Role of insurance in determining utilization of healthcare and financial risk protection in India

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 impact of health insurance on hypertension care: a household fixed effects study in India

INTRODUCTION

Hypertension is highly prevalent in India, but the proportion of patients achieving blood pressure control remains low. Efforts have been made to expand health insurance coverage nationwide with the aim of improving overall healthcare access. It is critical to understand the role of health insurance coverage in improving hypertension care.

METHODS

We used secondary data from the nationally representative sample of adults aged 15-49 years from the 2015-2016 National Family Health Survey (NFHS) in India. We defined the hypertension care cascade as four successive steps of (1) screened, (2) diagnosed, (3) treated, and (4) controlled, and operationalized these variables using blood pressure measurements and self-reports. We employed household fixed effect models that conceptually matched people with and without insurance within the household, to estimate the impact of insurance coverage on the likelihood of reaching each care cascade step, while controlling for a wide range of additional individual-level variables.

RESULTS

In all 130,151 included individuals with hypertension, 20.4% reported having health insurance. For the insured hypertensive population, 79.8% (95% Confidence Interval: 79.3%-80.3%) were screened, 49.6% (49.0%-50.2%) diagnosed, 14.3% (13.9%-14.7%) treated, and 7.9% (7.6%-8.2%) controlled, marginally higher than the percentages for the uninsured 79.8% (79.5%-80.0%), 48.2% (47.9%-48.6%), 13.3% (13.1%-13.5%), and 7.5% (7.4%-7.7%) for each cascade step, respectively. From the household fixed effects model, health insurance did not show significant impact on the hypertension care cascade, with the estimated relative risks of health insurance 0.97 (0.93-1.02), 0.97 (0.91-1.03), 0.95 (0.77-1.30), and 0.97 (0.65-1.10) for each cascade step, respectively. We further performed stratified analyses by sociodemographic and behavioral risk factors and a sensitivity analysis with district fixed effects, all of which yielded results that confirmed the robustness of our main findings.

CONCLUSIONS

Health insurance did not show significant impact on improving hypertension care cascade among young and middle-aged adults with hypertension in India. Innovative strategies for overcoming practical barriers to healthcare services in addition to improving financial access are needed to address the large unmet need for hypertension care.

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.

Measuring the Effect of Ayushman Bharat-Pradhan Mantri Jan Aarogya Yojna (AB-PMJAY) on Health Expenditure among Poor Admitted in a Tertiary Care Hospital in the Northern State of India

Background

Ayushman Bharat-Pradhan Mantri Jan Aarogya Yojna (AB-PMJAY) as a financial risk protection scheme intends to reduce catastrophic health expenditure (CHE), especially among poor. The current study was carried out to assess the utility of AB-PMJAY in terms of reduction in CHE from before and after admission in a tertiary hospital in the northern state of India.

Methodology

It was a hospital-based cross-sectional study carried out from August 2020 to October 2021 at a public tertiary hospital of Himachal Pradesh, India. Data were collected from surgery- and medicine-allied (SA and MA) specialties. Along with socio-demographic details, information for total monthly family expenditure (TMFE), out-of-pocket expenditure (OOPE), and indirect illness-related expenditure (IIE) was recorded before and after hospital admission. CHE was considered as more than 10.0% OOPE of THFE and more than 40.0% of capacity to pay (CTP).

Results

A total of 336 participants with a mean age of 46 years were recruited (MA: 54.6%). The majority (~93.0%) of participants had illness of fewer than 6 months. The mean TMFE was observed to be INR 4213.1 (standard deviation: 2483.7) and found to be similar across specialties. The OOPE share of TMFE declined from 76.1% (before admission) to 30.0% (after admission). Before admission, CHE was found among 65.5% (10.0% of THFE) and 54.2% (40.0% of CTP) participants. It reduced to about 29.0% (based on both THE and CTP) after admission to hospital.

Conclusion

AB-PMJAY scheme found to be useful in reducing CHE in a tertiary hospital.

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.

Index construction and application of digital transformation in the insurance industry: Evidence from China

In the context of digitization, the insurance industry's value chain is undergoing significant shifts. However, the existing research on its comprehension and measurement remains relatively limited. This study constructs an index system for digital transformation in the insurance industry (DTII) on three components: digital infrastructure, digital platform, and digital applications. Utilizing data from 31 provinces in China, this study employs the entropy weight method, analytic hierarchy process method and minimum relative entropy method to measure the weights of indicators, empirically applying this index system. The results show that DTII in China experiences rapid advancement with an average annual growth rate of 20.46% from 2014 to 2020 and there exists strong regional convergence. In addition, the spatial agglomeration and spatial effects of DTII are mainly concentrated in the life insurance industry and the eastern region. This study provides an index system and empirical evidence for evaluating the DTII, providing policy insights for exploring the sustainable development path of the insurance industry in the digital era.

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.

