Research on impact of publicly financed health insurance has paid relatively little attention to the nature of healthcare provision the schemes engage. India’s National Health Insurance Scheme or RSBY was made universal by Chhattisgarh State in 2012. In the State, public and private sectors provide hospital services in a context of extensive gender, social, economic and geographical inequities. This study examined enrolment, utilization (public and private) and out of pocket (OOP) expenditure for the insured and uninsured, in Chhattisgarh. The Chhattisgarh State Central sample (n = 6026 members) of the 2014 National Sample Survey (71st Round) on Health was extracted and analyzed. Variables of enrolment, hospitalization, out of pocket (OOP) expenditure and catastrophic expenditure were descriptively analyzed. Multivariate analyses of factors associated with enrolment, hospitalization (by sector) and OOP expenditure were conducted, taking into account gender, socio-economic status, residence, type of facility and ailment. Insurance coverage was 38.8%. Rates of hospitalization were 33/1000 population among the insured and 29/1000 among the uninsured. Of those insured and hospitalized, 67.2% utilized the public sector. Women, rural residents, Scheduled Tribes and poorer groups were more likely to utilize the public sector for hospitalizations. Although the insured were less likely to incur out of pocket (OOP) expenditure, 95.1% of insured private sector users and 66.0% of insured public sector users, still incurred costs. Median OOP payments in the private sector were eight times those in the public sector. Of households with at least one member hospitalized, 35.5% experienced catastrophic health expenditures (>10% monthly household consumption expenditure).
The study finds that despite insurance coverage, the majority still incurred OOP expenditure. The public sector was nevertheless less expensive, and catered to the more vulnerable groups. It suggests the need to further examine the roles of public and private sectors in financial risk protection through government health insurance.
Citation: Nandi S, Schneider H, Dixit P (2017) Hospital utilization and out of pocket expenditure in public and private sectors under the universal government health insurance scheme in Chhattisgarh State, India: Lessons for universal health coverage. PLoS ONE 12(11): e0187904. https://doi.org/10.1371/journal.pone.0187904
Editor: Shankar Prinja, Post Graduate Institute of Medical Education and Research School of Public Health, INDIA
Received: April 4, 2017; Accepted: October 28, 2017; Published: November 17, 2017
Copyright: © 2017 Nandi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and the supplementary files. The complete Chhattisgarh unit level information from the 71st round of the National Sample Survey, conducted by the office of National Sample Survey Organization (NSSO) is available from the Deputy Director General, Computer Centre, Ministry of Statistics and Programme Implementation, Government of India, East Block No. 10 R.K. Puram, New Delhi-110066. The access policy for this data is available here: http://mail.mospi.gov.in/index.php/catalog/161/study-description#page=accesspolicy&tab=study-desc.
Funding: This paper is part of the PhD of the first author for which a part fellowship had been provided by the Institute of Tropical Medicine, Belgium. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Universal health coverage and government health insurance schemes
The concept of Universal Health Coverage (UHC) arose out of a global concern for high levels of out of pocket expenditure for health care in many low- and middle-income countries (LMIC) . UHC has the goal of “ensuring that everyone within a country can access the health services they need, which should be of sufficient quality to be effective, and providing all with financial protection from the costs of using health services” [2: 3]. The three critical dimensions of UHC are: coverage of the population, coverage by services and financial protection . Core to the design of UHC is the health financing system and how it engages with the mechanisms for provision of healthcare. Progress towards UHC requires strengthened health system functioning [1, 3–6] and a focus on equity [7–11].
Despite this broad vision, at country level, UHC has often focused on the establishment of state funded insurance schemes [12, 13] and stopped short of addressing the health systems strengthening or equity aspects of UHC. Kutzin [12: 607] raises this as a concern and calls for a shift in emphasis from a scheme to the health system in its entirety and for the “impact of that scheme on the attainment of the objectives for the population and system as a whole” to be monitored. The impact of state funded insurance schemes on financial protection and health equity are currently a subject of keen debate the world over, including in India [5, 13–16].
In their review of studies on the impact of national health insurance for the poor and the informal sector in LMICs, Acharya et al  found generally low enrolment rates in many of the schemes. There was lower enrolment among the poor, unless special efforts were made, and mixed findings with respect to rural versus urban enrolment. To date, gender has not been identified as a determinant of low enrolment [17–20]. Once enrolled, the evidence on subsequent utilization and financial risk protection is mixed , sometimes within the same country. While most studies found that insurance increased these parameters [21, 22], sometimes more for the poor , in others the impacts were unevenly distributed, with the poor benefitting less than the rich [17, 24–26].
The role of the health system capacity in determining the impact of the insurance schemes has been extensively documented [4, 20, 25–29]. However, few studies have explicitly disaggregated or compared the roles of the private and public sectors in achieving the objectives of UHC [1, 17].
Beyond the UHC debates, systematic reviews have concluded that the private health sector may not be more efficient than the public sector  nor result in greater access equity , although others maintain that the evidence is not conclusive .
Government Health Insurance In India
India has a mixed health system, consisting of a network of government health facilities and health programmes as well as a dominant and unregulated private health sector [32, 33]. It is characterized by extensive inequities in health service utilization and access related to socio economic status, caste, geography, and gender, amongst others [33–39]. Private expenditure (including out of pocket payments) constitutes 70% of total health expenditure and 75% of primary and ambulatory healthcare episodes and 61% of inpatient episodes or hospital visits are in the private sector. Two percent (2%) of public sector expenditure relies on out of pocket fees and charges .
Studies of healthcare utilization patterns have found the poor in India are more likely to utilize the public sector for healthcare, making it pro-equity, than the private sector which relies predominantly on fee-for-service payment [39, 40]. However, Jain et al  argue that utilization of the public sector by the poor is not by choice but due to financial constraints that could be overcome by health insurance.
In India many players, including government, view state funded health insurance as the key mechanism to achieve UHC [41–44]. Over the last decades, states across India introduced government funded insurance schemes with the aim to protect the poor from catastrophic health expenditure [32, 45]. The National Health Insurance Scheme or RSBY, launched by the Ministry of Labour in 2007, and taken over by the Health Ministry in 2015, was the first national scheme for the unorganized sector, providing hospital cover for mainly Below Poverty Line (BPL) households. The key initial considerations for introducing RSBY were to promote India’s economic growth, the private healthcare market (drawing extensively on private healthcare providers) and worker productivity, especially in the informal sector [46, 47].
