluate the effect of Health Poverty Alleviation Project on the economic burden of disease among poor families and to provide references for further improvement of the Health Poverty Alleviation Project.

Methods

The difference-in-differences with propensity score matching method was used to analyze 48 counties in Sichuan Province. Propensity score matching was first carried out with data from the Sichuan Provincial Information System for Medical Care for Low-Income Population and the New Rural Cooperative Medical Insurance data to identify the non-poor population closest to the poor population. Then, difference-in-difference method was used to determine the effect of the Health Poverty Alleviation Project.

Results

Health Poverty Alleviation Project reduced the total annual out-of-pocket (OOP) payments by 13.1% on average, the outpatient OOP payments by an average 2.4%, inpatient OOP payments by an average 19.5%, and the probability of incurring catastrophic health care expenditures by an average of 3.9% for low-income households. In addition, the program had a more significant effect in poverty-stricken counties than it did in non-poverty-stricken counties. Despite the significant effectiveness of the project, 12.1% of the low-income families still incurred catastrophic health expenditures after the program was implemented.

Conclusion

Health Poverty Alleviation Project reduces the economic burden of disease for poor households, and it has a better effect on reducing the economic burden of poor households in poverty-stricken counties. However, a certain number of households still incurred catastrophic health expenditures. When consolidating and expanding the effects of Health Poverty Alleviation Project and monitoring medical expenses for poverty prevention, policymakers should focus on the households with catastrophic medical expenditures to prevent them from sinking back into poverty.

Does the presence of health insurance and health facilities improve access to healthcare for major morbidities among Indigenous communities and older widows in India? Evidence from India Human Development Surveys I and II

In this paper, we examine whether access to treatment for major morbidity conditions is determined by the social class of the person who needs treatment. Secondly, we assess whether health insurance coverage and the presence of a PHC have any significant impact on the utilisation of health services, either public or private, for treatment and, more importantly, whether the presence of health insurance and PHC modify the treatment use behaviour for the two excluded communities of interest namely Indigenous communities and older widows using data from two rounds (2005 and 2012) of the nationally representative India Human Development Survey (IHDS). We estimated a multilevel mixed effects model with treatment for major morbidity as the outcome variable and social groups, older widows, the presence of a PHC and the survey wave as the main explanatory variables. The results confirmed access to treatment for major morbidity was affected by social class with Indigenous communities and older widows less likely to access treatment. Health insurance coverage did not have an effect that was large enough to induce a positive change in the likelihood of accessing treatment. The presence of a functional PHC increased the likelihood of treatment for all social groups except Indigenous communities. This is not surprising as Indigenous communities generally live in locations where the terrain is more challenging and decentralised healthcare up to the PHC might not work as effectively as it does for others. The social class to which one belongs has a significant impact on the ability of a person to access healthcare. Efforts to address inequity needs to take this into account and design interventions that are decentralised and planned with the involvement of local communities to be effective. Merely addressing one or two barriers to access in an isolated fashion will not lead to equitable access.

Impact of India's publicly financed health insurance scheme on public sector district hospitals: a health financing perspective

Background

Districts hospitals in India play a pivotal role in delivering health care services in the public sector and are empanelled under India's national health insurance scheme i.e. Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PMJAY). In this paper, we evaluate the extent to which the PMJAY impacts the district hospitals from a financing perspective.

Methods

We used cost data from India's nationally representative costing study-'Costing of Health Services in India' (CHSI) to determine the incremental cost of treating PMJAY patients, after adjusting for resources that are paid through supply-side government financing route. Second, we used data on number and claim value paid to public district and sub-district hospitals during 2019, to determine the additional revenue generated through PMJAY. The annual net financial gain per district hospital was estimated as the difference between payments under PMJAY, and the incremental cost of delivering the services.

Findings

At current levels of utilisation, the district hospitals in India gain a net annual financial benefit of $ 26.1 (₹ 1839.3) million, which can potentially increase up to $ 41.8 (₹ 2942.9) million with an increase in the share of patient volume. For an average district hospital, we estimate net annual financial gain of $ 169,607 (₹ 11.9 million), increasing up to $ 271,372 (₹ 19.1 million) per hospital with increased utilisation.