Gender-specific inequalities in coverage of Publicly Funded Health Insurance Schemes in Southern States of India: evidence from National Family Health Surveys

BACKGROUND

Publicly Funded Health Insurance Schemes (PFHIS) are intended to play a role in achieving Universal Health Coverage (UHC). In countries like India, PFHISs have low penetrance and provide limited coverage of services and of family members within households, which can mean that women lose out. Gender inequities in relation to financial risk protection are understudied. Given the emphasis being placed on achieving UHC for all in India, this paper examined intersecting gender inequalities and changes in PFHIS coverage in southern India, where its penetrance is greater and of longer duration.

DATA AND METHODS

This study used the fourth (NFHS-4, 2015-16) and fifth (NFHS-5, 2019-21) rounds of India's National Family Health Survey for five southern states: namely, Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, and Telangana. The World Health Organization's Health Equity Assessment Toolkit (HEAT) Plus and Stata were used to analyse PFHIS coverage disaggregated by seven dimensions of inequality. Ratios and differences for binary dimensions; Between Group Variance and Theil Index for unordered dimensions; Absolute and Relative Concentration Index (RCI) for ordered dimensions were computed separately for women and men.

RESULTS

Overall, PFHIS coverage increased significantly (p < 0.001) among women and men in Andhra Pradesh, and Kerala from NFHS-4 to NFHS-5. Overall, men had higher PFHIS coverage than women, especially in Andhra Pradesh, Tamil Nadu, and Telangana in both surveys. In both absolute and relative terms, PFHIS coverage was concentrated among older women and men across all states; age-related inequalities were higher among women than men in both surveys in Andhra Pradesh, Kerala, and Telengana. The magnitude of education-related inequalities was twice as high as among women in Telangana (RCINFHS-4: -12.23; RCINFHS-5: -9.98) and Andhra Pradesh (RCINFHS-4: -8.05; RCINFHS-5: -7.84) as compared to men in Telangana (RCINFHS-4: -5.58; RCINFHS-5: -2.30) and Andhra Pradesh (RCINFHS-4: -4.40; RCINFHS-5: -3.12) and these inequalities remained in NFHS-5, suggesting that lower education level women had greater coverage. In the latter survey, a high magnitude of wealth-related inequality was observed in women (RCINFHS-4: -15.78; RCINFHS-5: -14.36) and men (RCINFHS-4: -20.42; RCINFHS-5: -13.84) belonging to Kerala, whereas this inequality has decreased from NFHS-4 to NFHS-5., again suggestive of greater coverage among poorer populations. Caste-related inequalities were higher in women than men in both surveys, the magnitude of inequalities decreased between 2015-16 and 2019-20.

CONCLUSIONS

We found gender inequalities in self-reported enrolment in southern states with long-standing PFHIS. Inequalities favoured the poor, uneducated and elderly, which is to some extend desirable when rolling out a PFHIS intended for harder to reach populations. However, religion and caste-based inequalities, while reducing, were still prevalent among women. If PFHIS are to truly offer financial risk protection, they must address the intersecting marginalization faced by women and men, while meeting eventual goals of risk pooling, indicated by high coverage and low inequality across population sub-groups.

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.

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.

Does health insurance solve health care utilization puzzle in Tanzania?

OBJECTIVES

The global target of achieving universal health coverage by 2030 is a nightmare in most developing countries. To seek in-depth reasons, this study examines the effects of health insurance on healthcare utilization in Tanzania.

STUDY DESIGN

This study used a non-experimental research design.

METHODS

Probit model, negative binomial regression, and instrumental variable Poisson with generalized method of moments were used to solve the healthcare utilization puzzle by the use of Andersen Health Care Utilization Model by using the Tanzania Panel Survey data of 2020/21.

RESULTS

The findings showed that education level, income, age, residence, household size, insurance, and distance from homestead to health facilities are significant policy intervention factors for improving households' healthcare utilization behavior among households in Tanzania.

CONCLUSION

Prioritize should be made on interventions that ensure the affordability of health services without compromising the quality of services offered and expanding the share of the government budget on health sector.

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.

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.

The Role of Government-run Insurance in Primary Health Care Utilization: A Cross-Sectional Study in Papua Region, Indonesia, in 2018

Health development in the Papua region often lags behind other areas of Indonesia. The study aims to analyze the role of government-run insurance in primary health care utilization in the Papua region, Indonesia. The study examined 17,879 Papuan. The study used primary health care utilization as an outcome variable and health insurance ownership as an exposure variable. The study also employed nine control variables: province, residence, age, gender, marital status, education, employment, wealth, and travel time to primary health care. The research employed data using binary logistic regression in the final analysis. The results show that Papuans with government-run insurance were three times more likely to utilize primary health care than uninsured Papuans (AOR 3.081; 95% CI 3.026-3.137). Meanwhile, Papuan with private-run insurance were 0.133 times less likely to utilize primary health care than uninsured Papuans (AOR 0.133; 95% CI 0.109-0.164). Moreover, Papuans who have two types of health insurances (government-run and private-run) were 1.5 times more likely to utilize the primary health care than uninsured Papuan (AOR 1.513; 95% CI 1.393-1.644). The study concluded that government-run insurance increases the chance of primary health care utilization in the Papua region, Indonesia. Government-run insurance has the most prominent role compared to other health insurance categories.

