How effective health insurance schemes are in tackling economic burden of healthcare in India

How effective health insurance schemes are in tackling economic burden of healthcare in India

G Model CEGH 182 No. of Pages 8 Clinical Epidemiology and Global Health xxx (2017) xxx–xxx Contents lists available at ScienceDirect Clinical Epide...

753KB Sizes 0 Downloads 38 Views

G Model CEGH 182 No. of Pages 8

Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

Contents lists available at ScienceDirect

Clinical Epidemiology and Global Health journal homepage: www.elsevier.com/locate/cegh

Original article

How effective health insurance schemes are in tackling economic burden of healthcare in India Sandhya R. Mahapatroa , Pushpendra Singhb,* , Yadawendra Singhc a

A.N. Sinha Institute of Social Studies, Patna, India Department of Humanities and Social Sciences, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India c Jawaharlal Nehru University (JNU), Centre for the Study of Regional Development, School of Social Sciences (SSS) III, New Delhi, Delhi 110067, India b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 6 February 2017 Accepted 13 April 2017 Available online xxx

Background: India is one of the most privatised health systems with high OOP payment for health care in the world. The financial burden of OOP payment has an iniquitous effect on access to health care as it restricts health care accessibility among poor. To provide universal health care access to all its citizen government has launched health insurance programs in the recent past. Objective: The study attempts to understand the impact of health insurance schemes on tackling the economic burden of out of pocket expenditure and its effectiveness in reducing economic inequalities in health care spending. Method: The study utilises National Sample Survey 2014 data to fulfill the objectives. Bi-variate analysis and two-part model were used to examine the association of health insurance with the level of health expenditure and financial burden. Results: The paper shows that health insurance schemes are effective in reducing the burden of OOP expenditure but economic disparities in the financial burden of OOP expenditure exist where the poor with less income spends a greater share of household income than the rich. Conclusion: An increasing coverage of poor under health insurance no doubt protects against health care impoverishment, but mere provision health care does not address the issue of equity in health spending as the burden of health spending was more among poor. The major implication of the findings is that there is a need for analysing the efficiency and equity implication of the health insurance schemes in providing financial protection © 2017 INDIACLEN. Published by Elsevier, a division of RELX India, Pvt. Ltd. All rights reserved.

Keywords: Health insurance Out of pocket expenditure Inequality Economic burden India

1. Introduction Together with demographic ageing, rising longevity and epidemiological transition in India, the demand for health care and consequently health expenditure is increasing across socioeconomic strata. India has one of the highly privatised health systems in the world with the accelerated cost of health, and it ranks third among the South Asian countries in terms of Out-OfPocket Expenditure (60%) followed by Myanmar & Bangladesh.1 Many of the times, the Out-of-Pocket spending, the principal source of health care financing in India, has a disastrous impact on the households as the households are forced to borrow and sell their assets to meet these expenses in the absence of any

* Corresponding author. E-mail addresses: [email protected] (S.R. Mahapatro), [email protected], [email protected] (P. Singh), [email protected] (Y. Singh).

prepayment mechanism.2 More than 80% of health expenditure in India is met through private sources, which placed a considerable financial burden on households. Health shocks associated with catastrophic expenditure adversely impact household economics by pushing households into below poverty line.3,1,4,5 Further, inequality in access to health care exacerbates with a higher burden of OOP expenditure among the households with lower capacity to pay6,7 and hence restricts access to basic health care services.8,9,10 Addressing these issues in Indian context (given the high level of the poverty level, one-fourth of the population living below the poverty line) is significant as health might play a critical role in its development process. During last decade the policy debate in India shifted from “health for all” to “health for all with financial protection.”11 With the aspiration to provide universal health coverage to all the citizens, the governments both at the central and state level have launched various health insurance schemes in the recent past. The country, which had a coverage of health insurance as low as about 75 million people in 2007 saw the rapid increase and its insurance

http://dx.doi.org/10.1016/j.cegh.2017.04.002 2213-3984/© 2017 INDIACLEN. Published by Elsevier, a division of RELX India, Pvt. Ltd. All rights reserved.

