Open Access

Out-of-pocket expenditure and catastrophic health spending on maternal care in public and private health centres in India: a comparative study of pre and post national health mission period

Health Economics Review20177:31

https://doi.org/10.1186/s13561-017-0167-1

Received: 11 May 2017

Accepted: 7 September 2017

Published: 18 September 2017

Abstract

Background

The National Health Mission (NHM), one of the largest publicly funded maternal health programs worldwide was initiated in 2005 to reduce maternal, neo-natal and infant mortality and out-of-pocket expenditure (OOPE) on maternal care in India. Though evidence suggests improvement in maternal and child health, little is known on the change in OOPE and catastrophic health spending (CHS) since the launch of NHM.

Aim

The aim of this paper is to provide a comprehensive estimate of OOPE and CHS on maternal care by public and private health providers in pre and post NHM periods.

Data and method

The unit data from the 60th and 71st rounds of National Sample Survey (NSS) is used in the analyses. Descriptive statistics is used to understand the differentials in OOPE and CHS. The CHS is estimated based on capacity to pay, derived from household consumption expenditure, the subsistence expenditure (based on state specific poverty line) and household OOPE on maternal care. Data of both rounds are pooled to understand the impact of NHM on OOPE and CHS. The log-linear regression model and the logit regression models adjusted for state fixed effect, clustering and socio-economic and demographic correlates are used in the analyses.

Results

Women availing themselves of ante natal, natal and post natal care (all three maternal care services) from public health centres have increased from 11% in 2004 to 31% by 2014 while that from private health centres had increased from 12% to 20% during the same period. The mean OOPE on all three maternal care services from public health centres was US$60 in pre-NHM and US$86 in post-NHM periods while that from private health center was US$170 and US$300 during the same period. Controlling for socioeconomic and demographic correlates, the OOPE on delivery care from public health center had not shown any significant increase in post NHM period. The OOPE on delivery care in private health center had increased by 5.6 times compared to that from public health centers in pre NHM period. Economic well-being of the households and educational attainment of women is positively and significantly associated with OOPE, linking OOPE and ability to pay. The extent of CHS on all three maternal care from public health centers had declined from 56% in pre NHM period to 29% in post NHM period while that from private health centres had declined from 56% to 47% during the same period. The odds of incurring CHS on institutional delivery in public health centers (OR .03, 95% CI 0.02, 06) and maternal care (OR 0.06, 95% CI 0.04, 0.07) suggest decline in CHS in the post NHM period. Women delivering in private health centres, residing in rural areas and poor households are more likely to face CHS on maternal care.

Conclusion

NHM has been successful in increasing maternal care and reducing the catastrophic health spending in public health centers. Regulating private health centres and continuing cash incentive under NHM is recommended.

Keywords

National Health Mission National Rural Health Mission Maternal care Delivery care Catastrophic health spending Out-of-pocket expenditure India

Background

Reduction of maternal mortality, neonatal and under-five mortality and financial risk protection are three key health related targets of sustainable development goals (SDGs) [1]. Achieving health related SDGs required significant investment in maternal and child health to protect households from high out-of-pocket expenditure (OOPE) and catastrophic health spending (CHS). High OOPE is positively associated with CHS and reduced access to health services, increases untreated morbidity, reduce consumption of goods and services, and lead to long-term impoverishment [2]. The level of CHS varies across countries, among socio-economic groups and by nature and type of health services. Cross country studies suggest that households with low educational attainment, lower economic status, without health insurance and residing in rural areas are more likely to incur CHS [36]. The OOPE and CHS are high for maternal services in many developing countries including India [7, 8].

Estimates of OOPE and CHS on health care are gaining increasing research and programmatic attention. A growing number of studies from developing countries suggest that the health care payment has increased the poverty level and affect the poor most [911]. Globally, OOPE studies on maternal care addressed socioeconomic and demographic differentials and estimated the incidence and correlates of CHS. The general findings suggest higher OOPE for caesarean delivery, complicated delivery, deliveries in private health centres and for higher socioeconomic groups [1216]. The global progress in improvement of maternal and child health and reduction of CHS is contingent on India’s success on these indicators.

Maternal and child health in pre and post NHM periods in India

India with one-sixth of the world’s population, federal nature of governance and sustained economic growth, is undergoing health transition. The healthcare system in the country is characterized by the presence of both public (central, state and local government) and private health care providers, varying delivery structures and multiple systems of medicine [17]. While health is a state subject (within the state government) the central government helps in policy making, planning, guiding, evaluating and providing the funding to implement the national program. The utilization of health services from private health care providers is generally linked to the ability to pay and quality of care.