Health insurance schemes in India emerged in parallel to an existing major strand of health sector reform, namely the National Rural Health Mission (NRHM), launched in 2005, re-named the National Health Mission (NHM) in 2013, incorporating the Urban Health Mission. While the NHM aims to strengthen public health systems to provide “universal access to equitable, affordable and quality health care” [33, 48], the RSBY aims to actively draw in private sector providers through a “business model” involving both private and public sectors .
The stated objectives of RSBY are to provide financial protection and improve access to quality health care for the poor and other vulnerable groups, through “empowering the beneficiary” with “freedom of choice between public and private hospitals”, and providing “cashless” services .
The emerging evidence on the impact of the national and state government health insurance schemes in India shows that its beneficial effects have been, at best, limited. Some studies report an increase in enrolment and utilization of health care [50, 51, 52] and appropriate coverage of vulnerable groups . However, in many others, socio-economic status, place of residence, caste, tribal group and women-headed households have emerged as significant determinants of inequity in enrolment and utilization [13, 37, 50, 54–58]. Moreover, instances of unnecessary hospitalizations and procedures and “provider-induced demand” have been documented, especially in the private sector [54, 59–65], also found in previous studies conducted by the authors in Chhattisgarh [66, 67].
Some studies have shown a decrease in out of pocket payments in those covered with insurance [52, 68, 69] but most find that enrolled patients continue to pay out of pocket, more so in the private sector, with instances of increased payment also reported [52, 58, 60, 65, 70–75].
Government health insurance in chhattisgarh
Chhattisgarh State has a population of more than 25 million people , 79% of whom have been identified as poor, and requiring food security support . With 44% of its geographical area under forests , the population is predominantly rural (77%) . In a complex landscape of social groupings, “Scheduled Tribes” (indigenous groups) constitute 31% of the total population and “Scheduled Castes” a further 13% , both of whom are considered as marginalized and socially excluded groups relative to the others (“Other Backward Classes” and “Others”) .
Although Chhattisgarh has recorded improvements in health status since it was formed in 2000, it is still one of the low performing states in India .
Chhattisgarh was one of the first states to launch RSBY in 2009, expanding the scheme to all families living in the state in 2012 through the Mukhyamantri Swasthya Bima Yojana (MSBY) or Chief Minister’s Health Insurance Scheme. This move is seen as positive , as targeting in social programmes often leads to exclusion of the poor and disadvantaged [13, 81]. Both schemes (RSBY and MSBY) have identical provisions. They cover a family of five for pre and post hospitalization expenses up to an annual limit of Rs.30, 000 (US$ 442), with a one-time registration fee of Rs.30 to be paid by the family. Private and government hospitals are “empanelled” to provide services through pre-determined packages, reimbursed at fixed rates. As per the government data of April 2016, around 12.5 million people in Chhattisgarh are enrolled under RSBY/MSBY , mostly mobilized through processes involving rural grassroots workers, like the Mitanins (Community Health Workers) . Of the 735 hospitals empanelled, 462 (62.9%) are private facilities . Programme data for the 2015–16 financial year shows that the public sector made a smaller proportion of total number of claims (25.3%) than the private sector (74.7%), while the private sector received 82.9% of the claim amounts disbursed .
Rationale for the study
Evidence on the extent of financial protection through government funded insurance schemes is mixed both globally and in India. Further, little attention has been given to evaluating the healthcare provision mechanisms government insurance schemes engage, and on the differential effects of public and private sector use on financial protection and reducing inequity. Moreover, recent debates related to measuring financial protection for UHC in the Sustainable Development Goals (SDGs) emphasize the need for looking at household expenditure on health and its ‘impoverishing effect’, instead of simply measuring coverage with an insurance scheme .
In Chhattisgarh, both public and private sectors are involved in providing services under the insurance scheme, in a context of extensive geographical, socio economic and gender inequities. The state funded Universal Health Insurance Scheme in Chhattisgarh provides the opportunity to study these elements and explore the pathways of utilization and extent of financial protection.
Materials and methods
The conceptual framework for the study is illustrated in Fig 1. It represents the relationships between enrolment (yes/no), utilization (public and private sector hospitalization) and financial risk protection (out of pocket and catastrophic household expenditures).
Study design, sampling and data collection
Drawing on household survey data, this descriptive study aimed to examine the relationships between enrolment, utilization of public and private sector sectors and financial risk protection for the insured and uninsured under the state funded health insurance in Chhattisgarh.
The Chhattisgarh State data used in this study were extracted from the 25th schedule of the 71st round of the cross-sectional Indian National Sample Survey, conducted between January and June 2014. The National Sample Survey Office (NSSO), under the Ministry of Statistics of the Government of India, conducts the survey on a periodic basis. The data is available from the Deputy Director General, Computer Centre, Ministry of Statistics and Programme Implementation, Government of India, New Delhi. The Chhattisgarh sample included 1205 households and 6026 individuals (household members), obtained in a stratified two-stage sampling design, with census villages and urban frame survey blocks as the first-stage units (FSUs) for the rural and urban areas respectively, and households as the second-stage units (SSUs).
The survey collected data in face-to-face interviews, using an interview schedule, on morbidity (self-reported), utilization of health care services (including types), and household expenditure on health care. Information was collected on every event of hospitalization of a household member, whether living or deceased at the time of survey, during the 365 days preceding the date of enquiry .
Information on household consumption expenditure was collected to create a consumption aggregate in the 30 days prior to the survey. Questions were asked to assess the “sum total of monetary values of all goods and services usually consumed (out of purchase or procured otherwise) by the household on domestic account during a month” [86: 8].