Interpretation

Demand-side financing mechanisms can be used to strengthen the public sector. Increasing utilisation of district hospitals, by either gatekeeping or improving availability of services will enhance financial gains for district hospitals and strengthen public sector.

Funding

Department of Health Research, Ministry of Health & Family Welfare, Government of India.

Digital health for all: The turn to digitized healthcare in India

In India, the use of digital technologies has become the key to the everyday operation of the welfare state in terms of accessing essential and life-sustaining entitlements. In this context, our article explores the genesis of India's digital turn in healthcare and maps the characteristics of a 'digital health for all' policy, based on empirical analysis of India's first digital-based universal health coverage programme - Rashtriya Swasthya Bima Yojana (RSBY) - with fieldwork material from the states of Jharkhand and Chhattisgarh. Being a smart-card-centred programme, RSBY marks the genesis of a digital approach to healthcare in India. The experiences of this scheme hold crucial implications for the digital healthcare landscape in India, as in the past its promoters pitched for its use to provide quality healthcare at lower cost. The technological design of the programme illustrates the construction and politics of a digitalized public-private welfare policy intended to meet the health needs of the poorest. By examining data on digital access to healthcare in the RSBY programme, as propounded and sustained by public health policies and a public-private model of governance, our article raises questions about the construction of new digital health policies and their contribution to private health markets. In doing so, it explores the key question of how digital technologies are transforming access to healthcare in India.

China's Smoke-free Policies in Public Place and the Smoking Cessation Status of Smokers

INTRODUCTION

Smoking remains a major health risk factor and China is the world's largest consumer of tobacco. Smoke-free policies in public places are a powerful weapon in tobacco control. Therefore, the aim of this study was to assess the association between smoke-free policies in public places and smoking cessation among smokers in China from 2012 to 2020.

METHODS

In this study, we assessed the impact of smoke-free public places policies on smoking cessation situation among smokers aged 16 years and older. We do this by conducting a difference-in-differences analysis using data from the China Family Panel Study (CFPS) 2012-2020.

FINDINGS

By 2020, about 60.2% of the cities were covered by partial smoke-free policies and about 38.5% by comprehensive smoke-free policies. Based on the results of the study, we found that the medium-term effect model (Model 2, 2012:2016; Model 3, 2012:2018) of the impact of partial smoke-free policies on smoking cessation was not statistically significant using 2012 as the study baseline; the short-term effect model (Model 1; 2012:2014; P< .01) and the long-term effect model (Model 4; 2012:2020; P< .05) were statistically significant; the effect of a comprehensive smoke-free policy on smoking cessation (Model 5; 2012:2020; P<.05) was statistically significant.

CONCLUSION

China's existing comprehensive smoke-free policies have had a modest impact on smoking cessation among the smoking population, and a strong, comprehensive national smoke-free law is urgently needed to achieve greater public health outcomes.

IMPLICATIONS

Smoke-free policies are an important intervention to influence smoking behavior. This study demonstrates that comprehensive smoke-free policies in public places in China can effectively influence smoking behavior and show long-term trends in smoke-free behavior, while also reflecting the need to promote comprehensive smoke-free policies. This study provides a basis for the implementation of comprehensive smokefree policies into law and also provides a basis for policy makers.

A Critical Analysis of the World's Largest Publicly Funded Health Insurance Program: India's Ayushman Bharat

Background

Launched in September 2018, the ABPMJAY is the world's largest publicly funded health insurance (PFHI) program with population coverage of 500 million. A systematic review was conducted.

Methods

A comprehensive literature search was conducted in four databases: PubMed, Web of Science, Scopus, and Google Scholar. The literature search was conducted with the search terms: "Ayushman Bharat OR ABPMJAY OR modicare AND RSBY." The search was set to title and abstract. Gray literature and government websites were also searched for relevant documents. A total of 881 documents were identified (PubMed: 53, Web of Science: 46, Scopus: 97, Google Scholar: 681, government websites: two, and gray literature: two). Fifty-two duplicates were identified. After the elimination of the duplicates, 829 unique documents were identified. These 829 unique citations were then subjected to a review of title and abstract independently by 2 reviewers. Six-hundred and ninety-two articles were rejected after review of title and abstract. One-hundred and thirty-seven articles were screened for full text independently by two reviewers. Sixty-six articles were rejected after review of the full text. Disagreements were resolved by discussion. Seventy-one unique articles were included in the final review. To attain the objective of the study, which is to critically analyze and provide an overview of Ayushman Bharat, a narrative synthesis was performed.