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

2

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

coverage rose to 302 million in 2010.12 As per government report,13 health insurance covered approximately 15% of the total population. The manifold increase in insurance coverage was the result of the introduction of the government of India’s flagship scheme of Rashtriya Swasthya Bima Yojana (RSBY). Evidence on the adequacy of health insurance in financing health care and health care access showed mixed results.14,15,16,17 Examining the effectiveness of the pro-poor public-funded insurance schemes especially RSBY, studies show that these insurance schemes failed in providing financial protection to the poor.5,18,19,20 However, these studies were limited only to RSBY. After a long year gap of 10 years, the information released by National Sample Survey Office on health insurance has provided an opportunity to analyse the different health insurance schemes both public and private in financing health care. Further, it is also interesting to examine the role of insurance schemes to tear down the economic disparities in health expenditure which was not addressed in earlier studies. The increase in coverage of insurance increases health care utilisation but might lead to the changes in health behaviour of the insurer leading to moral hazard problem as the additional amount of medical care demanded may drive up health expenditure.Thus, taking into consideration the presence of moral hazard, the present study attempt to investigate whether increasing insurance coverage reduces the cost of medical treatment or not. The objective of this paper is thus twofold: first, to understand the impact of health insurance on the burden of Out of pocket expenditure and secondly, to understand the role of health insurance in reducing economic inequalities in health care spending. The remainder of the paper is divided into following parts. Data and method used for this study are discussed in section two. The socioeconomic differential in coverage of health insurance is presented in section three. Health care utilisation and OOP expenditure by insurance status are presented in section four. The empirical estimation of the impact of health insurance schemes on OOP is presented in section five. The last section discusses the inequalities in health care cost and the role of health insurance in this aspect. 2. Data and method 2.1. Data source Data for the present study was drawn from 71 st round National Sample Survey, 2014, ‘Social Consumption: Health’ Schedule 25.0. This survey aimed at generating basic quantitative information on the behaviour of the sample households seeking treatment (for ailments) during the last 15 days and hospitalisation (as inpatients) during last 365 days. The information on the insurance coverage was collected for both the reference periods; however, we used information of hospitalisation during 365 days in our analysis. The NSSO 71 st round is not an evaluation of the insurance schemes. But it does draw attention to this wide gap between nominal coverage and effective coverage and this is consistent with most other evaluations of government-financed insurance schemes.19 2.2. Variables used NSS provides information regarding sources of finance for healthcare expenses (income, saving, borrowing, sale of asset, etc.); annual amount of insurance premium paid by household members and reimbursement received (whether covered by any scheme for health expenditure support: government funded insurance scheme e.g. RSBY, Arogyasri, CGHS, ESIS, etc. employer supported health protection (other than govt.), arranged by

household with insurance companies, others, and not covered). This allows us to identify the insured and uninsured persons under a particular scheme with Out-of-Pocket (OOPE) Expenditure and socio-economic variables. The OOPE includes expenditure during hospitalisation such as registration fees, doctor’ fee, medicine, tests, transportation etc. and exclude the health insurance reimbursement. For examining the impact of health insurance on health care expenditure, the present study has considered only those who were hospitalised and made hospitalisation expenditure during last 365 days. 2.3. Data analysis Bivariate and Multivariate analysis were used to carry out the objective. For the econometric analysis, the outcome variable of interest is the amount of Out-of-Pocket Expenditure during last 365 days. To examine the impact of health insurance on OOP payment, two-part model was used as the OOP payment for certain cases have zero values and the two-part model was used in the study to capture the zero-inflated values. Two-part model has also used because it adds elasticity by modeling separate processes to describe the probability of positive expenditure and the ordinary OOP amount.21,22 The first part estimates the probability of incurring OOP expenditure based on the full sample through logit model and second part models the level of expenditure conditional to OOP > 0 through linear regression. The first part is, whether the claim outcome is positive. Conditional on its being positive, the second part refers to its level. To be more specific, let Yi denote the claim amount for individual i (i = 1, 2,. ., n) and let xi denote the vector of explanatory variables associated with it. Then the conditional distribution of Yi given xi is the logit function was: f Y ðyi ; ujxi Þ ¼

(

f ðxÞ ¼

if yi > 0 Pr ðY i ¼  E 0;  u1 jxi Þ f Y yi ; u2 jxi ; yi 0 Pr ðY i > 0; u1 jxi Þ if yi > 0