The NSSO survey does not ask about the specific type of government funded insurance scheme in its question on enrolment. The government health insurance schemes in the State, other than RSBY/MSBY are the Employees’ State Insurance Scheme (ESIS) and Central Government Health Scheme (CGHS). However, coverage data of these schemes reveal that during the period of the study the families covered under RSBY/MSBY made up the highest proportion of the enrolled under any government insurance. Under the RSBY 4th round of enrolment for 2013–2015, the number of enrolled families was 38,28,024 . Under the Employees’ State Insurance (ESI) in 2014, 2,50,720 families were covered . In 2014 (year of the NSSO survey), RSBY/MSBY thus constituted 93.9% of the enrolled. The Central Government Health Scheme (CGHS) gives coverage to central government employees residing in ‘CGHS-covered cities’, however, no areas or cities in Chhattisgarh are designated as CGHS-covered cities . Moreover, CGHS eligibility  also includes retired central government personnel, of whom the numbers residing in Chhattisgarh would be very small. Hence the data on insured in government insurance schemes in the NSSO survey primarily reflects the coverage under RSBY/MSBY.
The NSSO used a multistage sampling design that is not self-weighting. The NSSO provides the appropriate weights for analyses to ensure representativeness of aggregated data. These were applied in all the analyses, unless otherwise specified. The details of the sampling weights, methods and organization of the NSSO are reported elsewhere .
Descriptive analyses of the elements in Fig 1 (enrolment, hospitalization, use of public and private sectors, out of pocket and catastrophic expenditures) were conducted. The usual monthly per capita consumer expenditure (UMPCE) was calculated as the household’s usual consumption expenditure in a month divided by the size of the household and then divided into five economic quintiles, from Q1 (poorest) to Q5 (richest). Out of pocket expenditure on hospitalization was calculated per episode as medical expenditure minus reimbursements. Weighted medians of OOP expenditure were calculated. The methodology proposed by Wagstaff and van Doorslaer  was applied for assessing catastrophic payments for health care, namely, expenditure that exceeded 10% of annual total household consumption expenditure.
Further, multivariate logistic analyses were undertaken to examine the following relationships:
- Between enrolment and variables of gender (women-men), social group (Scheduled Caste, Scheduled Tribe, Other Backward Classes and General), place of residence (urban-rural) and UMPCE (referred to collectively as socio-economic factors).
- Between hospitalization and the above socio-economic factors, adding enrolment status.
- Between public sector hospitalization and the above socio-economic factors, adding enrolment and type of ailment.
- Between OOP expenditure and socio-economic factors, enrolment, type of ailment and level of facility.
Adjusted Odds Ratios (AOR) and 95% confidence intervals (CI) were estimated for each of the models.
In the logistic regressions, outcome variable was coded as ‘1’ for an individual enrolled in government insurance scheme and ‘0’ for an individual not enrolled in any insurance scheme; ‘1’ for an individual who was hospitalized and ‘0’ if not; ‘1’ if an individual was hospitalized in the public sector during last 365 days from the date of survey and ‘0’ if hospitalized in the private sector; ‘1’ if incurred any OOP expenditure and ‘0’ if did not incur any OOP expenditure. The binary response (‘y’), enrolled in government insurance scheme or not/hospitalized or not/hospitalized in public sector or private sector/incurred OOP expenditure or not) for each individual was related to a set of categorical predictors, ‘X’, and a fixed effect by a logit link function as follows:
The probability of an individual who had enrolled in government insurance scheme/hospitalized/hospitalized in public sector/incurred OOP expenses is πi. The parameter β0 estimates the log odds of enrolled in government insurance scheme/hospitalized/ hospitalized in public sector/incurred OOP expenses for the reference group, and the parameter β estimates with maximum likelihood, the differential log odds of enrolled in government insurance scheme/hospitalized/ hospitalized in public sector/incurred OOP expenses are associated with the predictor X, as compared to the reference group and ε represents the error term in the model.
As the data is from an official government survey, the researchers did not have any control over the validity or reliability of data. However, it is regarded as one of the most important sources of public health data in India, having high validity .
Characteristics of the study sample
The gender, residential (urban/rural) and social group distribution (number and weighted percentage), of the 6026 household members, is shown in Table 1. The study used the complete sample in its analysis.
Coverage with insurance
Of the total surveyed, 38.8% were covered by any government insurance scheme, which includes both the universal insurance scheme and central and state schemes for government employees (Table 2). A further 0.5% was covered with private insurance, while 60.7% of the sample had no insurance coverage of any kind.
Henceforth, ‘insurance’ refers only to government health insurance, and no further data on private insurance is presented.
Table 2 gives the socio-economic characteristics of the insured and uninsured. When gender, residence, social group and consumption expenditure (UMPCE) were combined in a logistic regression model, with enrolment as an outcome variable (Table 2), social group and UMPCE emerged as predictors of coverage. Scheduled Tribes were significantly more likely to be enrolled than other social groups while the richest (Q5) were significantly less likely to be enrolled (AOR 0.654; 95% CI: 0.516–0.761) among the UMPCE groups.
Hospitalization and choice of facility
Of the sample, 817 persons were hospitalized during the prior 365 days, with a total of 856 episodes of hospitalization. Weighted rates of hospitalization were 33 per 1000 in those with insurance, compared to 29 per 1000 in those with no insurance. After controlling for gender, place of residence, social group and UMPCE quintile, a person with insurance was significantly more likely to be hospitalized compared to a person with no insurance (AOR 1.388; 95% CI: 1.190–1.620) (S1 Table).
In those covered by insurance, two thirds of hospitalization episodes were in the public sector (67.2%), compared to less than half (46.6%) in those with no insurance (Fig 2).
The level of facility for hospitalizations for the insured and uninsured are given in Table 3. It shows that most of the hospitalizations were in the higher level facilities both in the public and private sectors, which for the public sector means that they were in district hospitals and medical colleges (as opposed to lower level health centers).
The multivariate logistic regression showed that women (AOR 1.80; 95% CI: 1.25–2.58), Scheduled Tribes and the poorest (Q1) were significantly more likely to be hospitalized in the public sector than men, other social groups and other UMPCE groups respectively (S2 Table). Taking infection as the reference group, conditions like cancer (AOR 0.11; 95% CI: 0.01–0.94) and respiratory conditions (AOR 0.30; 95% CI: 0.09–0.97) were significantly less likely causes of admission in the public sector, while obstetric and child birth-related conditions were significantly more likely in the public sector (AOR 1.63; 95% CI: 1.03–2.57) (S2 Table). Enrolment in government insurance was associated with hospitalization in the public sector at 90% Confidence Levels (AOR 1.32; 90% CI: 1.01–1.72) (S2 Table).