A decade ago, the state of maternal and child health in India was extremely poor. The maternal mortality ratio (MMR) and the infant mortality rate (IMR) were high. About three-fifths of the mothers were delivering without any medical assistance and women perceived cost as a major barrier to the utilization of maternal care. As a policy response, the Government of India launched the National Rural Health Mission (NRHM) in 2005 to improve the health system by providing universal access to equitable, affordable and quality health care. The NRHM intended to reduce maternal and child mortality and OOPE on maternal care in rural areas of 18 states that had poor health infrastructure and health indicators. Subsequently, the program was extended to all the states and urban areas in the country and renamed as National Health Mission (NHM). The key components of NHM are Janani Suraksha Yojana (JSY) and Janani Shishu Suraksha Karyakram (JSSK). The JSY is a cash incentive scheme provided to mothers for delivering at public health centres or accredited health centers [18]. The incentive to mothers varies in rural and urban areas and in low and high performing states. Besides, it covers the incentive to Accredited Social Health Activist (ASHA). The JSSK, launched in 2011 entitled all pregnant women to deliver in public health institutions absolutely free and free treatment to sick infants up to 1 year. Over ten million pregnant women are provided cash incentives under the scheme annually. Details of the NHM are documented elsewhere [19].

Figure 1 presents the trends in health budget and that of NHM over time at constant prices [1US$ = 65.43]. The NHM accounts for more than half of the health spending of the central government over time. In 2014–15, about US$ 2626 million (Rupees 16,809 crores) were spent on NHM [20]. The recently released National Health Policy, 2017 highlights the success of NHM in the public health system and aim to reduce IMR to 26 per 1000 live births by 2019 and MMR to 100 per 100,000 live births by 2020 [21].
Fig. 1

Trends in annual budget (US$) of Ministry of Health and Family Welfare (MoHFW), Govt. of India and National Health Mission (NHM), 2009–16 (at 2015–16 prices and 2015–16 exchange rate). Source: Kapur A, Srinivas V. Budget Brief 2015-16: National Health Mission Accountability Initiative [Internet]. New Delhi; 2016. Available from: http://www.cprindia.org/research/reports/budget-brief-2017-18-national-health-mission-nhm

Since the implementation of NHM in 2005, there has been significant progress in maternal and child health in the country. Trends in IMR and MMR suggest substantial improvements in the post NHM period; IMR declined from 58 in 2004 to 40 per 1000 live births in 2013 (31% decline in the post NHM period) [22, 23] and MMR declined from 254 in 2004–06 to 167 per 100,000 live births in 2011–13 (34% decline) [24, 25]. Process indicators such as prenatal care, institutional delivery and postnatal care have shown significant progress in India [26]. JSY had a significant impact on increasing antenatal and natal care and reducing perinatal and neo-natal deaths [27]. Several small-scale studies have examined the success and constraints of the program [2831]. Besides improving maternal and child health survival, the NHM was intended to reduce the OOPE and CHS on delivery, prenatal and post natal care. Though a number of studies have examined the differentials and determinants of maternal care [3234], there are limited studies on the economic burden of maternal care over time in India.

The first systematic attempt on estimating OOPE and CHS on maternal care for India suggest high CHS to poor, rural households and the less educated [7]. The OOPE on delivery care varies largely across states and household characteristics [35]. Studies also found that maternal care in India placed a high economic burden on households and suggested reduction in OOPE to benefit the poor [3638].

The aim of this paper is to estimate the OOPE and CHS on maternal care before the launch of the National Health Mission in India and a decade later. It addresses the research question whether the OOPE and CHS on maternal care have declined in the post NHM period? The paper has been conceptualized with the following rationale. First, large-scale investment in the public health programs of developing countries has large opportunity costs. Though there has been significant reduction in maternal and child mortality and increase in maternal care utilization in public health centres in the post NHM period, there is no study that has examined the OOPE by public and private health care providers in the pre and post NHM period. Understanding the level of OOPE in the pre and post NHM periods will help assess the functioning of the program and will be of immense help to multiple stakeholders. Second, both public and private entities in India are providers of maternal care services and are guided by varying principles. Hence, any systematic analyses in understanding the effectiveness of the program should focus on disaggregated analyses by type of provider (public-private). Third, high OOPE on health care is associated with higher CHS and increasing poverty [39, 40]. Studies also suggest that the medical care costs has been rising faster than the overall well-being of the households [41]. Reduction of CHS among the poor and marginalized was one of the main objectives of NHM and analyses on CHS need to be sensitive to account the health spending among the poor.

The paper is organized as follows: Section I gives a brief introduction of NHM and delineates the progress of maternal and child health in the post NHM period, Section II presents data and method, while Section III presents the results and Section IV provides discussion and conclusion.