ð1Þ

where u ¼ ðu1 ; u2 Þ denotes a pair of the parameter and the parameters in the first and the second parts. To estimate Pr ðY i > 0; u1 jxi Þ for the first part in (1), we choose a logistic regression Pr ðY i > 0; u1 jxi Þ ¼ 1þexp 1u0 x f 1 ig Several specifications have been applied for estimating  E  f Y yi ; u2 jxi ; yi 0 the second part in (1). Given Yi > 0, one might simply assume the standard linear normal model Y i ¼ u0 2 xi þ 2i where 2i are errors and assumed to be independent and identically distributed as a normaldistribution with zero mean and a constant variances .2 3. Results 3.1. Coverage of insurance by socio-economic and demographic characteristics Table 1 presents the distribution of people in different insurance categories by their socio-economic characteristics. The government funded insurance schemes like RSBY, CGHS, ESIS, etc. covered 12.8% of the population in India and other schemes (other than govt funded insurance schemes) cover 2.48 percent population. It was also observed that insurance coverage differed by place of residence and found to be higher in the urban areas (18%) than in rural areas (14%). The study revealed that education was playing an important role in access to health insurance as with the increase in

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

3

Table 1 Percentage Distribution of Insurance coverage by socio-demographic characteristic in India, NSS, 2014. Background Characteristics

Government funded (RSBY, CGHS, ESIS.)

Others

Not covered

Sex Male Female

12.53 13.12

2.56 2.39

84.9 84.49

Place of Residence Rural Urban

13.16 12.03

0.94 6.07

85.9 81.9

Education Illiterate Up to Primary school Up to Intermediate School Graduation and Above

12.79 12.7 12.89 13.16

1.06 1.61 2.94 11.37

86.15 85.7 84.17 75.47

Religion Hindu Non-Hindu

13.37 10.46

2.57 2.10

84.07 87.44

Caste Scheduled tribes Scheduled castes OBC Others

18.24 13.11 13.63 9.51

0.84 0.88 1.96 4.95

80.91 86.01 84.41 85.54

Poverty Level APL BPL

13.63 9.55

2.9 0.8

83.47 89.65

Level of Care Public Private Total%

16.8 15.89 12.82

1.23 4.75 2.48

81.97 79.36 84.70

the level of education the coverage of health insurance also increased. The figures showed that those had graduate or higher education had higher insurance coverage (13.16%) than those who were less educated. One of the striking findings is that among social groups, a higher share of Scheduled Tribes (18.24%) was covered by government health insurance schemes than OBC (13.6%), Others (9.59%) and Scheduled Caste (13.11%). Health insurance schemes could not protect the large BPL population as the coverage was limited to only 9.55% indicating the limited success of the schemes in reaching to the target population. Surprisingly, almost 85% people in India were not protected by any health insurance scheme till 2014. 3.2. Health care utilisation and Out-of-Pocket Expenditure by insurance status This section presents the hospitalisation rate and Out-of-Pocket Expenditure by insurance status. Data presented in Table 2 showed higher hospitalisation rate among insured than uninsured. While hospitalisation rate among insured person on an average was 6.2%, it was 4.6% for uninsured. The pattern of health care utilisation by economic quintile indicates that the hospitalisation rate increases with an increase in economic class irrespective of

insurance status. For instance, for govt. insurance holder while 4% from lowest economic class reporting illness utilised health care services it was 9% for the richer and richest class. It seems health insurance might increase health care accessibility; however, the economic inequality in health care access persists despite insurance coverage. The findings also show that the difference in the hospitalisation rate among the lowest and highest quintile was the most for the people who were enrolled under government insurance schemes. 3.3. Out-of-Pocket Expenditure by type of insurance Table 3 showed the variances in paid OOP expenditure after subtracting any reimbursements. Mean OOP expenditure for hospitalisation was higher for private insurance holder than those covered by public-funded insurance or not covered by any insurance. For instance, the average OOP payment for private/ Table 3 Average OOP Expenditure per Hospitalisation by Choice of provider and by Different Insurance Categories in Last 365 days, NSS, 2014. Schemes

Provider

Mean (Rs.)

% Visiting

Government funded insurance scheme (e.g. RSBY, Arogyasri, CGHS, ESIS, etc.)

Public

3987

47

Private Total

19737 12408

53 100

Others

Public Private Total

7934 20764 18510

18 72 100

Not covered

Public Private Total

5437 24341 15647

46 54 100

Table 2 Inpatient rate by type of health insurance across economic class in India, NSS, 2014. Economic Class

Lowest Second Middle Fourth Highest Total

Insured

Uninsured

Govt.