Results

Seven themes were identified from the review: (1) health and wellness centers (HWCs); (2) out-of-pocket health expenditure (OOPHE); (3) fraud; (4) upcoding and provision of unnecessary medical care; (5) moving focus away from primary care; (6) coverage; and (7) lop-sided access, exclusion at the periphery, and brain drain. There is very little impact evidence of the ABPMJAY available.

Conclusions

The government could plan impact evaluation studies in every state that the ABPMJAY is functional in. Any high-quality feedback generated might enable the National Health Authority, the government body leading and coordinating the ABPMJAY, to take necessary steps operationally and advice the government on strategy. Another concern is that the ABPMJAY PFHI might negatively impact the ongoing process of continuous strengthening and development of the government health-care system at all levels-primary, secondary, and tertiary. Continual recalibration and course corrections on the basis of high-quality feedback might enable ABPMJAY reduce catastrophic OOPHE for 500 million Indians. This is more than 6% of humanity: the largest block of people served by a single PFHI in history.

Short and longer-term impacts of health insurance on catastrophic health expenditures in Kwara State, Nigeria

BACKGROUND

Out- of-pocket health expenditures (OOPs) constitute a significant proportion of total health expenditures in many low- and middle-income countries (LMICs), leading to an increased likelihood of exposure to financial catastrophe in the event of illness. Health insurance has the potential to reduce catastrophic health expenditures (CHE), but rigorous evidence of its sustained impact is limited, especially in LMICs. This study examined the short- and longer-term effects of a health insurance program in Kwara State, Nigeria on CHE.

METHODS

The analysis is based on a panel dataset consisting of 3 waves of household surveys in program and comparison areas. The balanced data consists of 1,039 households and 3,450 individuals. We employed a difference-in-differences (DiD) regression approach to estimate intention-to-treat effects, and then computed average treatment effects on the treated by combining DiD with propensity score weighting and an instrumental variables analysis. CHE was measured as OOPs exceeding 10% of household consumption and 40% of capacity-to-pay (CTP).

RESULTS

Using 10% of consumption as a CHE measure, we found that living in the program area was associated with a 4.3 percentage point (pp) decrease in CHE occurrence (p < 0.05), while the effect on insured households was 5.7 pp (p < 0.05). The longer-term impact four years after program introduction was not significant. Heterogeneity analyses show a reduction in CHE of 7.2 pp (p < 0.01) in the short-term for the poorest tercile. No significant effects were found for the middle and richest terciles, nor in the longer-term. Households with a chronically ill member experienced a reduction in CHE of 9.4 pp (p < 0.01) in the short-term, but not in the longer-term. Most estimates based on the 40% of CTP measure were not statistically significant.

CONCLUSION

These findings highlight the critical role of health insurance in reducing the likelihood of catastrophic health expenditures, especially for vulnerable populations such as the poor and the chronically ill, and by extension in achieving universal health coverage. They also show that the beneficial impacts of health insurance may attenuate over time, as households potentially adjust their health-seeking behavior to the new scheme.

Eliciting relative preferences for the attributes of health insurance schemes among rural consumers in India

There is a limited understanding of the preferences of rural consumers in India for health insurance schemes. In this article, we investigate the preferences of the rural population for the attributes of a health insurance scheme by implementing a discrete choice experiment (DCE). We identified six attributes through qualitative and quantitative study: enrollment, management, benefit package, coverage, transportation facility, and monthly premium. A D-efficient design of 18 choices has been constructed, each comprising two health insurance choices. We collected the representative sample from 675 household heads of the rural population through personal interviews. The preferences for the attributes and attribute levels were estimated using the multinomial logit (MNL) and random-parameter logit (RPL) models. The analysis shows that all attribute levels significantly affect the choice behavior (P < 0.05). The relative order of preferences for attributes are; enrollment, benefit package, monthly premium, management, coverage, and transportation.