Impact evaluation of subsidized health insurance programs on utilization of healthcare facilities: evidence from Indonesia

Despite subsidized health insurance has long been proclaimed by many countries including Indonesia, the variety of evaluation results showing that the optimization of benefits obtained by recipients is still questionable. The objective of this study is to analyze the impact of subsidized health insurance programs (ASKESKIN and JAMKESMAS) on the utilization of healthcare facilities in Indonesia. Data from two waves longitudinal data, the Indonesian Family Life Survey (IFLS), were analyzed using the propensity score matching method. This study found that in general, ASKESKIN and JAMKESMAS had very small impacts on the utility of healthcare facilities measured by outpatient and inpatient visits by program's beneficiaries. It implies that being subsidized health insurance holders does not necessarily encourage them to visit formal healthcare facilities. In addition, the comparison of average treatment effect on the treated (ATT) between ASKESKIN and JAMKESMAS also did not show any significant improvement even though the program had tried to be improved. The results of this study provide the basis for advising policy makers that there needs to revisit the effectiveness of subsidized health insurance program implementation.

An analysis of government-sponsored health insurance enrolment and claims data from Meghalaya: Insights into the provision of health care in North East India

Introduction

The Megha Health Insurance Scheme (MHIS) was launched in 2013 in the North-East Indian state of Meghalaya to reduce household out-of-pocket expenditure on health and provide access to high-quality essential healthcare. Despite substantial expansion of the MHIS since the scheme’s inception, there is a lack of comprehensive documentation and evaluation of the scheme’s performance against its Universal Health Care (UHC) objectives.

Methods

We analysed six years of enrolment and claims data (2013–2018) covering three phases of the scheme to understand the pattern of enrolment, utilisation and care provision under the MHIS during this period. De-identified data files included information on age, sex, district of residence, the district of provider hospital, type of hospital, date of admission, status at discharge, claimed category of care, package codes, and amount claimed. Descriptive statistics were generated to investigate key trends in enrolment, service utilisation, and Government health spending under the MHIS.

Results

Approximately 55% of the eligible population are currently enrolled in MHIS. Enrolment increased consistently from phase I through III and remained broadly stable across districts, gender, age group and occupation categories, with a small decline in males 19–60 years. Claims were disproportionately skewed towards private provision; 57% of all claims accrued to the 18 empanelled private hospitals and 39% to the 159 public sector facilities. The package ‘General Ward Unspecified’ was responsible for the highest volume of claims and highest financial dispensation across all three phases of the scheme. This likely indicates substantial administrative error and is potentially masking both true burden of disease and accurate financial provision for care under the MHIS. Anti-rabies injections for dog/cat bite contributed to 11% of total claims under MHIS III, and 1.6% of all claims under MHIS II. This warrants investigation to better understand the burden of animal bites on the Meghalayan population and inform the implementation of cost-effective strategies to reduce this burden.

Conclusions

This paper describes the first analysis of health insurance enrolment and claims data in the state of Meghalaya. The analysis has generated an important evidence base to inform future MHIS enrolment and care provision policies as the scheme expands to provide Universal Health Coverage to the state’s entire population.

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.

Hospital utilization in Indonesia in 2018: do urban-rural disparities exist?

Background

The government must ensure equality in health services access, minimizing existing disparities between urban and rural areas. The referral system in Indonesia is conceptually sound. However, there are still problems of uneven service access, and there is an accumulation of patients in certain hospitals. The study aims to analyze the urban–rural disparities in hospital utilization in Indonesia.

Methods

The study used secondary data from the 2018 Indonesian Basic Health Survey. This cross-sectional study gathered 629,370 respondents through stratification and multistage random sampling. In addition to the kind of home and hospital utilization, the study looked at age, gender, marital status, education, occupation, wealth, and health insurance as control factors. The research employed multinomial logistic regression to evaluate the data in the final step.

Results

According to the findings, someone who lives in an urban region has 1.493 times higher odds of using outpatient hospital services than someone in a rural area (AOR 1.493; 95% CI 1.489–1.498). Meanwhile, someone who lives in an urban region has 1.075 times higher odds of using an inpatient facility hospital than someone who lives in a rural one (AOR 1.075; 95% CI 1.073–1.077). Furthermore, someone living in an urban region has 1.208 times higher odds than someone who lives in a rural area using outpatient and inpatient hospital services simultaneously (AOR 1.208; 95% CI 1.204–1.212).