Methods

Data

The unit data of the 25th Schedule of the 60th and 71st rounds of the National Sample Survey (henceforth referred to as 60th and 71st respectively) is primarily used in the analyses. Both rounds of the surveys are population based nationally representative surveys, similar with respect to design, content and coverage and provide comprehensive information on morbidity, health care and cost of hospitalization. The 60th round was held from January to June 2004 and the 71st round was held from January to June 2014. These time periods were best suited for analyses as 2004 was the pre NHM period and 2014 marked a decade since the implementation of the NHM (post NHM period). No health survey of NSS was conducted between 2004 and 2014. Information on natal care in 2014 was collected as part of hospitalization and missed the cost of deliveries conducted at home. We have created data at the women’s level to compute the OOPE and at the household level to compute CHS. In 2014 sample, there were 236 households that had more than one woman who had availed institutional delivery and there were 96 such households in 2004. On the other hand the CHS is used at household level, derived from household consumption expenditure, subsistence expenditure and household’s OOPE. The 60th round covered a total of 73,868 households and 383,338 individuals and the 71st round covered a total of 65,932 households and 333,104 individuals. The NSS uses a stratified multistage sampling design and samples are drawn from all states and union territories of India. Samples drawn are representative and provide robust estimates at the state level by rural and urban and selected characteristics. The sampling methodology and findings from these surveys are available in the respective reports [42, 43]. Since the expenditure on maternal care is analyzed for 2004 and 2014, we have adjusted the expenditure at 2014 prices for valid comparison using the price deflator for rural (agricultural labourer) and urban areas (industrial worker) and at 2001 base prices [44]. Estimates on OOPE is presented in US$ at the 2014 exchange rate. Besides, in calculating CHS, we have used the state specific poverty line (for subsistence expenditure) for rural and urban areas as recommended by the Planning Commission for 2004–05 and 2011–12 [45]. The poverty estimates are derived from the household consumption expenditure data based on calories intake. The per capita calories intake of 2400 for rural areas and 2100 for urban areas are demarcated as poverty cut-off point in India and make poverty estimates comparable across states of India. The corresponding money value is labeled as poverty line. The poverty estimates in India are usually provided at 5-year interval and the 60th and 71st rounds of NSS (health surveys) are close to that of time period that estimates poverty in India. Mother is the unit of analyses for estimating OOPE while household is the unit of analyses for CHS. The sampling weights are used in the analyses for representativeness of the sample.

Outcome

OOPE and CHS are two outcome variables, computed for delivery care, and maternal care (pre-natal, natal and post-natal) by type of health care provider (public-private). In computing the maternal care from private and public sources, we consider only those women who availed these three services either from the public or private. The OOPE is defined as the expenditure incurred by the women during pre-natal, institutional delivery and post-natal care net of reimbursement. Expenditure on prenatal care, institutional delivery and postnatal care was directly available in the data set and were summed to obtain expenditure on total maternal care. The CHS is defined as the health spending over 40% of household’s capacity to pay. The consumption expenditure data of the household and the state specific poverty line is used in deriving the household’s capacity to pay.

Covariates

Individual and household level covariates are used in the analyses. The household characteristics pertain to the head of the household while individual characteristics pertain to the woman. The selection of covariates is guided by availability of variables in data set and literatures. The covariates included are age, residence (rural/urban), educational level, caste1 (Scheduled Tribe, Scheduled Caste, Other Backward Classes and Others), religion (Hindu, Muslims and Others), monthly per capita consumption expenditure (MPCE) quintile and household type (labourer household and others). We have also introduced an interaction term in the regression model, namely, type of health care provider and time (pre and post NHM) to capture the effect of time and source of provider in explaining change in OOPE and CHS in India.

Analytical methods

Descriptive statistics, estimation of CHS, log linear regression and the logit regression models are used in the analyses. In literature, two alternative approaches are used in estimating CHS, both using capacity to pay (CTP). The approach suggested by Berki (1986) and later by Van Doorslar et al. (2007) defines CHS as a proportion of consumption expenditure (usually 10% and more) [46, 47]. The limitation of this approach is its inability to account for the CHS of poorer sections as the poor spend less on health due to their lower ability to pay. Studies have demonstrated the limitation of this method in the empirical estimation of maternal expenditure [7]. The second approach by Xu et al. (2003) [3] derives CTP by deducting the subsistence expenditure (SE) and is largely used in literatures [48, 49]. It defines CHS;
$$ {\mathrm{CHS}}_{\mathrm{i}}={\mathrm{OOPE}}_{\mathrm{i}}/\Big(\mathrm{X}\mathrm{i}-\mathrm{f}\left(\mathrm{X},\Big)\right)>=\mathrm{z} $$
(1)