Assessing the Prevalence of Financial Toxicity, its Predictors and Association with Health- Related Quality of Life Among Radiation Oncology Patients in India: A Cross-Sectional Patient Reported Outcome Study

PURPOSE

Financial toxicity has been associated with several clinical outcomes such as early mortality and poor quality of life. The aim of this study was to evaluate the magnitude of financial toxicity among radiation oncology patients and its association with health-related quality of life (HRQOL) in Indian health care settings.

METHODS AND MATERIALS

This cross-sectional study was conducted among patients with cancer who had completed radiation therapy, either standalone or as part of a multimodal treatment. Financial toxicity and HRQOL were assessed using the Comprehensive Score for Financial Toxicity (COST) and Functional Assessment of Cancer Therapy: General (FACT-G) measures, respectively. Associations between financial toxicity and HRQOL were assessed using Pearson correlation. Univariate and multivariate regression analyses were conducted to identify the factors associated with financial toxicity.

RESULTS

A total of 350 patients were included in this study. Of the 350 participants, 57.7% were male, 95.7% had no health insurance, and 61% were diagnosed with Head & Neck cancers. The average COST score was 15.38 ± 9.18 (range, 2-35), and the average FACT-G score was 69.63 ± 12.25 (range, 33-99). Based on the total COST score, 7.4% of participants reported grade 3 and 44.9% reported grade 2 financial toxicity. A significant positive correlation was observed between the COST and FACT-G scores, with a correlation coefficient of 0.58 (P < .001), indicating a large effect size. The COST score also significantly predicted the FACT-G score (β = 0.77; 95% confidence interval [CI], 0.66-0.88; P < .001). The results of multivariate linear regression identified annual household income (β = 3.9; 95% CI, 3.29-4.57; P < .001) and cancer type (β = 3.74; 95% CI, 2.33-5.14; P < .001) as significant predictors of the COST score.

CONCLUSIONS

More than 80% of the participants experienced financial toxicity in this study. The results highlight the need for interventions to alleviate the growing financial toxicity among cancer survivors in India.

The impact of increasing expenditure on National Essential Public Health Services on the medical costs of hypertension in China: A difference-in-difference analysis

BACKGROUND

The prevention and control of hypertension should be an effective way to reduce deaths and it has been a high priority in China. In 2013, the Chinese government increased the subsidy standard for the National Essential Public Health Services Package (NEPHSP) from RMB 15 to RMB 30 per person, which was expected to cover 70 million hypertensions. This study explored the influence of increasing NEPHSP subsidy on outpatient and inpatient expenditure among patients with hypertension.

METHODS

Data were mined from the 2011-2015 Harmonized China Health and Retirement Longitudinal Study. The study sample included 3192 hypertensive patients who were not lost to follow-up from 2011 to 2015. Hypertensive patients who covered by NEPHSP from 2011 to 2015 were defined as the treatment group, otherwise defined as the comparison group. The policy intervention was the increase of NEPHSP subsidy in 2013, and the years before and after 2013 were respectively considered as pre- (2011) and post-intervention (2015). The primary outcomes variables were the outpatient and inpatient expenditure of patients with hypertension, based on direct spending of outpatients and inpatients separately reported by patients with hypertension. Using propensity score matching (PSM) to match the individual characteristics of hypertension in the treatment group and the comparison group, difference-in-differences (DID) were used to analyze the outcomes.

RESULTS

The patients with hypertension' outpatient and inpatient expenditure patterns in the treatment and control group show an increasing trend from 2011 to 2015. After PSM, of the 1 956 hypertensive participants, 369 covered by the NEPHSP before and after 2013. A DID estimate of the increased NEPHSP subsidy was associated with a significant decrease of 1 251.35 RMB (t = 2.13, P = 0.034) in hypertension related inpatient expenditure, no significant change (t = 0.61, P = 0.544) among outpatient expenditure.