Conclusion

The study concluded there were urban–rural disparities in hospital utilization in Indonesia.

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.

How does Context Influence Implementation Mechanism of Publicly Funded Health Insurance Schemes in Indian States

Introduction:

The success of any insurance scheme is contingent upon well-defined processes related to payment, referral, grievances and quality control mechanisms. Any deviation observed may result in unsatisfactory performance. This study attempts to examine various processes related to the implementation of Pradhan Mantri Jan Arogya Yojana (PMJAY) and a state-specific insurance scheme across three states of India.

Objective:

To describe the policies and process adapted by selected states in implementing a government-sponsored health insurance scheme. To examine the strategies that work effectively, how they operate and what contextual factors enable or disable the desired implementation mechanisms.

Methodology:

The three states of Karnataka, Chhattisgarh, and Odisha were selected to understand various processes related to the implementation of Publicly Funded Health Insurance Schemes (PFHIS) schemes in diverse settings. A realist evaluation framework was used to study the contexts and mechanisms and how this influences outcomes.

Results:

The three schemes differ in implementation modes and follow different strategies owing to the local contexts. Some mechanisms worked well in specific contexts, whereas similar things have hindered the process in other contexts.

Conclusion:

The evidence generated is helpful to strengthen implementation processes under PMJAY and allows learning from each other to increase uptake of the scheme.

Healthcare Cost Reduction and Health Insurance Policy Improvement

OBJECTIVES

Reducing healthcare costs is a constant endeavor of all healthcare organizations, governments, policy makers, and individuals. A comparative study of available healthcare policies from the patient's perspective is not available. Furthermore, an analysis of how the various components of these policies affect the healthcare cost of a patient is required.

METHODS

Data were collected from 150 hospitalized patients in India regarding their views on 7 healthcare cost categories covering 22 cost components. These are statistically analyzed under 4 commonly used health insurance policies (2 government insurance schemes: ex-servicemen contributory health scheme and employee state insurance; private insurance schemes; and self-financing-ie, no insurance) to assess which healthcare cost component is more important under which policy option.

RESULTS

Under 7 healthcare cost categories, 22 cost components were studied, and out of these 22, 16 were found statistically significant. Results revealed that the treatment of all 16 significant cost components under the 4 health insurance policy options was statistically different.

CONCLUSIONS

Patients covered under government sector health insurance policies were found to be less concerned about healthcare costs, whereas those covered under private health insurance policies were found to be more cost-conscious. Access to healthcare or transportation costs to the healthcare facility is a key concern area for self-financed patients.

Cost of Illness Due to Severe Enteric Fever in India

BACKGROUND

Lack of robust data on economic burden due to enteric fever in India has made decision making on typhoid vaccination a challenge. Surveillance for Enteric Fever network was established to address gaps in typhoid disease and economic burden.

METHODS

Patients hospitalized with blood culture-confirmed enteric fever and nontraumatic ileal perforation were identified at 14 hospitals. These sites represent urban referral hospitals (tier 3) and smaller hospitals in urban slums, remote rural, and tribal settings (tier 2). Cost of illness and productivity loss data from onset to 28 days after discharge from hospital were collected using a structured questionnaire. The direct and indirect costs of an illness episode were analyzed by type of setting.

RESULTS

In total, 274 patients from tier 2 surveillance, 891 patients from tier 3 surveillance, and 110 ileal perforation patients provided the cost of illness data. The mean direct cost of severe enteric fever was US$119.1 (95% confidence interval [CI], US$85.8-152.4) in tier 2 and US$405.7 (95% CI, 366.9-444.4) in tier 3; 16.9% of patients in tier 3 experienced catastrophic expenditure.

CONCLUSIONS

The cost of treating enteric fever is considerable and likely to increase with emerging antimicrobial resistance. Equitable preventive strategies are urgently needed.

National Methodological Guidelines to Conduct Budget Impact Analysis for Health Technology Assessment in India

OBJECTIVE

Our paper aims to present Budget Impact Analysis (BIA) guidelines for health technology assessment (HTA) in India.

METHODOLOGY

A Systematic Literature Review (SLR) was conducted to retrieve information on existing BIA guidelines internationally. The initial set of principles for India were put together based on an interactive process between authors, taking into consideration the existing evidence on BIA and features of Indian healthcare system. These were reviewed by Technical Appraisal Committee (TAC) of Health Technology Assessment in India (HTAIn) for their inputs. Three rounds of consultations were held before finalising the guidelines. Finally, user feedback on the draft guidelines was obtained from the policy makers and programme managers involved in the budgeting decisions.