Out of pocket expenditure
Of those with insurance, 34.0% of hospitalization episodes in the public sector were ‘cashless’, that is, no OOP expenditure was incurred, whereas 16.1% of public sector users without insurance got cashless services. For those going to the private sector, 5.0% of the insured and 5.7% of those not insured did not incur any OOP expenditure. In those with insurance who incurred OOP expenditure, the median OOP expenditure in private (Rs.10, 000) was eight times more than in the public sector (Rs.1, 200). In the uninsured, median OOP expenditure in private (Rs.17, 900) was nearly twelve times higher than in the public sector (Rs.1, 500).
Table 4 gives the median OOP expenditure disaggregated by insurance coverage and socio-economic categories, although analysis is limited by small sample sizes in the disaggregated analysis precluding public/private comparisons.
Multivariate logistic regression with OOP expenditure (Y/N) as the outcome variable showed that government insurance coverage (AOR 0.265; 95% CI: 0.174–0.405) and childbirth conditions (AOR 0.516; 95% CI: 0.290–0.918) were significantly less likely to entail OOP expenditure than no insurance and other ailments respectively (S3 Table). On the other hand, women (AOR 1.700; 95% CI: 1.012–2.858) were more likely to incur OOP expenditure than men and hospitalization in private hospital had a significantly higher possibility of incurring OOP expenditure than any other type of facility (S3 Table).
Among people who were hospitalized and incurred OOP payments, 82% used their savings, and 13% borrowed money (Fig 3). The others took money from friends or family (3%), sold physical assets (0.2%) or arranged for it in some other way (2%).
Catastrophic expenditure due to hospitalization costs
Household catastrophic expenditure due to hospitalization was calculated for the 645 households where at least one person was hospitalized during the prior 365 days. Using 10% of household consumer expenditure on OOP expenditure for hospitalization as the cut-off mark, 35.5% of the households experienced catastrophic expenditure due to hospitalization costs. It was not possible to assess the effects of insurance coverage on this as within the households, members had a mixed profile of enrolment.
This study, using the National Sample Survey (71st Round) on Health conducted in 2014, explored coverage of government insurance schemes, utilization of hospitalization and out of pocket expenditure for the insured and uninsured in Chhattisgarh State of India. The discussion below examines these findings in the context of other studies and their relevance to the larger debates on government insurance and UHC.
Chhattisgarh, a state with predominantly rural and poor populations started implementing RSBY in 2009 and universalized the scheme in 2012. At the time of the study (2014) enrolment percentages were low, although the recent programme data shows continuing growth—the number of families enrolled increased from 1.04 million in March 2011 (before universalization)  to 4.16 million in April 2016 . The study found that enrolment was marginally higher in rural areas, among women and Scheduled Tribes, compared to the total covered. These finding on gender and rural residence echo findings from other studies [17, 18, 52].
The rates of hospitalization for those who were covered with insurance were slightly higher than for those not covered with insurance. The evidence on impacts of insurance on utilization elsewhere is mixed . In the utilization of hospital services, one of the critical purposes of the health insurance scheme is to “empower” people by providing freedom of choice to go to a public or private sector facility . Jain et al  argue that a purchasing mechanism like health insurance can make the private sector more accessible to the poor. However, this study shows that even when insured, people appear to be utilizing the public sector more. Certain explanations could be drawn using the evidence from this and other studies. Firstly, multivariate logistic regression on public sector hospitalization shows that women, tribal populations and poorest are significantly more likely to go to the public sector. Other studies too have documented the higher use of the public sector by poorer populations  and the lower availability of private facilities in poorer and rural areas [36, 39, 40]. Moreover, a recent study comparing two rounds of NSSO data for whole of the country has found that use of public sector hospitals has increased and for the insured, there is higher probability of being hospitalized in a public, rather than a private hospital . Secondly, our study also shows obstetrics and gynecological conditions were significantly more likely to be hospitalized in the public sector. The National Family Health Survey-4 data of Chhattisgarh shows that deliveries in the public sector increased by eight times over ten years (from 6.9% in 2005–06 to 55.9% in 2015–16), one of the highest increases in the country . Therefore the high number of public sector hospitalizations could be related to the high public sector utilization by women for delivery and other conditions, which has also emerged from other studies . Thirdly, the data on OOP expenditure shows that there was greater probability of incurring expenditure in the private sector and the median amounts in the private sector even for the insured were higher than in the public sector. Lack of financial protection is a critical barrier to access and utilizing health services [1, 2] and therefore higher affordability of the public sector may have led to more people utilizing it.
Although the study shows a higher rate of utilization of the public sector by the people who were enrolled in the government insurance, programme data of the scheme shows that the insurance card is being used more in private than in public sector . One possible explanation for this difference could be that although people are making greater use of the public sector, they may not be routinely using the insurance card in the public sector.
Financial protection has been the mainstay of any government insurance scheme. For RSBY too, providing “cashless” hospitalization services and reducing catastrophic expenditure for hospitalization has been highlighted as the most important objective of the scheme . The results of the study show that although the insured were less likely to incur OOP expenditure than the uninsured, most of the insured had to incur OOP expenditure. One third (35.5%) of the households experienced catastrophic health expenditure (CHE) due to medical expenses for hospitalizations.
Studies both from India [52, 68, 69] and other countries [21, 22] have found evidence of financial protection from insurance schemes. However, most studies from India also show that patients continue to incur OOP expenditure despite coverage with government insurance [15, 58, 60, 65, 70, 71, 73, 75]. A recent systematic review on the impact of publicly financed health insurance schemes found that though utilization increased with coverage, there was no impact on reduction of OOP expenditure . Moreover, studies have also shown that the impact is often less on the poor and rural populations [17, 25, 51, 68, 75]. Analyzing the same NSSO survey data for the whole of India, Sundararaman et al  argue that the difference in net OOP expenditure between the insured and uninsured is too small to claim financial protection.