CONCLUSIONS

The NEPHSP may reduce inpatient expenditure among hypertension. Further strengthening of the NEPHSP may reduce their burden.

Which indicator should be used? A comparison between the incidence and intensity of catastrophic health expenditure: using difference-in-difference analysis

BACKGROUND

Catastrophic health expenditure (CHE) represents out-of-pocket payment as a share of household income. Most previous studies have focused on incidence aspects when assessing health policy effects. However, because CHE incidence is a binary variable, the effect of the health policy could not accurately be evaluated. On the contrary, the intensity of CHE is a continuous variable that can yield completely different results from previous studies. This study reassesses the coverage expansion plan for four serious diseases using the intensity of CHE in Korea.

METHODS

We used the Korea Health Panel Study from 2013 to 2015 to conduct the analysis. The study population is households with chronic diseases patients. We divided the population into two groups: the policy beneficiary group, i.e., households with a patient of any of the four serious diseases, and the non-beneficiary group. A difference-in-difference model was employed to compare the variation in the intensity and incidence of CHE between the two groups. We defined the incidence of CHE as when the ratio of out-of-pocket medical expenses to household income is more than a threshold of 10%, and the intensity of CHE is the height of the ratio subtracting the threshold 10%.

RESULTS

The increased rate of CHE intensity in households with four serious diseases was lower than that in households with other chronic diseases. The interaction term, which represents the effect of the policy, has a significant impact on the intensity but not on the incidence of CHE.

CONCLUSIONS

CHE indicators should be applied differently according to the purpose of policy evaluation. The incidence of CHE should be used as the final achievement indicator, and the intensity of CHE should be used as the process indicator. Furthermore, because CHE has an inherent characteristic that is measured by the ratio of household income to medical expenses, to lower this, a differential out-of-pocket maximum policy for each income class is more appropriate than a policy for strengthening the coverage for specific diseases.

Effect of adolescent female fertility and healthcare spending on maternal and neonatal mortality in low resource setting of South Asia

BACKGROUND

Maternal and neonatal mortality is high in South Asia. Recent studies have identified factors such as adolescent female fertility, healthcare spending is reducing maternal and neonatal mortality. The objective of this study is to examine the effect of adolescent female fertility and healthcare spending on maternal and neonatal mortality in South Asian countries.

METHODS

A retrospective panel study design was used, a total of 8 South Asian countries (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) data from World development indicator 1990-2020 considered for analysis. Descriptive statistical method was used for summary. The effect of adolescent female fertility and healthcare spending on maternal and neonatal mortality were analysed using fixed and random effect regression with multiple imputation.

FINDINGS

Adolescent female fertility, maternal, and neonatal mortality is very high in the aforementioned countries, and considerably varies among countries. A significant relationship between the maternal mortality and healthcare spending, neonatal mortality and adolescent female fertility was observed. We found neonatal and maternal mortality are more likely to decrease depends on healthcare spending. Healthcare spending has a significantly negative effect on neonatal mortality (- 0.182, 95% CI: [- 0.295 to -.069]; P-value < 0.01) and maternal mortality (- 0.169, 95% CI: [- 0.243 to - 0.028]; P-value < 0.05). A change in 1 % increases in healthcare spending should decrease by 0.182 neonatal mortality per 1000 live births and maternal mortality by 0.169 per 100,000 live births.

CONCLUSIONS

In south Asian countries, increasing healthcare spending and decreasing adolescent female fertility may contribute to reduce maternal and neonatal mortality. In addition, number of service providers such as physicians supplied contributed to the decline of neonatal mortality. These findings have important implications for future improvement of healthcare spending in maternal and neonatal health programs.

Does Elderly Chronic Disease Hinder the Sustainability of Borderline Poor Families’ Wellbeing: An Investigation From Catastrophic Health Expenditure in China

Objectives: Health and health expenditure caused by elderly chronic diseases are a global problem. As China has just lifted itself out of poverty in 2020, the sustainable development of Borderline Poor Families’ Wellbeing faces severe challenges. Therefore, it is of great practical significance to explore the impact of elderly chronic diseases on the catastrophic health expenditure of Borderline Poor Families.