RESULTS

We recommend a payer's perspective, which will include both a multi-payer (depicting the current situation in India) and a single-payer scenario (which reflects a futuristic universal health care situation). A time horizon of 1-4 years is recommended. For estimation of eligible population, a top-down approach is considered appropriate. The future and current mix of interventions should be analysed for different utilisation and coverage patterns. We do not recommend discounting; however, inflation adjustments should be performed. The presentation of results should include total and disaggregated results, segregated year-wise throughout the chosen time horizon, as well as segregated by the type of resources. Deterministic sensitivity analysis and scenario analysis are recommended to address uncertainty.

CONCLUSION

Our recommendations, which are tailored for the Indian healthcare and financing context, aim to promote consistency and transparency in the conduct as well as reporting of the BIA. BIA should be used along with evidence from economic evaluation for decision making, and not as a substitute to evidence on value for money.

Comparing the average cost of outpatient care of public and for-profit private providers in India

Introduction

Understanding the cost of care associated with different kinds of healthcare providers is necessary for informing the policy debates in mixed health-systems like India’s. Existing studies reporting Out of Pocket Expenditure (OOPE) per episode of outpatient care in public and private providers in India do not provide a fair comparison because they have not taken into account the government subsidies received by public facilities. Public and private health insurance in India do not cover outpatient care and for-profit providers have to meet all their costs out of the payments they take from patients.

Methods

The average direct cost per acute episode of outpatient care was compared for public providers, for-profit formal providers and informal private providers in Chhattisgarh state of India. For public facilities, government subsidies for various inputs were taken into account. Resources used were apportioned using Activity Based Costing. Land provided free to public facilities was counted at market prices. The study used two datasets: a) household survey on outpatient utilisation and OOPE b) facility survey of public providers to find the input costs borne by government per outpatient-episode.

Results

The average cost per episode of outpatient care was Indian Rupees (INR) 400 for public providers, INR 586 for informal private providers and INR 2643 for formal for-profit providers and they managed 39.3, 37.9 and 22.9% of episodes respectively. The average cost for government and households put together was greater for using formal for-profit providers than the public providers. The disease profile of care handled by different types of providers was similar. Volume of patients and human-resources were key cost drivers in public facilities. Close to community providers involved less cost than others.

Conclusions and recommendations

The findings have implications for the desired mix of public and private providers in India’s health-system. Poor regulation of for-profit providers was an important structural cost driver. Purchasing outpatient care from private providers may not reduce average cost. Policies to strengthen public provisioning of curative primary care close to communities can help in reducing cost.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06777-7.

Estimating the effectiveness of national health insurance in covering catastrophic health expenditure: Evidence from South Korea

The catastrophic health expenditure (CHE) indicator has been used to measure the medical cost burden of households. Many countries have institutionalized their health insurance systems to reduce out-of-pocket payments, the main contributor to the financial burden. However, there is no method to estimate how the insurance coverage reduces the CHE. This study proposes an approach to evaluate the effectiveness of insurance in reducing the CHE impacts in terms of incidence and gap, which are based on a modified calculation method of CHE. Additionally, we apply these methods to data from the Korea Health Panel Survey (2011-2016). The results are as follows. First, under the setting of a threshold of 10%, the CHE incidence rate was 19.26% when the Korean national health insurance benefits reduced the CHE's incidence for 15.17% of the population in 2017. Second, the results of the concentration index of CHE showed that the intensity approach of CHE is better than the incidence approach. Third, the new approach we applied revealed that health insurance reduces the burden of CHE to some degree, although it was not an efficient way to reduce CHE. In conclusion, this study provides new policy approaches to save the finances of national health insurance and reduce the intensity of CHE at the same time by raising the low-cost burden of medical services and lowering that of high cost. Moreover, we suggest that policymakers should focus on income level of the households rather than specific diseases.

Cost-Effectiveness of Temozolamide for Treatment of Glioblastoma Multiforme in India

PURPOSE

Glioblastoma multiforme (GBM) has poor outcomes following surgery and radiation. Adjuvant temozolamide along with radiation therapy has been shown to improve survival. In this paper, we evaluate the cost-effectiveness of concomitant temozolamide with radiation and maintenance temozolamide for 6 months of treatment for GBM in India.

MATERIALS AND METHODS

We used a Markov model to evaluate the lifetime costs and consequences of treating GBM with radiation alone versus radiation with adjuvant temozolamide. The model was calibrated using the published evidence from European Organisation for Research and Treatment of Cancer-NCIC trial on progression-free survival and overall survival to estimate the life years (LYs) and quality-adjusted LYs (QALYs). Cost of treatment and management of complications were estimated using the data from the National Health System Cost Database and Indian studies. Future cost and consequences were discounted at 3%. Incremental cost per QALY gained with temozolamide was estimated to assess cost effectiveness.

RESULTS

Temozolamide resulted in an increase of 0.59 (0.53-0.66) LY and 0.33 (0.29-0.40) QALY per person at an incremental cost of ₹75,120 in Indian national rupee (INR) (59,337-93,960). Overall, the use of temozolamide incurs an incremental cost of ₹212,020 INR (138,127-401,466) per QALY gained, which has a 4.7% probability to be cost-effective at 1-time per capita Gross Domestic Product (GDP) threshold. In case the current price of temozolamide could be decreased by 90%, the probability of its use for GBM being cost-effective increases to 80%.