Where Xi is the consumption expenditure of ith household and f(X) is the subsistence expenditure of the population. The SE is estimated either using median food expenditure or as poverty line of the specific country/region. Unfortunately, the health surveys in India do not collect detailed consumption expenditure and therefore the food expenditure is not available. In such cases, we have used the state specific poverty line to account for the subsistence expenditure. This approach is sensible where the poor are concerned, as those households below poverty line are classified as incurring CHS if they incurred OOPE for maternal care. The cut-off point of CHS is normative and usually taken as 40% in literature. Thus, a household is said to incur CHS if its health spending exceeds 40% of its capacity to pay.

To understand the impact of NHM on OOPE and CHS, we have pooled the variables of both rounds of health surveys. Two types of regression models are used; a log linear regression model for OOPE and a logit regression model for CHS. The log linear regression model was estimated as OOPE was continuous variable and skewed in nature. The logit model was used as the CHS was dichotomous variable, 0 for not incurring catastrophic health spending and 1 for incurring catastrophic health spending. Both set of models were estimated for delivery care and maternal care. We clustered standard error by first stage sampling unit (village/urban blocks). Each of the regression models were adjusted for state and time (survey-year) fixed effect. The fixed effects are captured at the state level because the states in India exhibit large variation in demographic, social, economic and health parameters. Also, health is a state subject and the state makes policies, programs and implement uniformly across the state. Besides, the state fixed effect model captures the unobserved factors in the regression model.

The regression models used for OOPE is defined as
$$ \ln\ \left({\mathrm{OOPE}}_{\mathrm{i}}\right)=\upalpha +{\upbeta}_1{\mathrm{res}}_{\mathrm{i}}+{\upbeta}_2{\mathrm{age}}_{\mathrm{i}}+{\upbeta}_3{\mathrm{e}\mathrm{duc}}_{\mathrm{i}}+{\upbeta}_4{\mathrm{mpceqt}}_{\mathrm{i}}+{\upbeta}_5{\mathrm{caste}}_{\mathrm{i}}+{\upbeta}_6{\mathrm{religion}}_{\mathrm{i}}+{\upbeta}_7{\mathrm{htype}}_{\mathrm{i}}+{\upbeta}_8\mathrm{INT}\_\mathrm{NHM}\_{\mathrm{SOU}}_{\mathrm{i}}+{\upbeta}_9{\mathrm{state}}_{\mathrm{i}}+{\mathrm{e}}_{\mathrm{i}} $$
(2)
where α is the intercept, res is residence (rural/urban), age is age of the woman, edu is educational level of the mother, mpceqt is monthly per capita consumption expenditure quintile of the household, caste is the caste of the household, religion is religion of the household, htype is the type of household (labourer or non-labourer household). INT_NHM_SOU is the interaction term computed based on time (pre / post NHM) and source of providers (public/private). These are public*preNHM, private*preNHM, public*postNHM and private*post NHM. The interaction term helps to understand the role of NHM in reducing the CHS in public/private health centres. A total of 36 states and union-territories are included in the analyses. The subscript i is used for ith woman.
Similarly, the regression models used for CHS is defined as
$$ \mathrm{logit}\ \left({\uppi}_{\mathrm{i}}\right)=\upalpha +{\upbeta}_1{\mathrm{res}}_{\mathrm{i}}+{\upbeta}_2{\mathrm{age}}_{\mathrm{i}}+{\upbeta}_3{\mathrm{educ}}_{\mathrm{i}}+{\upbeta}_4{\mathrm{mpceqt}}_{\mathrm{i}}+{\upbeta}_5{\mathrm{caste}}_{\mathrm{i}}+{\upbeta}_6{\mathrm{religion}}_{\mathrm{i}}+{\upbeta}_7{\mathrm{htype}}_{\mathrm{i}}+{\upbeta}_8\mathrm{INT}\_\mathrm{NHM}\_{\mathrm{SOU}}_{\mathrm{i}+}{\upbeta}_9{\mathrm{state}}_{\mathrm{i}} $$
(2)
where πi is the probability of incurring catastrophic health spending for delivery/maternal care of ith household. The model estimates the log odds of incurring CHS adjusted for a set of explanatory variables. All explanatory variables are same as of Eq. (1) except age and education. Information on age and education of the head of the household is used, as household is the unit of analyses and there are cases where more than one woman had delivered from the same household. Results are presented with the help of regression coefficients, odds ratio and 95% CI.