Others

4 5.7 6 9.0 9.0 6.2

4.4 6.1 6.1 6.6 6.4 6.2

3.8 4.3 4.5 5.7 6.2 4.6

Note: OOP expenditure includes only medical expenses. Costs of care are calculated with weightages.

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

4

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

other insurance holder was Rs.18510 during the last 365 days while it was Rs 12408 for Public funded insurance schemes and Rs.15647 for those who were uninsured. Irrespective of the insurance status, hospitalisation was higher in private health facilities despite high OOPE. Most of the people under publicly funded insurance schemes (RSBY, CGHS, and ESIS), were hospitalised in private health facilities (53%) than public facilities (47%). It was also noticed that the hospitalisation rate in private hospitals was much higher among private insurance holders (72%) as against insurance holders of govt. schemes (18%). The findings suggest the dominance of private providers in the insurance market. The larger dependence on private health care despite high OOPE perhaps could be the results of poor functioning of public health system. As a consequence, high OOPE due to the higher cost of treatment for illness leaves many into impoverishment. Mean OOP expenditure across economic class revealed that irrespective of economic status OOP expenditure was lower for government insurance holder than those not having any of government Insurance schemes. As depicted in Fig. 1 among the poorest (Q1) covered under government insurance scheme, mean OOP was Rs. 674 while it was Rs. 684 for private insurance holders and Rs.766 for uninsured. A similar pattern was observed for other economic groups as well. For instance, richest class (Q5) under Government funded insurance schemes incurred Rs 1759 as OOP expenditure; it was Rs. 2738 for uninsured. It appears that cost of hospitalisation was lower among those covered under government insurance scheme than other categories of insurance. 3.4. Factors affecting the degree of OOP expenditures in India (Twopart model) The two-part model result presents (Table 4) the effect of various socio-economic factors along with health insurance on the probability of incurring OOP expenditure and on the level of expenditure. Our estimation reveals that along with health insurance several socio-economic characteristics such as household economic status, household size, and place residence are significant in explaining the probability of expenditure in the first part. Caste and education do not explain much in determining the probability OOP expenditure. In the second part, except for age, the other covariates significantly influence the average OOP expenditure.

The results reveal that individuals with health insurance (both govt/private) have a lower probability of incurring positive OOP expenditure than uninsured. Further, the level of OOP expenditure was lower for those covered by any insurance than uninsured implying uninsured spends more on health than those were covered by insurance schemes. Household economic status is another important factor determining the probability of OOP expenditure. Both Part-I and II regression demonstrate that the coefficient of wealth quintile is positive and highly significant at 1% level. As expected, individuals belong to the higher economic class have the higher probability of incurring Out-of-Pocket Expenditure due to high capacity to pay. Thus, average OOPE is higher among those belongs to higher economic class than the poorest. The probability of incurring positive OOP is lower for graduate and above, however, with an increase in the level of education amount of OOP also increases. Perhaps the likelihood of falling sick among the educated lowers the probability of OOP spending. Compared to urban, the probability of incurring positive OOP is higher in rural and also the level of OOP is higher in a rural area. Frequent illness in rural areas perhaps increases the OOP expenditure. The average OOP spending was lower in the backward social class and OBC’s than general category. 3.5. Inequality in OOP expenditure by insurance status Economic deprivation has a major impact on access to health services in India, and it is generally found that the poor spend a larger part of their budget share on health as compared to the rich.23,24 With increasing coverage of insurance especially publicly funded schemes, it is crucial to examine how far the insurance schemes are effective in reducing inequality in health expenditure. Table 5 presents the extent of inequality in healthcare expenditure across economic class by insurance status. The results show that irrespective of insurance status, OOP expenditure as a percentage of total household expenditure was lower for households with better income and substantially higher for the poor. For instance, the poorest class (Q1) under Government Insurance scheme incurred around one-fifth (19%) of their household budget for meeting hospitalisation expenditure which was significantly more than the richest (9.4%) Among uninsured belong to poorest quintile, 21% of household expenditure allocated

Fig. 1. Extent of OOP expenditure (Monthly) across economic class by Insurance Status, NSS, 2014.