CONCLUSION

Temozolamide is not cost-effective for treatment of patients with GBM in India. This evidence should be used while framing guidelines for treatment and price regulation.

H, Nambiar D. Empanelment of health care facilities under Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB PM-JAY) in India

Introduction

India’s Pradhan Mantri Jan Arogya Yojana (PM-JAY) is the world’s largest health assurance scheme providing health cover of 500,000 INR (about USD 6,800) per family per year. It provides financial support for secondary and tertiary care hospitalization expenses to about 500 million of India’s poorest households through various insurance models with care delivered by public and private empanelled providers. This study undertook to describe the provider empanelment of PM-JAY, a key element of its functioning and determinant of its impact.

Methods

We carried out secondary analysis of cross-sectional administrative program data publicly available in PM-JAY portal for 30 Indian states and 06 UTs. We analysed the state wise distribution, type and sector of empanelled hospitals and services offered through PM-JAY scheme across all the states and UTs.

Results

We found that out of the total facilities empanelled (N = 20,257) under the scheme in 2020, more than half (N = 11,367, 56%) were in the public sector, while 8,157 (40%) facilities were private for profit, and 733 (4%) were private not for profit entities. State wise distribution of hospitals showed that five states (Karnataka (N = 2,996, 14.9%), Gujarat (N = 2,672, 13.3%), Uttar Pradesh (N = 2,627, 13%), Tamil Nadu (N = 2315, 11.5%) and Rajasthan (N = 2,093 facilities, 10.4%) contributed to more than 60% of empanelled PMJAY facilities: We also observed that 40% of facilities were offering between two and five specialties while 14% of empanelled hospitals provided 21–24 specialties.

Conclusion

A majority of the hospital empanelled under the scheme are in states with previous experience of implementing publicly funded health insurance schemes, with the exception of Uttar Pradesh. Reasons underlying these patterns of empanelment as well as the impact of empanelment on service access, utilisation, population health and financial risk protection warrant further study. While the inclusion and regulation of the private sector is a goal that may be served by empanelment, the role of public sector remains critical, particularly in underserved areas of India.

Prevalence of chronic morbidities and healthcare seeking behavior among urban community dwelling elderly population residing in Kalyani Municipality area of West Bengal, India

Introduction:

Demographic transition has resulted in higher proportion of elderly population in every community. The pattern of chronic morbidity along with healthcare seeking behavior and factors associated with it are important for implementation of national health policies targeted toward elderly population.

Methods:

A community based cross-sectional study was done including 457 urban dwelling elderly population of Kalyani Municipality area of West Bengal. Sociodemographic details, profile of chronic morbidities, and healthcare seeking behavior for chronic morbidities were studied using a pretested semi structured questionnaire.

Results:

The average education and financial independence were high among study participants. The prevalence of chronic morbidities was 82.3% and hypertension was the most common morbidity in both male and female. Around half of the individuals with chronic morbidities (57.7%) sought healthcare advice at least once in last 6 months. Most of the study participants preferred private healthcare setup and allopathic system of medicine. Females have been found to have higher treatment seeking behavior than males in logistic regression.

Conclusion:

We found hypertension and diabetes were more prevalent in the study population. Higher financial independence and education among study participants might have influenced the healthcare seeking behavior, which was mainly from private setup. Implementation of national health policies for elderly has to be accelerated in acceptable ways to promote health among elderly.

Mapping of Health Technology Assessment (HTA) teaching and training initiatives: Landscape for evidence-based policy decisions in India

Demographic transitions accompanied with epidemiological shifts are affecting many countries around the globe. These apprehensions have raised the concern for constructing and sustaining healthcare systems especially among resource-constrained low- and middle-income-countries (LMICs) such as India. Introducing Health-Technology-Assessment (HTA) in the educational initiatives could support planners and policy-makers in formulating evidence-based-decision-making along with tackling inequalities/inefficiencies and promoting cost-effectiveness in resource allocation. A mapping exercise has been undertaken for examining the feasibility and implementation of HTA curriculum in the existing courses in India. To gain best possible insight on HTA curriculum, a situational analysis was conducted using systematic search strategy through search engines such as Google, Google Scholar, ProQuest and PubMed. Currently, seventy-one institutes in India are offering one or more courses through regular mode at undergraduate/postgraduate/diploma-certificate/doctorate-level pertaining to Medical-technology (MT), Biostatistics (BS), and Health-economics (HE). MT was offered in 37 institutes (52.12%), followed by BS in 23 (32.39%), and HE in nine (12.67%). Only two institutes (2.81%) are offering certificate-courses on HTA, mainly confined in virtual modules. This review reveals noticeable gaps in the existing curriculum in India and necessitates a novel academic initiative by introducing HTA in a full-fledged manner. Reforms in the research and educational initiatives need to be brought for promoting awareness regarding HTA. The application of domain needs to be widened from the field of health-policy formulators to research and teaching. This should be further strengthened with the strong academic collaborations to generate replicable findings, address challenges, and offer solutions for existing threats to HTA.