Methods: Based on screening 8086 effective samples from China Health and Retirement Longitudinal Study (CHARLS) database and calculating catastrophic health expenditure, this paper uses two-part model and logit regression to discuss the impact of elderly chronic diseases on the sustainable development of Borderline Poor Families’ Wellbeing.

Results: The results showed that stroke, cancer, and liver disease caused the most catastrophic health expenditures and had the greatest impact on the Borderline Poor Families’ Wellbeing.

Conclusion: Therefore, in order to ensure the sustainable development of Borderline Poor Families’ Wellbeing, the government should strengthen the publicity of pre-prevention and post-healthcare of chronic diseases such as stroke, and combine pre-prevention policy with post-guarantee policy.

Explaining Caste-Based Disparities in Enrollment for National Health Insurance Program in India: a Decomposition Analysis

BACKGROUND

Caste plays a significant role in individual healthcare access and health outcomes in India. Discrimination against low-caste communities contributes to their poverty and poor health outcomes. The Rashtriya Swasthya Bima Yojana (RSBY), a national health insurance program, was created to improve healthcare access for the poor. This study accounts for caste-based disparities in RSBY enrollment in India by decomposing the contributions of relevant factors.

METHODS

Using the data from the 2015-2016 round of the National Family Health Survey, we compare RSBY enrollment rates of low-caste and high-caste households. We use a non-linear extension of Oaxaca-Blinder decomposition and estimate two models by pooling coefficients across the comparison groups and all caste groups. Enrollment differentials are decomposed into individual- and household-level characteristics, media access, and state-level fixed effects, allowing 2000 replications and random ordering of variables.

RESULTS

The analysis of 480,766 households show that scheduled tribe households have the highest enrollment (18.85%), followed by 14.13% for scheduled caste, 10.67% for other backward caste, and 9.33% for high caste. Household factors, family head's characteristics, media access, and state-level fixed effects account for a 32% to 52% gap in enrollment. More specifically, the enrollment gaps are attributable to differences in wealth status, educational attainment, residence, family size, dependency ratio, media access, and occupational activities of the households.

CONCLUSIONS

Weaker socio-economic status of low-caste households explains their high RSBY enrollments.

The trust and insurance models of healthcare purchasing in the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana in India: early findings from case studies of two states

BACKGROUND

The Pradhan Mantri Jan Arogya Yojana (PMJAY), a publicly funded health insurance scheme for the poor in India, was launched in 2018. Early experiences of states with various purchasing arrangements can provide valuable insights for its future performance. We sought to understand the institutional agencies and performance of the trust and insurance models of purchasing with respect to; a) Provider contracting b) Claim management c) Implementation costs.

METHODS

A mixed methods case study design was adopted. Two states, Uttar Pradesh (representing a trust model) and Jharkhand (representing the insurance model) were purposively selected. Data sources included document reviews, key informant interviews, quantitative scheme data from the provider empanelment and claims database, and primary data on costs. Descriptive statistics were reported for quantitative data, content analysis was used for thematic reporting of qualitative data.

RESULTS

In both models, the state was the final authority on empanelment decisions, with no significant influence of the insurance company. Private hospitals constituted the majority of empanelled providers, with wide variations in district-wise distribution of bed capacities in both states. The urgency of completing empanelment in the early days of the scheme created the need for both states to re-review hospitals and de-empanel those not meeting requirements. Very few quality- accredited private hospitals were empaneled. The trust displayed more oversight of support agencies for claim management, longer processing times, a higher claim rejection rate and numbers of queries raised, as compared to the insurance model. Support agencies in both states faced challenges in assessing the clinical decisions of hospitals. Cost-effectiveness showed mixed results; the trust cost less than the insurance model per beneficiary enrolled, but more per claim generated.

CONCLUSIONS

Efforts are required to enable a better distribution and ensure quality of care in empanelled hospitals. The adoption of standard treatment guidelines is needed to support hospitals and implementing agencies in better claim management. The oversight of agencies through enforcement of contracts remains vital in both models. Assessing the comparative performance of trusts and insurance companies in more states at later stages of scheme implementation, would be further useful to determine their cost-effectiveness as purchasers.