Results

The mean age of women was 25.52 years in 2004 and 25.69 years in 2014. In 2004, 52.03% women were illiterate, 43.48% had primary education and 4.49% had secondary and above education. In 2014, 28.58% women were illiterate, 23.24% had primary and 48.18% had secondary and above educated. The MPCE of the household was 1066 rupees in 2004 and 1311 rupees at 2014 prices. About 34.17% households were labourer households in 2004 compared to 28.46% in 2014 (Table not shown). Table 1 presents the definition of variables used and the descriptive statistics. The utilization of maternal care has increased from both public and private health providers and the increase was larger from public health center. On the other hand, the increase in OOPE in private health center is large compared to public health center. The standard deviation of OOPE on all three maternal care in private health center was 240 in 2004 and 455 in 2014 suggesting increasing variation over time. In case of public health center the standard deviation of all three maternal care had declined from 108 in 2004 to 86 in 2014 suggesting reduction in variability in OOPE. The standard deviation for institutional delivery was similar for OOPE.
Table 1

Definitions and descriptive statistics of variables on maternal care in India by source of provider, 2004–15

Variable

Definition

Descriptive statistics

Pre NHM (2004)

Post NHM (2014)

Public

Private

Total

Public

Private

Total

Ante-Natal Care (ANC)

Percentage of mothers who received any of the ante-natal check-ups during pregnancy.

43.34

32.04

75.38

55.13

35.30

90.43

Institutional Delivery

Percentage of mothers who delivered at either public or private health care facility

21.97

22.31

43.28

53.17

29.47

82.64

Post Natal Care (PNC)

Percentage of mothers who availed any post natal services following childbirth.

28.52

35.90

64.42

45.69

33.62

79.31

All three maternal care services

Percentage of mothers who received all of the three maternal care services (ANC, natal care and PNC).

11.32

11.54

31.80

31.22

20.20

66.09

Out-of-Pocket Expenditure (OOPE) on Institutional Delivery in US$

Total expenditure on institutional delivery net of reimbursement (mean)

42

170

56

46

300

138

Out-of-Pocket Expenditure (OOPE) on all three maternal care services in US$

Total expenditure on ANC, natal and post-natal care net of reimbursement (mean)

60

260

170

86

478

239

Prenatal, natal and postnatal care in pre and post NHM periods

Figure 2 presents the extent of prenatal, natal and postnatal care in the pre and post NHM periods by source of provider. The utilization of prenatal care had increased from 75% in 2004 to 90% in 2014. Postnatal care was estimated at 64% in 2004 and 79% in 2014. Among the three maternal care services, the increase in natal care was the highest while the postnatal care was the least during the post NHM period. Women who had availed all three services irrespective of the health care provider accounts 32% in 2004 and 66% in 2014. The pattern was similar for natal and post-natal care. Since 2004, all three maternal care has recorded increase in public health centres. For example, prenatal care from public health centres has increased from 43% in 2004 to 55% in 2014 while that in private health centres has increased from 32% to 35% during the same period. One interesting pattern that emerges is the continuity of maternal care services and decline in switching of services from public health centres in the post NHM period. Among those women who had availed all three services in 2004, 11% availed these services only from public health centres, 12% availed services only from private health centres and 77% switched from public to private or vice versa (Fig. 3). In 2014, among mothers who availed maternal care services, 31% availed only from public health centres, 20% availed only from private health centres and 49% switched services between private and public health centres.
Fig. 2

Percent distribution of women who received pre-natal, natal and post-natal care by public and private health centres during Pre and Post NHM Periods in India

Fig. 3

Percent distribution of women who availed prenatal, natal and postnatal care from public health care providers only, private health care Providers only and switch from public to private and vice versa in pre NHM and post NHM periods in India

OOPE on prenatal, natal and postnatal care in pre and post NRHM periods

Appendix 1 presents the differentials in OOPE on institutional delivery (natal care) and all three maternal care services in 2004 and 2014 by type of health care providers. The OOPE on total maternal care is presented for those who availed all three services either from public or private health centres exclusively, and those who switched between public and private service providers during pregnancy and childbirth. Among women who availed all three services in public health centres, the mean OOPE had increased from US$60 to US $86 (by 43%) while that in private health centres has increased from US$260 to US$ 478 (by 84%). For those who switched services between private and public provider, the OOPE increased by 17%. The mean OOPE on all three services increased with the educational attainment of women and economic well-being of household, irrespective of type of health care providers. The OOPE on institutional delivery had increased from US$ 56 to US$ 138 during the pre and post NHM periods (at 2014 prices). The differentials in OOPE on delivery care in public health centres had increased marginally over time - US$ 42 in the pre NHM period and US$ 46 in the post-NHM period while that from private health centres had increased from US$ 170 in 2004 to US$ 300 in 2014 (by 76%). The differentials in OOPE in natal care in public health centres among women with no education or primary education had declined in the post-NHM period compared to the pre-NHM period, while it increased among those who had secondary, high school education and above. The differentials in OOPE from private health centres by MPCE quintile in the pre and post NRHM periods suggest that the OOPE among the poorest had increased threefold and that among the richest twofold.