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx Table 4 Two Part Regression Results for OOP Expenditure, NSS, 2014. Background Age Age Age Square HH Size Caste General1 SC/ST OBC Religion Hindu1 Non-Hindu Education Illiterate1 Below Primary Sch. Intermediate Sch. Graduation & ab. Wealth quintile Lowest1 Second Middle Fourth Highest Insurance status Uninsured Insurance (PFHI) Others illness Sector Rural 1 Urban LR chi2(17) Prob. >Chi2 Pseudo R2 Observation Constant

Part I (Logit Model)

Part II (Linear Model)

0.01 0.00 0.06**

0.00 0.00 0.03***

0.30* 0.14

0.36*** 0.07***

0.49***

0.09***

0.20 0.21 0.73***

0.02 0.22*** 0.59***

0.34 0.72*** 0.76*** 0.39***

0.23*** 0.41*** 0.64*** 0.97***

2.47*** 2.83*** 0.43**

0.34*** 0.31*** 0.18***

0.43*** 431.54 0.0000 0.1414 54727 7.42

0.13*** Prob > F = 0.0000 Adj R-squared = 0.1072 54390 8.33

Note: Significance Level: ***p < 0.01, **p < 0.05, *p < 0, and 1 denotes the reference category.

for inpatient care while the richest class spends 13.5% of their household income. The Gini coefficient for OOP expenditure showed that the expenditure on health care was more skewed indicating a high level of inequality in health care expenditure. It was higher among govt. insurance holder (0.68) followed by others (0.67) and uninsured (0.66). Fig. 2 shows the Lorenz curve for health expenditure by govt and other insurance holder. The Lorenz curve for both govt and other insurance holder fall to the right and below the line of equality reflecting inequality in health expenditure persists irrespective of the type of insurance. Moreover, the distance of the Lorenz curve from the line of equality of the government insurance holders is higher than other (private) insurance holders. This indicates that inequality in health care expenditure is higher among govt insurance holder. Further, to show the difference in expenditure between the two extreme economic class(that is richest and poorest) equity ratio was also Table 5 OOP expenditure as a percentage of household expenditure across economic class by type of insurance in India, NSS, 2014. Economic Class

Government insurance

Other insurance

Uninsured

Poorest(Q1) Poor(Q2) Middle(Q3) Rich(Q4) Richest(Q5) Mean Gini Coefficient Equity Ratio(Q1/Q5)

18.83 14.29 11.66 10.62 9.4 13.4 0.68 2.00

13.3 15 16.9 12.8 8.1 11.1 0.67 1.64

21.2 16.3 13.3 13.1 13.5 16.1 0.66 1.57

Source: Author calculated from 71 st Round National Sample Survey 2014–15.

5

used in adjacent to it.The results show that health expenditure is two times higher for the poorest covered by govt. Insurance schemes than the richest while for other insurance and uninsured, the inequality in health expenditure is 1.6 times. It appears from the inequality measures of health expenditure that the health care expenditure was unequal across the economic classes and the financial burden is more pronounced among the lower economic class. To get more insights about the severity of the burden of OOP, the percentage of people belong to two extreme economic class that is poorest and richest spending more than 75% of their household income on hospitalisation is presented. As depicted in Fig. 3, around one-fourth of the poorest (25.5%) under government insurance schemes spend more than three-fourth (75%) of their budget on medicalisation whereas among the richest 15% people spend more than 75% of the budget on health. This relation holds true for the private insurance holders as well. Among the private insurance holders, while 25% people belonging to poorest quintile spend 3/4th of their income, it was 11% for the richest. Moreover, irrespective of the insurance schemes the poor bear the burden of catastrophic health expenditure much more than the richest quintile. Meeting Out-of-Pocket medical expenses by source of finance also address the financial burden of people. Around 30% individual covered by government Insurance schemes met the health expenses through borrowing while it was 9.2% and 18% for the private insurance holder and uninsured respectively.13 It appears that a significant share of people under govt insurance financed medical expenses through borrowing which is identified in the literature as a distress financing and this would push them further into poverty and deprivation. 4. Discussion In the recent past, the government has taken several measures to improve health outcomes through different policies and programs. Health insurance is one among them to achieve universal health coverage by reducing inequality in health care accessibility. The study found the public-funded insurance schemes had limited success in terms of coverage (15%) and the coverage was disproportionately higher under govt insurance (12.8%). The socioeconomic differential in insurance coverage reveals educated and better off economic class were covered mostly by insurance. The Government funded schemes were poorly implemented in reaching the target group as only 10% people living below the poverty line were under govt. funded insurance schemes. Some factors can be attributed to low enrollment, which includes the cost of enrolment, the mobility of households, no compulsive mandate on the insurance companies to achieve higher enrollment rates, short and inflexible time span of enrollment and lack of oversight by government agencies.19,25 In terms of coverage, the prevalence of government funded insurance scheme was higher among the Scheduled Tribe community compared to another social group. This shows the commitment on the part of the government to reach the backward community in providing health care services.7 The association of health insurance with health care utilisation and OOPE reveals that hospitalisation rate was higher for the insured than the uninsured indicating health insurance increased the access to health services. However, inequality in accessing health care was persisting as access to health care was higher among the higher economic class than the poor. Out-of-pocket spending for hospitalisation shows that those who were not access to public-funded insurance schemes were paying the most on average. One can argue that government insurance schemes are more effective than private insurance schemes in lowering the