How Jaminan Kesehatan Nasional (JKN) coverage influences out-of-pocket (OOP) payments by vulnerable populations in Indonesia

While Indonesia introduced a national health insurance scheme (JKN) in 2014 and coverage has grown to over 80% of the population, Indonesians still spend significant sums out-of-pocket (OOP) for their healthcare-over 30% of current health expenditure (CHE). This study aims to better understand how JKN is influencing OOP payments, especially among the poor and rural, at the range of health facilities. This study uses data from the National Socio-Economic Survey (SUSENAS) in 2018 and 2019, as these surveys started including a question on how much OOP spending a household incurs on health. The results show that households with JKN membership are far less likely than the uninsured to pay OOP for healthcare, and that if they do incur a cost, the magnitude of this cost is much lower among JKN households than uninsured ones. The results also show that JKN households in the two poorest quintiles have a higher probability to not incur any OOP (37% and 35%, respectively) compared to those in the wealthier quintiles 4 (32%) and 5 (30%). Poorer JKN households living in the eastern part of Indonesia-the less urbanized and developed regions-experienced the most cost-savings, though largely due to supply-side constraints. In fact, JKN members save more at public primary health care facilities vs. private ones (who often do not contract with JKN) and also save significantly more (over 50%) than uninsured households at both public and private hospitals. The study demonstrates the positive influence JKN has on OOP payments, especially among the poor and rural, but also highlights how the scheme needs to better engage with the growing private sector and invest in infrastructure in rural areas to help secure financial protection for its entire population.

What Policy Approaches Were Effective in Reducing Catastrophic Health Expenditure? A Systematic Review of Studies from Multiple Countries

BACKGROUND

The United Nations set a goal for universal health coverage in all countries by 2030 and selected the catastrophic health expenditure (CHE) indicator as an assessment tool for this goal. Many countries have strived to reduce household CHE. However, no study has compared countries whose policies have had a remarkable effect on decreasing CHE. Therefore, the purpose of this systematic literature review is to find appropriate methods for measuring CHE that can help us to analyze the impact of health policies and identify countries whose health policies are most effective in reducing CHE.

METHOD

PubMed and Web of Science were searched. Studies that measured the incidence or intensity of CHE in multiple years were included. Two independent reviewers screened the literature, extracted the data, and analyzed the studies selected. Thirty-eight studies met the inclusion criteria for the review. We classified the selected research papers to random sampling and quasi-experimental studies.

RESULTS

We graphically presented the results of CHE incidence and intensity rates reported in the collected papers as a time series data set. Since most studies did not use sample weights, it was not easy to confirm whether the time series changes of CHE are significant. Therefore, we could find only two countries that had policy effects. Both countries established policies that focus on the poor.

CONCLUSION

There are so many studies that analyze CHE, but policies that are effective in reducing CHE are unknown. This study uses a systematic literature review methodology to determine effective policies by comparing CHE time series trends among countries. As a policy implication, it was found that because CHE is defined as the ratio of the ability to pay to medical expenses, a policy of differential medical expenses that is based on income level is effective.

How much do government and households spend on an episode of hospitalisation in India? A comparison for public and private hospitals in Chhattisgarh state

BACKGROUND

Improvements in the financing of healthcare services are important for developing countries like India to make progress towards universal health coverage. Inpatient-care contributes to a big share of total health expenditure in India. India has a mixed health-system with a sizeable presence of private hospitals. Existing studies show that out-of-pocket expenditure (OOPE) incurred per hospitalisation in private hospitals was greater than public facilities. But, such comparisons have not taken into account the healthcare spending by government.

METHODS

For a valid comparison between public and for-profit private providers, this study in Indian state of Chhattisgarh assessed the combined spending by government and households per episode of hospitalisation. The supply-side and demand-side spending from public and private sources was taken into account. The study used two datasets: a) household survey for data on hospital utilisation, OOPE, cash incentives received by patients and claims raised under publicly funded health insurance (PFHI) schemes (n = 903 hospitalisation episodes) b) survey of public facilities to find supply-side government spending per hospitalisation (n = 64 facilities).