Table 2 present result of log-linear regression model of OOPE for institutional delivery and maternal care. Women aged 25 years and above are likely to incur 5% more OOPE on delivery care and all three maternal care ((exp(0.05)-1)). The OOPE on institutional delivery and all three maternal care increases significantly with the economic well-being of the households. Compared to the poorest MPCE quintile, the OOPE on institutional delivery among the richest MPCE quintile was 55% higher (exp(0.44)-1)). The OOPE was higher among women with higher educational attainment and other than labourer households. The OOPE in post NHM period from public health center was 3% lower than that of pre NHM period (not statistically significant). The OOPE for institutional delivery from private health center in post NHM period was 5.62 times higher than that of public health center in pre NHM period. The OOPE for institutional delivery from private health center in post NHM period was even higher than that from private health center in pre NHM period. In post NHM period, the OOPE for all three maternal care from public health center had increased by 32% ((exp(0.28)-1) and statistically significant. In case of private health centers in post NHM period, the increase in OOPE on all three maternal care was about 5.62 times compared to that from public health center in pre NHM period. In general, the pattern on OOPE in maternal care is similar to that of institutional delivery.
Table 2

Regression coefficient and 95% confidence interval of OOPE on institutional delivery and total maternal care during pre and post NHM periods in India

Background characteristics

Institutional delivery

All three maternal care

Coef.

95% CI

Coef.

95% CI

Age of Mother

 < 25 (R)

  25+

0.05

0.02–0.08

0.05

0.01–0.08

Place of Residence

 Rural (R)

  Urban

−0.04

−0.08- -0.00

−0.01

−0.05-.0.03

Education Level

 No Education (R)

  Primary

0.07

0.02–0.12

0.14

0.08–0.21

  Secondary

0.20

0.15–0.26

0.24

0.18–0.31

  Higher secondary +

0.30

0.24–0.36

0.31

0.24–0.38

MPCE Quintile

 Poorest (R)

  Poorer

0.08

0.03–0.14

0.09

0.03–0.15

  Middle

0.16

0.11–0.22

0.16

0.09–0.22

  Higher

0.29

0.24–0.35

0.28

0.22–0.35

  Highest

0.44

0.38–0.50

0.43

0.36–0.49

Caste

 Scheduled Tribe (R)

  Scheduled Caste

0.08

0.00–0.15

0.14

0.05–0.22

  Other Backward Caste

0.13

0.06–0.20

0.20

0.12–0.28

  Others

0.19

0.12–0.26

0.23

0.15–0.31

Religion

 Hindu (R)

  Muslim

−0.02

−0.07-0.03

−0.07

−0.12- -0.01

  Others

0.02

−0.05-0.10

0.04

−0.04-0.11

Household Type

 Other (R)

  Labourer

0.08

0.04–0.12

0.07

0.03–0.12

Interaction effect

 Public*Time (PreNHM) (R)

  Private*Time (PreNHM)

1.43

1.35–1.51

1.52

1.41–1.62

  Public*Time (PostNHM)

−0.03

−1.10-0.03

0.28

0.19–0.37

  Private*Time (PostNHM)

1.89

1.82–1.96

2.02

1.92–2.11

  Constant

7.60

7.43–7.76

8.08

7.91–8.25

(R): Reference Category

Catastrophic health spending in pre and post NHM periods

Table 3 presents the differentials of CHS on maternal care and delivery care by public and private health centres and socio demographic characteristics in the pre and post NHM periods. Among mothers who availed all three maternal care from public health centres, the CHS has declined from 56% in the pre NHM period to 29% in the post NHM period and that from private health centres declined from 56% to 47% during the same period. The decline in CHS was quite substantial among all economic groups (except the poorest MPCE quintile) and all educational groups. The CHS on delivery care in public health centres had declined from 51% in 2004 to 20.5% in 2014 and that in private health centres has declined from 52% to 34% during the same period. Overall, the level of CHS on delivery care has declined from 52% in 2004 to 25% in 2014. The CHS on delivery care and maternal care reduced for many socio-demographic characteristics. The CHS on maternal care and delivery care is negatively associated with the economic status of the household, irrespective of the type of service and time.
Table 3

Percentage of households incurring catastrophic health spending on institutional delivery and all three maternal care by source of provider and selected characteristics during pre NHM (2004) and post NHM (2014) periods in India