Comparing OOP expenditure in the public and private sectors, “cashless” hospitalizations were more common in public than in private facilities and those going to the private sector were more likely to incur OOP expenditure. Where OOP expenditure was incurred, amounts were eight times higher in private than in public facilities for people covered with insurance. Previous work in Chhattisgarh [72, 94] by the authors, and by Rent & Ghosh  in neighbouring Maharashtra has found similar differences. It is pertinent to note that in Chhattisgarh, the private sector receives the major share (82.9%) of claim amounts, and accounts for two-third of hospitalizations under the scheme . While the NSSO data-set does not indicate whether the insurance was actually used during hospitalization, it is assumed that those covered would try to utilize it and ensure “cashless” hospitalizations. The findings of this analysis suggest that the core RSBY/MSBY goal of “cashless” utilization of health facilities is far from being achieved.
The NSSO survey data on enrolment includes enrolment in ESIS and CGHS in addition to RSBY/MSBY, although, as discussed in the methods, the RSBY/MSBY made up the highest proportion of the enrolled under any government insurance.
The study found that in the private sector, 5.7% of the uninsured did not incur OOP expenditure. On examining these six cases, no pattern was found in terms of their socio-economic characteristics, age, rural/urban residence or type of ailment, and no reason could be gauged for the zero OOP expenditure. There may also have been a problem of recall bias in these cases.
Chhattisgarh is a predominantly rural state, as is the case with most of India. Of India’s population, 69% is rural with more than half (16 out of 29) of the states having rural populations of above 70% . All states have a similar healthcare system, with a private/public mix, and with government insurance schemes primarily relying on private providers. However, in most states, the insurance scheme has not been universalized and enrolment in the schemes is much lower than in Chhattisgarh. Nevertheless, universal insurance coverage is seen as a move towards UHC . Therefore the findings on enrolment, private and public sector utilization, and OOP expenditure for the insured and uninsured, which emerge from this study, in the context of geographical, socio-economic and gender inequities, are relevant for India and have lessons for UHC elsewhere. It also illustrates the relevance of the recently changed indicator for measuring financial risk protection of UHC in the SDGs .
This study of Chhattisgarh’s universal government health insurance scheme found that despite insurance coverage, most had to incur OOP expenditure, which was higher in the private than the public sector. Moreover, a large proportion of households with members hospitalized experienced catastrophic health expenditure. Whether through choice or availability, those with insurance coverage made greater use of services in the public sector. The public sector was less expensive, and catered to the more vulnerable groups. The patterns of utilization and differential OOP expenditure across public and private sectors under publicly financed health insurance warrant further investigation, so as to inform strategies that make best use of scarce public resources and deliver on the promise of equity under Universal Health Coverage.
S1 Table. Adjusted Odds Ratio of hospitalization by characteristics and its 95% CI (N = 5977).
S2 Table. Adjusted Odds Ratio of hospitalization in the public sector by characteristics and its 95% CI (N = 856*).
The authors wish to thank Dr. T. Sundararaman and Dr. Indranil Mukhopadhyay for their support in accessing and understanding the NSSO 71st round survey data.
- 1. World Health Organisation (WHO). The World Health Report–Health Systems Financing: The path to Universal Coverage. Geneva: World Health Organization; 2010.
- 2. McIntyre D., Ranson M. K., Aulakh B. K. and Honda A. Promoting universal financial protection: evidence from seven low- and middle-income countries on factors facilitating or hindering progress. Health Research Policy and Systems 2013; 11:36. pmid:24228762
- 3. House Chatham. Shared Responsibilities for Health: A Coherent Global Framework for Health Financing. Final Report of the Centre on Global Health Security Working Group on Health Financing. London: Chatham House; 2014.
- 4. Roberts M. J., Hsiao W. C., & Reich M. R. Disaggregating the Universal Coverage Cube: Putting Equity in the Picture. Health Systems & Reform. 2015; 1(1): 22–27.
- 5. Sen A. Universal healthcare: the affordable dream. The Guardian. 2015. Available from: www.theguardian.com/society/2015/jan/06/-sp-universal-healthcare-the-affordable-dream-amartya-sen
- 6. Kutzin J and Sparkes S. P. Health systems strengthening, universal health coverage, health security and resilience. Bulletin of the World Health Organisation. 2016; 94:2.
- 7. Frenz P., and Vega J. Universal health coverage with equity: what we know, don’t know and need to know. Background paper for the First Global Symposium on Health Systems Research, 16–19 November 2010, Montreux, Switzerland. 2010. Available from: www.healthsystemsresearch.org/hsr2010/images/stories/9coverage_with_equity.pdf
- 8. Kutzin J. Anything goes on the path to universal health coverage? No. Bulletin of the World Health Organization. 2012; 90: 867–868. pmid:23226900
- 9. World Health Organisation (WHO). Arguing for Universal Health Coverage. Geneva: World Health Organisation; 2013.
- 10. Ooms G., Latif L. A., Waris A., Brolan C. E., Hammonds R., Friedman E.A. et al Is universal health coverage the practical expression of the right to health care? BMC International Health and Human Rights. 2014; 14 (3): 1–7.
- 11. World Health Organisation (WHO). Making fair choices on the path to universal health coverage: Final report of the WHO Consultative Group on Equity and Universal Health Coverage. Geneva: World Health Organization; 2014.
- 12. Kutzin J. Health financing for universal coverage and health system performance: concepts and implications for policy. Bulletin of the World Health Organisation. 2013; 91: 602–611.
- 13. Lagomarsino G., Garabrant A, Adyas A, Muga E., Otoo N. Moving towards universal health coverage: health insurance reforms in nine developing countries in Africa and Asia. Lancet. 2012; 380: 933–43. pmid:22959390
- 14. Oxfam. Universal Health Coverage: Why health insurance schemes are leaving the poor behind. 2013. Available from: www.oxfam.org/sites/www.oxfam.org/files/bp176-universal-health-coverage-091013-en_.pdf
- 15. Sundararaman T., Muraleedharan V. R., Mukhopadhyay I. NSSO 71st Round Data on Health and Beyond Questioning Frameworks of Analysis. Economic & Political Weekly. 2016a; 51 (3): 85–88 pmid:27362818
- 16. Jain N., Kumar A., Nandraj S., Furtado K. M. NSSO 71st Round Same Data, Multiple Interpretations. Economic and Political Weekly. 2015; 50 (46 & 47): 84–87.
- 17. Acharya A., Vellakkal S., Taylor F., Masset E., Satija A., Burke M. et al. Impact of national health insurance for the poor and the informal sector in low- and middle-income countries: a systematic review. London: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London; 2012.