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

6

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

Fig. 2. Lorenz curve for Health expenditure by government and Other Insurance Holders. Source: Calculated from 71 st Round National Sample Survey 2014.

Fig. 3. Percentage Individual spending more than 75% of Household budget as OOP, NSS, 2014.

burden of hospitalisation. Looking at the differences in health care expenditure across economic class, it may infer that the lower ability to pay for the poor might restrict their health spending. In this line, studies show that individuals from the poor economic class spend less compared to the better off group, although the health-related loss of income is much higher among the poor.26 A further examination of health care spending for different types of ailment across the economic group will enlighten in this direction. The results of the two-part model confirmed that health insurance both public and private significantly reduced the Out-ofPocket Spending for hospitalisation. This shows insurance schemes are effective in reducing the financial burden of OOPE and the result was in line with many other studies.14,17,27,28,29 The results do suggest that the socially disadvantaged groups benefited from the government-funded insurance schemes in terms of coverage and

level of spending. However, it was also stated that poor and backward community people, in spite of their high health care needs, spent less on it due to their inability or inaccessibility to meet these health expenses.30 The association of the health insurance with health expenditure revealed that vulnerability in meeting health expenditure was higher among the poor than the rich. This challenges the existing insurance programs that why the low-income group does incur a disproportionate share of household expenditure on health despite insurance coverage. One plausible reason could be the limited benefit package in terms of providing services forcing patients to incur high OOP payment for hospitalisation. Evidence on the impact of public-funded insurance schemes especially RSBY on the incidence of OOP has shown that despite covered under insurance scheme and being entitled to the medical packages, the patients

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

treated in empanelled hospitals were asked to meet the expenses of medicine and diagnostics on their own.31,32 In this line studies have argued that due to the moral hazard problems health beahviour of the insurer changes and they tend to behave in riskier way, which results in greater utilisation of health care and hence leading to the increase in the cost of medical care.33,34 Furhter, examining the impact of public funded insurance schemes on health expenditures studies show that while the public insurance programs have minimal cost sharing but limited covered services result in high OOP expenditure.35 Systematic quality assessments and proper monitoring perhaps is a way out to reduce moral hazard. Therefore, these schemes need to be evaluated carefully to identify the problems associated with moral hazard in health insurance. The advantages and methodological limitations was also acknowledged to highlight the strength and weakness of the approach used in the study. The present paper was based on selfreported data on health expenditure and the hospitalisation information based on 12 month recall period, hence estimation of OOP expenditure may not be accurate due to recall bias. Secondly, the study is based on cross-sectional data and the pre-insurance health expenditure of the insurance holder was not captured. In addition our findings are related to hospitalisation expenditure and one must be cautious while generalising the findings to the total health expenditure, including outpatient health expenditure. Inspite these limiatiaons, the study has the advantage as the recent NSS survey captures those enrolled in RSBY to analyse its effectiveness and the findings based on the analysis throws light on further improvement in the existing programs. 5. Conclusion India has one of the highly privatised health care systems, where health care expenditure met largely through OOP payment. To achieve universal health care access and to reduce the financial burden of health expenditure, the government opted for increasing the coverage of prepayment schemes. Nevertheless, increasing coverage of health insurance programs through copayment increases the amount of medical care demanded (moral hazard) and may drive up health expenditure. In view of this, the present study aims to examine the impact of health insurance schemes in reducing OOP and achieving equality in health expenditure. Limited coverage of BPL people under public-funded schemes implies the failure of the scheme to reach a major section of BPL population. The findings of the study show that insurance programs were succeeded to some extent in reducing the OOP spending on hospitalisation, however, the disparity in health expenditure was more pronounced, especially under government funded schemes, and the poorest group spends a major share of their household budget than rich. The inequality in health expenditure thus highlights a regressive nature of health spending which may have a negative implication on accessing health care. Moreover, an increasing coverage of poor under health insurance no doubt protects against health care impoverishment, but mere provision health care does not address the issue of equity as there exists unequal health spending across economic class. The major challenge is to reduce the disproportionate financial burden of the poorest in accessing health services. Thus, analysing the efficiency and equity implication of these schemes in providing financial protection is needed. Though health insurance schemes are already in place, there is a sheer urgency to expand the benefit package of these schemes regarding increasing the coverage of services and financial incentives along with increasing enrollment. Globally, India ranks 112 th position in health care system out of 190 countries indicating huge investment in health care to meet