Background characteristics

CHS on institutional delivery

CHS on all three maternal care

Public

Private

All

All three care from public health centers only

All three care from private health centers only

2004

2014

2004

2014

2004

2014

2004

2014

2004

2014

Age

  < 30

54.5

20.1

55.2

41.7

54.8

25.7

52.9

30.6

54.7

59.2

 30–59

51.5

21.1

53.7

32.3

52.5

25.1

57.6

29.1

61.4

45.3

 60+

45.4

19

45

33.6

45.3

25.1

56.8

28.3

45.4

43.2

Residence

 Rural

55.3

21.1

61.8

37.2

58.5

25.7

58.9

30.4

68.9

51.5

 Urban

43.1

18

38.3

29.6

40.2

23.9

50.3

24.8

40.6

41.8

Education Level

 No Education

65.1

23.9

68.1

42.6

66.4

28.8

69

33.8

73.6

56.1

 Primary

49.7

21.6

58.9

38.5

53.9

26.9

55.9

31.7

67.6

48.7

 Secondary

31.8

18.1

36

33.2

34.4

23.8

48

24.7

32.6

48.8

 High School+

25.5

8.9

32.8

20.6

30.6

15.5

15.8

16.4

38.8

34.6

Caste

 Scheduled Tribe

59.7

29.7

65.4

23.7

61.4

28.6

51.8

37.5

65.3

28.9

 Scheduled Caste

59.4

22.2

63.8

48.4

61.1

28.3

59.1

33.3

68.4

56.8

 Other Backward Caste

50.9

19.5

59.8

34.5

55.8

25.2

56.8

27.2

67.6

49.4

 Others

42.5

15

38

29.5

39.9

21.6

51.8

24.1

38.9

43.2

Religion

 Hindu

52.1

20.5

51.7

34.8

51.9

25.4

55

29.8

55.6

48.3

 Muslim

53.4

20.6

66.8

34.1

60.5

25.2

66.8

27.8

66.8

44.6

 Others

37.4

20.4

28.8

26.3

32.6

23.1

52.7

26.8

33.3

39.1

Household Type

 Labourer

48.4

26

54.3

48.8

51.7

30.7

56.4

38.7

69.6

57.9

 Others

51.9

18.4

51.5

32

51.7

20.6

55.2

25.7

52.4

46

MPCE Quintile

 Poorest

79.8

62.8

99

90.4

87.6

67.9

76.8

74.6

100

95.8

 Poorer

79.3

7.4

95

57.3

87.3

22.3

80.4

23.5

99.4

68.4

 Middle

68.3

2.3

87

29.4

75.8

11.2

69.5

6.3

95.5

51.8

 Richer

31.6

0.9

48.2

19.2

40.1

8.6

40.7

3.2

61.2

37.8

 Richest

8

0.9

19

8

15.6

5.1

17.8

0.4

25.3

20.7

State

 Non EAG

47.9

16.6

48.5

31.7

48.3

23.3

52.3

24.9

53.9

45.1

 EAG

60.9

23.5

60.1

39

60.4

27.3

68.9

32.7

60.1

51.9

Total/India

51.4

20.5

52.1

34.2

51.7

25.2

56.2

29.4

55.6

47.2

Number of households

1835

8792

1866

5559

3701

14,351

1038

5263

910

4179

There were 38 households in 2014 and 8 households in 2004 where some women availed services in public and others in private health centres

Table 4 presents the odds of incurring CHS on all three maternal care services and institutional delivery. Age of the head of the household is a significant determinant of CHS for institutional delivery and all three maternal care. Urban households are less likely to incur CHS compared to rural households for institutional delivery (OR 0.29, 95% CI 0.26, 0.32) and all three maternal care services (OR 0.27, 95% CI 0.24, 0.31). The educational attainment of head of the household does not show consistent pattern for all three maternal care services. On the other hand, economic gradient is strong, negative and significant suggesting that CHS declines with economic well-being of the household. Type of households is not significant for maternal care services and institutional delivery. Maternal care (all three) in public health center in the post NHM period (OR 0.06, 95% CI 0.04, 0.07) are less probable to be catastrophic compared to public health center in pre NHM period. Similarly, all three maternal care services at private hospitals are significantly more likely to be catastrophic in the post NHM period compared to public health centres in the pre NHM period (OR 1.34, 95% CI 1.08, 1.67). In case of institutional delivery the odds of CHS from public (OR 0.03, 95% CI 0.02, 0.03) and private (OR 0.54, 95% CI 0.46, 0.63) health centers in post NHM period was significantly lower than public health centers in pre NHM period.
Table 4