RESULTS

Taking into account all relevant demand and supply side expenditures, the average total spending per day of hospitalisation was INR 2833 for public hospitals and INR 6788 for private hospitals. Adjusted model for logarithmic transformation of OOPE while controlling for variables including case-mix showed that a hospitalisation in private hospitals was significantly more expensive than public hospitals (coefficient = 2.9, p < 0.001). Hospitalisations in private hospitals were more likely to result in a PFHI claim (adjusted-odds-ratio = 1.45, p = 0.02) and involve a greater amount than public hospitals (coefficient = 0.27, p < 0.001). Propensity-score matching models confirmed the above results. Overall, supply-side public spending contributed to 16% of total spending, demand-side spending through PFHI to 16%, cash incentives to 1% and OOPE to 67%. OOPE constituted 31% of total spending per episode in public and 86% in private hospitals.

CONCLUSIONS

Government and households put together spent substantially more per hospitalisation in private hospitals than public hospitals in Chhattisgarh. This has important implications for the allocative efficiency and the desired public-private provider-mix. Using public resources for purchasing inpatient care services from private providers may not be a suitable strategy for such contexts.

Catastrophic Health Expenditure on Private Sector Pharmaceuticals: A Cross-Sectional Analysis from the State of Odisha, India

India has high rates of catastrophic health expenditure (CHE): 16% of Indian households incur CHE. To understand why CHE is so high, we conducted an in-depth analysis in the state of Odisha—a state with high rates of public sector facility use, reported eligibility for public insurance of 80%, and the provision of drugs for free in government-run facilities—yet with the second-highest rates of CHE across India (24%). We collected household data in 2019 representative of the state of Odisha and captured extensive information about healthcare seeking, including the facility type, its sector (private or public), how much was spent out-of-pocket, and where drugs were obtained. We employ Shapley decomposition to attribute variation in CHE and other financial hardship metrics to characteristics of healthcare, controlling for health and social determinants. We find that 36.3% (95% uncertainty interval: 32.7–40.1) of explained variation in CHE is attributed to whether a private sector pharmacy was used and the number of drugs obtained. Of all outpatient visits, 13% are with a private sector chemist, a similar rate as public primary providers (15%). Insurance was used in just 6% of hospitalizations and its use explained just 0.2% (0.1–0.4) of CHE overall. Eighty-six percent of users of outpatient care obtained drugs from the private sector. We estimate that eliminating spending on private drugs would reduce CHE by 56% in Odisha. The private sector for pharmaceuticals fulfills an essential health system function in Odisha—supplying drugs to the vast majority of patients. To improve financial risk protection in Odisha, the role currently fulfilled by private sector pharmacies must be considered alongside existing shortcomings in the public sector provision of drugs and the lack of outpatient care and drug coverage in public insurance programs.

Potential Impact of the Insurance on Catastrophic Health Expenditures Among the Urban Poor Population in India

Background:

Urban poor face a disproportionate burden of ill health and high out-of-pocket expenditure (OOPE), creating a severe unmet need for affordable and quality health care. This article highlights the impact of health insurance on OOPE and catastrophic healthcare expenditure among the urban poor of India.

Methods:

The study uses randomly collected household data from a baseline survey conducted in the states of Rajasthan and Uttar Pradesh. Separate Insurance impact models have been generated for the analysis.

Results:

Mean out-of-pocket health expenses is higher in the private health facility for the inpatient care but in case of outpatient care, the expenditure was more in public. Expenditure on medicine constitutes the largest part of the total OOPE. Insurance impact model shows that coverage on medicine alone can reduce medical impoverishment by 85% in the case of Outpatient Deparment (OPD) and 71% in the case of Inpatient Department (IPD). The urban poor preferred private facility for treatment in case of illness, albeit when it comes to delivery, they prefer public facility

Conclusions:

Study findings indicate overt reliance on private health care must be regulated, to reduce OOPE among the urban poor. Also, effective universal health insurance can go a long way in reducing the OOPE with availability of free medicines and diagnostics in the public health facilities.