7

the growing health needs. However, the health care spending in India was 4.2% of GDP, of which public health spending is merely 1.2%, compared to 3 percent in China and 8.3 percent in the United States. Despite the recommendation of health experts to increase the health budget by 2.5 to 3% of GDP, the allocation to health was not much varied in the current budget. The suggested remedy thus poses a great challenge to the state keeping in view of its limited fiscal space. Moreover, the lessons drawn from the study may be relevant to other developing countries which are undergoing similar socioeconomic, demographic transformation and also similar transitions in health care system. Source of support None. Conflict of interest The authors have none to declare. References 1. Arokiasamy P, Guruswamy M, Roy TK, Lhungdim H, Chatterji S, Nandraj S. Health System Performance Assessment-World Health Survey 2003, India. Mumbai: International Institute for Population Sciences; 2006:163–195. 2. Joe W. Distressed financing of household out-of-pocket health care payments in India: incidence and correlates. Health Policy Plan. 2015;30:728–741. 3. Berman P, Ahuja R, Bhandari L. The impoverishing effect of healthcare payments in India: new methodology and findings. Econ Polit Wkly. 2010;14:65–71. 4. Garg CC, Karan AK. Reducing out-of-pocket expenditures to reduce poverty: a disaggregated analysis at rural-urban and state level in India. Health Policy Plan. 2009;24:116–128. 5. Selvaraj S, Karan A. Deepening health insecurity in India: evidence from national sample surveys since 1980. Econ Polit Wkly. 2009;44:55–60. 6. Savitha S, Kiran KB. Health seeking behavior in Karnataka: does micro-health insurance matter. Indian J Commun Med. 2013;38:217–226. 7. Singh P, Kumar V. Insurance coverage under different health schemes in Uttar Pradesh, India. Clin Epidemiol Glob Health. 2017;5:33–39 10.1016/j. cegh.2016.03.002. 8. Pallikadavath S, Foss M, Stones RW. Antenatal care: provision and inequality in rural north India. Soc Sci Med. 2004;59:1147–1158. 9. Roy K, Howard DH. Equity in out-of-pocket payments for hospital care: evidence from India. Health Policy. 2007;80:297–307. 10. Borah BJ. A mixed logit model of health care provider choice: analysis of NSS data for rural India. Health Econ. 2006;15:915–932. 11. Hooda SK. Health insurance, health access and financial risk protection. Econ Polit Wkly. 2015;50:63–72. 12. Selvaraj S, Karan AK. Why publicly-financed health insurance schemes are ineffective in providing financial risk protection. Econ Polit Wkly. 2012;47:61– 68. 13. NSSO. Key indicators of social consumption of health. NSS 71 st round (January– June 2014). New Delhi: National Sample Survey Organization, Ministry of Statistics and Programme Implementation, Government of India; 2015. 14. Ekman B. The impact of health insurance on outpatient utilization and expenditure: evidence from one middle-income country using national household survey data. Health Syst Policy Res. 2007;5:6–19 10.1186/14784505-5-6. 15. De Costa A, Johannson E. By ‘default or design'? The expansion of the private health care sector in Madhya Pradesh, India. Health Policy. 2011;103:283–289. 16. Wagstaff A, Lindelow M. Can insurance increase financial risk? the curious case of health insurance in China. J Health Econ. 2008;27:990–1005. 17. Pal R. Can insurance reduce catastrophic Out-of-Pocket Health Expenditure? 10.2139/ssrn.1181694. 18. Madheswaran S, Sahoo AK. Out-Of-Pocket (OOP) Financial Risk Protection: The Role of Health Insurance. Institute for Social and Economic Change Working Paper. . [(Accessed: 6.02.17) Retrieved from:] http://www.isec.ac.in/WP%20330%20-% 20Amit%20Kumar%20Sahoo_3.pdf. 19. Ghosh S. Publicly-financed health insurance for the poor: understanding RSBY in Maharashtra. Econ Polit Wkly. 2014;49:93–99. 20. Ghosh S, Gupta ND. Targeting and effects of rashtriya swasthya bima yojana on access to care and financial protection. Econ Polit Wkly. 2017;52:61–70. 21. Cameron AC, Trivedi PK. Microeconometrics: Methods and Applications. Cambridge University Press; 2005:230–235. 22. Kogure A. Predicting Health Care Costs by Two-part Model with Sparse Regularization. The World Risk and Insurance Economics Congress. . [(Accessed: 6.02.17.) Retrieved from:] http://www.wriec.net/wp-content/ uploads/2015/07/7D2_Kogure.pdf.