- 18. Jehu-Appiah C., Aryeetey G., Spaan E., de Hoop T., Agyepong I. and Baltussen R. Equity aspects of the National Health Insurance Scheme in Ghana: Who is enrolling, who is not and why? Social Science & Medicine. 2011; 72:157–165
- 19. Odeyemi I. AO. and Nixon J. Assessing equity in health care through the national health insurance schemes of Nigeria and Ghana: a review-based comparative analysis. International Journal for Equity in Health. 2013; 12:9. pmid:23339606
- 20. Kusi A., Enemark U., Hansen K.S. and Asante F. A. Refusal to enrol in Ghana’s National Health Insurance Scheme: is affordability the problem? International Journal for Equity in Health. 2015; 14:2. pmid:25595036
- 21. Galarraga O., Sosa-Rubi S. G., Salinas-Rodriguez A., and Sesma-Vazquez S. Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico. European Journal of Health Economics. 2010; 11: 437–447 pmid:19756796
- 22. Knaul F. M., González-Pier E., Gómez-Dantés O., García-Junco D., Arreola-Ornelas H., Barraza-Lloréns M. et al. The quest for universal health coverage: achieving social protection for all in Mexico. Lancet. 2012; 380: 1259–79. pmid:22901864
- 23. Liu X., Tang S., Yu B., Phuong N. K., Yan F, Thien D.D. et al. Can rural health insurance improve equity in health care utilization? a comparison between China and Vietnam. International Journal for Equity in Health. 2012; 11:10. pmid:22376290
- 24. Spaan E., Mathijssen J., Tromp N., McBain F., ten Have A. and Baltussen R. The impact of health insurance in Africa and Asia: a systematic review. Bulletin of the World Health Organisation. 2012; 90:685–92.
- 25. Barraza-Lloréns M., Panopoulou G. and Díaz B.Y. Income-related inequalities and inequities in health and health care utilization in Mexico, 2000–2006. Rev Panam Salud Publica. 2013; 33(2): 122–30. pmid:23525342
- 26. Grogger J., Arnold T., Leo'n A.S. and Ome A. Heterogeneity in the effect of public health insurance on catastrophic out-of-pocket health expenditures: the case of Mexico. Health Policy and Planning. 2014; 30 (5).
- 27. Meng Q., Yuan B., Jia L., Wang J., Yu B., Gao J. et al. Expanding health insurance coverage in vulnerable groups: a systematic review of options. Health Policy and Planning. 2011; 26: 93–104. pmid:20813837
- 28. Jacobs B., Ir P., Bigdeli M., Annear P. L., and Van Damme W. Addressing access barriers to health services: an analytical framework for selecting appropriate interventions in low-income Asian countries. Health Policy and Planning. 2012; 27: 288–300. pmid:21565939
- 29. Macha J., Harris B., Garshong B., Ataguba J. E., Akazili J., Kuwawenaruwa A. et al. Factors influencing the burden of health care financing and the distribution of health care benefits in Ghana, Tanzania and South Africa. Health Policy and Planning. 2012; 27: 46–54.
- 30. Basu S., Andrews J., Kishore S., Panjabi R., Stuckler D. Comparative performance of private and public healthcare systems in low- and middle-income countries: a systematic review. PLoS Med. 2012; 9 (6).
- 31. Hsu J. The relative efficiency of public and private service delivery. World Health Report (2010) Background Paper, No. 39. World Health Organisation. 2010. Available from: www.who.int/healthsystems/topics/financing/healthreport/P-P_HSUNo39.pdf
- 32. Mackintosh M., Channon A., Karan A., Selvaraj S., Zhao H., Cavagnero E. What is the private sector? Understanding private provision in the health systems of low-income and middle-income countries. Lancet. 2016; 388: 596–605. pmid:27358253
- 33. Patel V., Parikh R., Nandraj S., Balasubramaniam P., Narayan K., Paul V. K. et al. Assuring health coverage for all in India. Lancet. 2015; 386: 2422–2435. pmid:26700532
- 34. Joe W., Mishra U. S. and Navaneetham K. Health Inequality in India: Evidence from NFHS. Economic and Political Weekly. 2008; 43 (31): 41–48.
- 35. Baru R., Acharya A., Acharya S., Shiva Kumar A.K., Nagaraj K. Inequities in Access to Health Services in India: Caste, Class and Region. Economic & Political Weekly. 2010; 45:49–58.
- 36. Balarajan Y, Selvaraj S, Subramanian SV. Health care and equity in India. Lancet. 2011; 377(9764): 505–515. pmid:21227492
- 37. Nandi A., Ashok A., Laxminarayan R. The Socioeconomic and Institutional Determinants of Participation in India’s Health Insurance Scheme for the Poor. PLoS ONE. 2013; 8(6).
- 38. Dreze J. and Sen A. An Uncertain Glory: India and Its Contradictions. New Delhi: Penguin Books; 2013.
- 39. Ghosh S. Equity in the utilization of healthcare services in India: evidence from National Sample Survey. International Journal of Health Policy and Management. 2014; 2(1): 29–38. pmid:24596902
- 40. Prinja S., Kumar M. I., Pinto A.D., Jan S., Kumar R. Equity in Hospital Services Utilisation in India. Economic & Political Weekly. 2013; 48 (12).
- 41. Shiva Kumar A. K., Chen L.C., Choudhury M., Ganju S., Mahajan V., Sinha A. et al. Financing health care for all: challenges and opportunities. Lancet. 2011; 377 (9766): 668–679. pmid:21227490
- 42. Dror D. M., and Vellakkal S. Is RSBY India’s platform to implementing universal hospital insurance? Indian Journal of Medical Research. 2012; 135: 56–63. pmid:22382184
- 43. Federation of Indian Chambers of Commerce and Industry (FICCI). Health Insurance Vision 2020. 2013. Available from: www.ficci.com/spdocument/20347/HI-Vision-2020-Exec-Summ.pdf
- 44. Singh J. Budget 2016: Health insurance for all. Live Mint. 2016. Available from: www.livemint.com/Politics/hQihM87Emz6wxsieuIUZvO/Budget-2016-Health-insurance-for-all.html
- 45. Public Health Foundation of India (PHFI). A Critical Assessment of the Existing Health Insurance Models in India. The Planning Commission of India: New Delhi; 2011.