Impact of Health Insurance on Health Care Utilisation and Out-of-Pocket Health Expenditure in Vietnam

Background

In recent years, health insurance (HI) has been chosen by many low- and middle-income countries to obtain an important health policy target—universal health coverage. Vietnam has recently introduced the Revised Health Insurance Law, and the effects of the voluntary health insurance (VHI) and heavily subsidised health insurance (HSHI) programmes have not yet been analysed. Therefore, this study is aimed at examining the impact of these HI programmes on the utilisation of health care services and out-of-pocket health expenditure (OOP) in general and across different health care providers in particular.

Methods

Using the two waves of Vietnam Household Living Standard Surveys 2014 and 2016 and the difference-in-difference method, the impacts of VHI and HSHI on health care utilisation and OOP in Vietnam were estimated.

Results

For both the VHI and HSHI groups, we found that HI increased the probability of seeking outpatient care, the mean number of outpatient visits, the total number of visits, and the mean number of visits at the district level of health care providers in the last 12 months. However, there was no evidence that the HSHI programmes increased the mean number of inpatient visits and the number of visits at the provincial hospital. We also found that while the VHI programme reduced OOP for both outpatient and inpatient care, the HSHI scheme did not result in a reduction in OOP for hospitalisation, although HI lowered the total OOP. Similarly, we found that for both groups, HI reduced OOP when the insured visited district and provincial hospitals. However, the statistically significant impact was not demonstrated when the enrolees of HSHI programmes visited provincial hospitals.

Conclusion

The study offers evidence that the Vietnamese HI scheme increased health care service utilisation and decreased OOP for the participants of the VHI and HSHI programmes. Therefore, the government should continue to consider improving the HI system as a strategy to achieve universal health coverage.

Performance of India's national publicly funded health insurance scheme, Pradhan Mantri Jan Arogaya Yojana (PMJAY), in improving access and financial protection for hospital care: findings from household surveys in Chhattisgarh state

BACKGROUND

A national Publicly Funded Health Insurance (PFHI) scheme called Pradhan Mantri Jan Arogaya Yojana (PMJAY) was launched by government of India in 2018. PMJAY seeks to cover 500 million persons with an annual cover of around 7000 USD per household. PMJAY claims to be the largest government funded health scheme globally and has attracted an international debate as a policy for Universal Health Coverage. India's decade-long experience of the earlier national and state-specific PFHI schemes had shown poor effectiveness in financial protection. Most states in India have completed a year of implementation of PMJAY but no evaluations are available of this important scheme.

METHODS

The study was designed to find out the effect of enrolment under PMJAY in improving utilisation of hospital services and financial protection in Chhattisgarh which has been a leading state in implementing PFHI in terms of enrolment and claims. The study analyses three repeated cross-sections. Two of the cross-sections are from National Sample Survey (NSS) health rounds - year 2004 when there was no PFHI and 2014 when the older PFHI scheme was in operation. Primary data was collected in 2019-end to cover the first year of PMJAY implementation and it formed the third cross-section. Multivariate analysis was carried out. In addition, Propensity Score Matching and Instrumental Variable method were applied to address the selection problem in insurance.

RESULTS

Enrollment under PMJAY or other PFHI schemes did not increase utilisation of hospital-care in Chhattisgarh. Out of Pocket Expenditure (OOPE) and incidence of Catastrophic Health Expenditure did not decrease with enrollment under PMJAY or other PFHI schemes. The size of OOPE was significantly greater for utilisation in private sector, irrespective of enrollment under PMJAY.

CONCLUSION

PMJAY provided substantially larger vertical cover than earlier PFHI schemes in India but it has not been able to improve access or financial protection so far in the state. Though PMJAY is a relatively new scheme, the persistent failure of PFHI schemes over a decade raises doubts about suitability of publicly funded purchasing from private providers in the Indian context. Further research is recommended on such policies in LMIC contexts.

Rashtriya Swasthya Bima Yojana (RSBY) and outpatient coverage

The healthcare industry worldwide is undergoing a radical transformation. An enthusiastic healthcare system of the Government of India (GOI) continually tries to tackle numerous challenges facing the system. The Rashtriya Swasthya Bima Yojana (RSBY) program has provided secondary level healthcare facilities to more than 36 million families across most states in India. This particular health insurance initiative was taken by the GOI with the purpose to safeguard the pitiable or marginalized Indian population or those households who are facing economic risks due to hospitalization and their everyday expenditures. RSBY provides affordable and accessible healthcare services along with insurance coverage for secondary care. However, it is limited to inpatient treatment or hospitalization. For outpatient coverage many strategies have been applied but low enrolment is still an existing flaw under this streamer. The present paper discusses various features of RSBY, outpatient projects undertook, and various obstacles that can be removed to integrate this insurance scheme with primary healthcare in India.