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002

G Model CEGH 182 No. of Pages 8

8

S.R. Mahapatro et al. / Clinical Epidemiology and Global Health xxx (2017) xxx–xxx

23. Leive A, Xu K. Coping with out-of-pocket health payments: empirical evidence from 15 African countries. Bull World Health Org. 2008;86:849–856C. 24. Valtorta NK, Hanratty B. Socioeconomic variation in the financial consequences of ill health for older people with chronic diseases: a systematic review. Maturitas. 2013;74:313–333. 25. Wu Q. What Cause the Low Enrolment Rate and Utilization of Rashtriya Swasthya Bima Yojana: A Qualitative Study in Two Poor Communities in India. (Doctoral Dissertation). Liverpool School of Tropical Medicine; 2012. [(Accessed: 6.02.17.) Retrieved from:] http://www.chsj.org/uploads/1/0/2/1/10215849/ qifei_wus_dissertation_august_2012.pdf. 26. Levesque JF, Haddad S, Narayana D, Fournier P. Affording what's free and paying for choice: comparing the cost of public and private hospitalizations in urban Kerala. Int J Health Plann Manage. 2007;22:159–174. 27. Sahoo AK, Madheswaran S. Socio-economic disparities in health care seeking behaviour, health expenditure and its source of financing in orissa: evidence from NSSO 2004–05. J Health Manag. 2014;16:397–414. 28. Aji B. De Allegri M, Souares A, Sauerborn R: The impact of health insurance programs on out-of-pocket expenditures in Indonesia: an increase or a decrease? Int J Environ Res Public Health. 2013;10:2995–3013.

29. Aryeetey GC, Westeneng J, Spaan E, Jehu-Appiah C, Agyepong IA, Baltussen R. Can health insurance protect against out-of-pocket and catastrophic expenditures and also support poverty reduction? Evidence from Ghana’s National Health Insurance Scheme. Int J Equity Health. 2016;15:116–129. 30. Mukherjee S, Haddad S, Narayana D. Social class related inequalities in household health expenditure and economic burden: evidence from Kerala, south India. Int J Equity Health. 2011;10:1–13. 31. Rent P, Ghosh S. Understanding the ‘Cash-Less’ Nature of Government-Sponsored Health Insurance Schemes: Evidence From Rajiv Gandhi Jeevandayee Aarogya Yojana in Mumbai, 5Sage Open; 2015 [2158244015614607]. 32. Devadasan N, Seshadri T, Trivedi M, Criel B. Promoting universal financial protection: evidence from the rashtriya swasthya bima yojana (RSBY) in gujarat, India. Health Syst Policy Res. 2013;11:29–41. 33. Folland S, Goodman A, Stano M. The Economics of Health and Health Care. 6th ed. New York: Prentice Hall Inc.; 2009. 34. Arrow K. Uncertainty and welfare economics of medical care. Am Econ Rev. 1963;53:941–973. 35. Galbraith AA, Wong ST, Kim SE, Newacheck PW. Out-of-Pocket financial burden for low-income families with children: socioeconomic disparities and effects of insurance. Health Serv Res. 2005;40:1722–1736.

Please cite this article in press as: S.R. Mahapatro, et al., How effective health insurance schemes are in tackling economic burden of healthcare in India, Clin Epidemiol Glob Health (2017), http://dx.doi.org/10.1016/j.cegh.2017.04.002