- 46. Shroff Z. C., Roberts M. J., and Reich M. R. Agenda Setting and Policy Adoption of India's National Health Insurance Scheme: Rashtriya Swasthya Bima Yojana. Health Systems & Reform. 2015; 1 (2): 107–118.
- 47. Virk A. K. and Atun R. Towards universal health coverage in India: a historical examination of the genesis of Rashtriya Swasthya Bima Yojana- The health insurance scheme for low-income groups. Public Health. 2015; 129 (6): 810–817. pmid:25753280
- 48. National Health Systems Resource Center (NHSRC). NRHM in the Eleventh Five Year Plan (2007–2012): Strengthening Public Health Systems. New Delhi: NHSRC; 2012.
- 49. www.rsby.gov.in [Internet]. Website of the Rashtriya Swasthya Bima Yojana (RSBY). Ministry of Health and Family Welfare, Government of India. 2016. Available from: www.rsby.gov.in
- 50. Ghosh S. Publicly-Financed Health Insurance for the Poor Understanding RSBY in Maharashtra. Economic & Political Weekly. 2014b: 49 (43 & 44):93–99
- 51. Prinja S., Chauhan A.S., Karan A., Kaur G., Kumar R. Impact of Publicly Financed Health Insurance Schemes on Healthcare Utilization and Financial Risk Protection in India: A Systematic Review. PLoS One [Internet]. 2017;12(2):e0170996. pmid:28151946
- 52. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. (2015). Health Insurance for India's poor: Meeting the challenge with information technology. A publication in the German Health Practice Collection. 2015. Available from: www.health.bmz.de/good-practices/GHPC/Health_Insurance_India_New/RSBY_EN_long-Oct-2011.pdf
- 53. Nagpal S. Expanding Health Coverage for Vulnerable Groups in India. Universal Health Coverage Studies Series (UNICO) No. 13. Washington DC: The World Bank; 2013.
- 54. Narayana D. Review of the Rashtriya Swasthya Bima Yojana. Economic and Political Weekly. 2010; 45 (29): 13–18.
- 55. Sun Changqing. Chapter 4: An analysis of RSBY enrolment patterns: Preliminary evidence and lessons from the early experience. In Palacios, Robert, Das, Jishnu and Sun. Changqing (eds) “India's Health Insurance Scheme for the Poor: Evidence from the Early Experience of the Rashtriya Swasthya Bima Yojana”. New Delhi: Centre for Policy Research; 2012. p. 84–116.
- 56. Rathi P. Evaluation of Rashtriya Swasthya Bima Yojana, a Health Insurance Scheme for below poverty line people in Amravati. 2012. Available from: www.iimb.ernet.in/sites/default/files/u181/IIMB%20PGPPM%20Policy%20Folio_Paper_Prateek%20Rathi_March%202012.pdf
- 57. Health Inc Consortium (Health Inc). Health Inc- Towards equitable coverage and more inclusive social protection in health. Studies in Health Services Organisation & Policy (SHSOP), 32, 2014. (Series ed) B. Criel, V. De Brouwere, W. Van Damme and B. Marchal, series editor. Antwerp: ITGPress; 2014.
- 58. Rao M, Katyal A, Singh P V, Samarth A, Bergkvist S, Kancharla M, et al. Changes in addressing inequalities in access to hospital care in Andhra Pradesh and Maharashtra states of India: a difference-in-differences study using repeated cross-sectional surveys. BMJ Open [Internet]. 2014 Jan [cited 2015 Sep 10];4(6):e004471. pmid:24898084
- 59. Desai S. Keeping the ‘Health’ in Health Insurance. Economic and Political Weekly. 2009; 44(38): 18–21.
- 60. Grover S. & Palacios R. Chapter 6: The first two years of RSBY in Delhi. In: Palacios Robert, Das Jishnu and Sun Changqing, editors. India's Health Insurance Scheme for the Poor: Evidence from the Early Experience of the Rashtriya Swasthya Bima Yojana. New Delhi: Centre for Policy Research; 2011. p. 153–188.
- 61. Shukla R., Shatrugna V., & Srivatsan R. Aarogyasri healthcare model: Advantage private sector. Economic and Political Weekly. 2011; 46(49): 38–42.
- 62. La Forgia G. and Nagpal S. Government-Sponsored Health Insurance in India: Are You Covered? Directions in Development. Washington DC: World Bank; 2012.
- 63. Kapilashrami A., and Venkatachalam D. Health Insurance: Evaluating the Impact on the Right to Health. Working Paper. New Delhi: Sama—Resource Group for Women and Health; 2013.
- 64. Prasad N. P. and Raghavendra P. Healthcare Models in the Era of Medical Neo-liberalism: A Study of Aarogyasri in Andhra Pradesh. Economic and Political Weekly. 2012; 47 (43).
- 65. Selvaraj S., & Karan A. K. Why publicly-financed health insurance schemes are ineffective in providing financial risk protection. Economic and Political Weekly. 2012; 48(11): 60–68.
- 66. Nundy M., Dasgupta R., Kanungo K., Nandi S. and Murugan G. The Rashtriya Swasthya Bima Yojana (RSBY) Experience in Chhattisgarh: What does it mean for Health For All. New Delhi: Sama—Resource Group for Women and Health; 2013.
- 67. Dasgupta R., Nandi S., Kanungo K., Nundy M., Murugan G. and Neog R. What the Good Doctor Said: A Critical Examination of Design Issues of the RSBY Through Provider Perspectives in Chhattisgarh, India. Social Change. 2013; 43 (2): 227–243.