Utilisation and financial protection for hospital care under publicly funded health insurance in three states in Southern India

BACKGROUND

Many LMICs have implemented Publicly Funded Health Insurance (PFHI) programmes to improve access and financial protection. The national PFHI scheme implemented in India for a decade has been recently modified and expanded to cover free hospital care for 500 million persons. Since increase in annual cover amount is one of the main design modifications in the new programme, the relevant policy question is whether such design change can improve financial protection for hospital care. An evaluation of state-specific PFHI programmes with vertical cover larger than RSBY can help answer this question. Three states in Southern India - Andhra Pradesh, Karnataka and Tamil Nadu have been pioneers in implementing PFHI with a large insurance cover.

METHODS

The current study was meant to evaluate the PFHI in above three states in improving utilisation of hospital services and financial protection against expenses of hospitalization. Two cross-sections from National Sample Survey's health rounds, the 60th round done in 2004 and the 71st round done in 2014 were analysed. Instrumental Variable method was applied to address endogeneity or the selection problem in insurance.

RESULTS

Enrollment under PFHI was not associated with increase in utilisation of hospital care in the three states. Private hospitals dominated the empanelment of facilities under PFHI as well as utilisation. Out of Pocket Expenditure and incidence of Catastrophic Health Expenditure did not decrease with enrollment under PFHI in the three states. The size of Out of Pocket Expenditure was significantly greater for utilisation in private sector, irrespective of insurance enrollment.

CONCLUSION

PFHI in the three states used substantially larger vertical cover than national scheme in 2014. The three states are known for their good governance. Yet, the PFHI programmes in all three states failed in fulfilling their fundamental purpose. Increasing vertical cover of PFHI and using either 'Trusts' or Insurance-companies as purchasers may not give desired results in absence of adequate regulation. The study raises doubts regarding effectiveness of contracting under PFHIs to influence provider-behavior in the Indian context. Further research is required to find solutions for addressing gaps that contribute to poor financial outcomes for patients under PFHI.

Utilization of health services in Tenali Mandal, Andhra Pradesh- A cross-sectional study

Introduction

India has a plurality of health care with different systems of medicine delivered by government and local bodies in hospitals and clinics. Public hospitals provide 60% of all hospitalizations, while the private sector provides 75% of all routine care. Utilization is the actual attendance by the members of the public at health care facilities, which measures the number of visits per year or the number of people with at least one visit during the previous year, serves as an important tool and acts as a guiding path in understanding disease profile and also helps resource allocation.

Materials and Methods

A cross-sectional study was done using the National Pathfinder survey (stratified cluster random sampling) to know the health care utilization, profile, and pattern in Tenali Mandal, Guntur, Andhra Pradesh.

Results

The study sample comprised of 1,500 subjects who were equally divided among 5 age groups. Out of 1,500 participants, 52.8% were females and 47.2% were males. In total, 71.7% of the study participants have utilized health services, with majority of them (44.5%) had availed services within the last 6 months with prime reason of fevers (15.8%), while the main barrier for not seeking care was distance (17.03%), almost an equal proportion of the population sought care for their problems through home remedies and over-the-counter.

Conclusion

There is an utmost need to minimize barriers of utilizing by making them aware of the health problems, so that they develop a positive attitude toward health care utilization. Therefore, knowledge of utilization of health services and associated factors is important in planning and delivery of interventions by the primary care physicians to improve health services coverage.

When state-funded health insurance schemes fail to provide financial protection: An in-depth exploration of the experiences of patients from urban slums of Chhattisgarh, India

This paper explores the dynamics of access under the state-funded universal health insurance scheme in Chhattisgarh, India, and specifically the relationship between choice, affordability and acceptability. A qualitative case study of patients from the slums of Raipur City incurring significant heath expenditure despite using insurance, was conducted, examining the way patients and their families sought to navigate and negotiate hospitalisation under the scheme. Eight purposefully selected ('revelatory') instances of patients (and their families) utilising private hospitals are presented. Patients and their family exercised their agency to the extent that they could. Negotiations on payments took place at every stage, from admission to post-hospitalisation. Once admitted, however, families rapidly lost the initiative, and faced mounting costs, and increasingly harsh interactions with providers. The paper analyses how these outcomes were produced by a combination of failures of key regulatory mechanisms (notably the 'smart card'), dominant norms of care as a market transaction (rather than a right), and wider cultural acceptance of illegal informal healthcare payments. The unfavourable normative and cultural context of (especially) private sector provisioning in India needs to be recognised by policy makers seeking to ensure financial risk protection through publicly financed health insurance.