- 68. Fan V., Karan A., Mahal A. State Health Insurance and Out- of-Pocket Health Expenditures in Andhra Pradesh, India. International Journal of Health Care Finance and Economics. 2012; 12 (3): 189–215 pmid:22767078
- 69. Sood N., Bendavid E., Mukherji A., Wagner Z., Nagpal S., and Mullen P. Government health insurance for people below poverty line in India: quasi-experimental evaluation of insurance and health outcomes. British Medical Journal. 2014; 349: g5114. pmid:25214509
- 70. Jain N. and Chandra U. Evaluating the impact of national health insurance programme 'Rashtriya Swasthya Bima Yojana' in India. Abstract no. L1.28. Abstracts of the Third Global Symposium on Health Systems Research: The Science and Practice of People-Centred Health Systems, 30 September– 3 October 2014, Cape Town, South Africa. 2014. Available from: www.healthsystemsresearch.org/hsr2014/sites/default/files/Poster-Presentations.pdf
- 71. Centre for Tribal and Rural Development (CTRD). Final Report on Evaluation of the ‘Rashtriya Swasthya Bima Yojana Scheme’ in Chhattisgarh. 2012. Available from: www.rsbychhattisgarh.in/WebSite/UploadDoc/70.pdf
- 72. Nandi S., Nundy M., Prasad V., Kanungo K., Khan H., Haripriya S. et al. The Implementation of RSBY in Chhattisgarh, India: A Study of the Durg District. Health, Culture and Society, (Health System Dynamics and Barriers). 2012; 2 (1).
- 73. Rajasekhar D., Berg E., Ghatak M., Manjula M., & Roy S. Implementing health insurance: The rollout of Rashtriya Swasthya Bima Yojana in Karnataka. Economic and Political Weekly. 2011; 46(20): 56–63.
- 74. Rao M., Kadam S., Sathyanarayana T.N., Shidhaye R., Shukla R., Ramachandra S. S. et al. A Rapid Evaluation of the Rajiv Aarogyasri Community Health Insurance Scheme-Andhra Pradesh. BMC Proceedings 2012; 6 Suppl 1:O4.
- 75. Rent P. and Ghosh S. Understanding the “Cash-Less” Nature of Government-Sponsored Health Insurance Schemes: Evidence From Rajiv Gandhi Jeevandayee Aarogya Yojana in Mumbai. SAGE Open. 2015; October-December: 1–10.
- 76. Registrar General, India (RGI). Provisional Population Totals: Chhattisgarh, CENSUS OF INDIA 2011. New Delhi: Government of India; 2011.
- 77. Department of Food and Public Distribution (DFPD). Coverage of Population under Nation Food Security Act, 2013. Foodgrain Bulletin, Government of India. 2015. Available from: www.dfpd.nic.in/writereaddata/images/EstdStatewiseNFSA.pdf
- 78. Forest Survey of India (FSI). India State of Forest Report, 2011. Dehradun: Ministry of Environment & Forests. 2011. Available from: www.fsi.nic.in/cover_2011/chattisgarh.pdf
- 79. Sinha D. Maternal and Child Health: Inching Ahead, Miles to Go. Economic and Political Weekly. 2015; 50(49): 16–19.
- 80. Joint Learning Network (JLN). India–Chhattisgarh State: Approaches to covering poor & informal populations to achieve UHC. Undated. Available from: www.jointlearningnetwork.org/resources/india-chhattisgarh-state-approaches-to-covering-poor-informal-populations-t
- 81. Dreze J. and Khera R. The BPL Census and a Possible Alternative. Economic & Political Weekly. 2010; 45 (9): 54–63
- 82. State Nodal Agency—RSBY and MSBY. Information on Enrolment in RSBY and MSBY till 30th April 2016. Health & Family Welfare Department, Government of Chhattisgarh.
- 83. Centre for Tribal and Rural Development (CTRD). Independent Assessment Study on Process of Enrolment under Rashtriya Swasthya Bima Yojana and Mukhyamantri Swasthya Bima Yojana in Chhattisgarh. 2013. Available from: www.cg.nic.in/healthrsby/RSBY_Documents/Revised%20FINAL%20REPORT%20on%20RSBY%20Enrollment%20%2029-06-2013.pdf
- 84. State Nodal Agency—RSBY and MSBY. Information on utilization in RSBY and MSBY for the financial year 2015–16. Health & Family Welfare Department, Government of Chhattisgarh.
- 85. McIntyre D., McKee M., Balabanova D., Atim C., Reddy K. S. and Patcharanarumol W. Open letter on the SDGs: a robust measure for universal health coverage is essential. The Lancet. 2016; 6736 (16).
- 86. National Sample Survey Office. Key Indicators of Social Consumption in India: Health, NSS 71st Round (January to June 2014). New Delhi: Ministry of Statistics and Programme Implementation, Government of India; 2015.
- 87. cg.nic.in/healthrsby [Internet]. Raipur: Health and Family Welfare Department, Government of Chhattisgarh; c2017 [cited 2017 Sept 20]. Available from: http://cg.nic.in/healthrsby/
- 88. Employees' State Insurance Corporation (ESIC). Annual Report 2013–14. Available from: http://www.esic.nic.in/Publications/ESICAnnual%20Report%202013-14.pdf
- 89. cghs.gov.in [Internet]. Delhi: Central Government Health Scheme, Ministry of Health and Family Welfare; c2017 [cited 2017 Sept 20]. Available from: http://cghs.gov.in/index.php
- 90. Wagstaff A., and van Doorslaer E. Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993–98. Health Economics. 2003; 12: 921–34. pmid:14601155
- 91. Katyal A., Singh P. V., Samarth A., Bergkvist S. and Rao M. Using the Indian National Sample Survey data in public health research. The National Medical Journal of India. 2013; 26:5:291–294. pmid:25017839
- 92. Ravi S., Ahluwalia R., Bergkvist S. Health and Morbidity in India (2004–2014). Brookings India Research Paper No. 092016. 2016. Available from: https://www.brookings.edu/wp-content/uploads/2016/12/201612_health-and-morbidity.pdf
- 93. International Institute for Population Sciences (IIPS), Macro International. National Family Health Survey (NFHS-4) 20015–16: State Fact Sheet Chhattisgarh. 2017. Available from: http://rchiips.org/NFHS/pdf/NFHS4/CT_FactSheet.pdf
- 94. Nandi S., Dasgupta R., Garg S., Sinha D., Sahu S., Mahobe R. Uncovering Coverage: Utilisation of the Universal Health Insurance Scheme, Chhattisgarh by Women in Slums of Raipur. Indian Journal of Gender Studies. 2016; 23 (1): 43–68.
- 95. Ministry of Rural Development. Demographic Profile. 2016. Available from: rural.nic.in/sites/downloads/IRDR/1.%20Demographic%20Profile.xls
- 96. A victory today for Universal Health Coverage- Statement from Oxfam. Available from: http://www.globalhealthcheck.org/?p=1943