Odds Ratio and 95% Confidence Interval (CI) of catastrophic spending on institutional delivery and total maternal care expenditure associated with socio-economic and demographic correlates during pre and post NHM periods in India

Background characteristics

Institutional delivery

All three maternal care

Odd ratio

95% CI

Odd ratio

95% CI

Age

  < 30 (R)

  30–59

0.86

0.77–0.97

0.78

0.68–0.89

  60+

0.75

0.64–0.86

0.65

0.56–0.77

Place of Residence

 Rural (R)

  Urban

0.29

0.26–0.32

0.27

0.24–.0.31

Education Level

 No Education (R)

  Primary

0.98

0.87–1.10

1.02

0.89–1.18

  Secondary

1.03

0.91–1.18

1.11

0.96–1.28

  Higher secondary +

1.08

0.92–1.27

1.17

0.98–1.40

MPCE Quintile

 Poorest (R)

  Poorer

0.06

0.05–0.07

0.08

0.07–0.10

  Middle

0.02

0.02–0.03

0.03

0.02–0.04

  Higher

0.01

0.01–0.01

0.01

0.01–0.02

  Highest

0.00

0.00–0.00

0.00

0.00–0.00

Caste

 Scheduled Tribe (R)

  Scheduled Caste

1.00

0.82–1.21

1.14

0.90–1.43

  Other Backward Caste

1.18

0.99–1.42

1.44

1.16–1.78

  Others

1.19

0.99–1.44

1.30

1.04–1.63

Religion

 Hindu (R)

  Muslim

0.88

0.77–1.01

0.77

0.65–0.91

  Others

1.00

0.81–1.23

1.00

0.79–1.26

Household Type

 Other (R)

  Labourer

1.10

0.97–1.15

1.14

0.98–1.33

Interaction effect

 Public*Time (PreNHM) (R)

  Private*Time (PreNHM)

3.48

2.92–4.16

4.97

3.88–6.36

  Public*Time (PostNHM)

0.03

0.02–0.03

0.06

0.04–0.07

  Private*Time (PostNHM)

0.54

0.46–0.63

1.34

1.08–1.67

  Constant

306.61

193.33–486.26

327.92

195.11–551.15

(R): Reference Category

Discussion

The NHM in India was intended to increase the utilization of maternal care, reduce maternal mortality, neo-natal and infant mortality and reduce the OOPE and catastrophic spending on maternal care. Though evidence suggests an increase in the utilization of maternal care services and reduction in maternal and infant mortality in the post NHM period [5052], there is no study that has examined the effectiveness of the program in reducing the OOPE on maternal care. Earlier studies were confined to a point of time or addressed particular services and none of these provided comparable estimates of OOPE in pre and post NHM by public and private health providers [7, 35, 38]. This study provides comprehensive estimates of OOPE and CHS in pre and post NHM periods in public and private health centres. The data set we have used is publicly available and the time period is best suited for analyses.

The salient findings are as follows. First, the OOPE on delivery care in public health centres (unadjusted mean at constant prices) has remained similar during the pre and post NHM periods and increased by 77% during post NHM period in private health centres. The OOPE on institutional delivery in private health centres was nearly four times higher than that in public health center in the pre-NHM period and increased by 6.5 times in the post NHM period. On controlling for socio-economic and demographic confounders and time, the OOPE on institutional delivery from public health center had not shown any significant increase in post NHM period. In case of private health centers, the increase in OOPE for institutional delivery was large and significant. This confirms that the overall increase in OOPE on institutional delivery was largely driven by increase in OOPE in private health centers. The OOPE on institutional delivery increased with educational attainment and MPCE quintile linking high OOPE to ability to pay and quality of care. Second, though, the OOPE on delivery care in public health centres has remained similar in pre and post NHM periods, it has increased significantly for all three maternal care services. The OOPE on all three maternal care in public health centers during post NHM period had increased by 32% (statistically significant) and that in private health centers had increased many fold. -Third, the CHS on delivery care and all maternal care services from public health centres in the post NHM period has declined by almost half. In the case of institutional deliveries, reduction of CHS in public health centres was experienced across all educational and economic classes. The decline in CHS was also noticeable in private health centres. With regard to all three maternal care services, the reduction of CHS was lower compared to that in delivery care but the level remained high. Fourth, the multivariate analyses confirmed decline in CHS in the post NHM period and a larger decline in the share of CHS in public health centres. Households residing in rural areas and with lower economic status are more likely to incur CHS and these findings are consistent with other studies [5, 6, 35, 38]. The interaction of time and NHM suggests that compared to those who delivered in public health centres during pre NHM period, those delivered or availed all there maternal care services in the post NHM period from public health centers were less likely to incur CHS in India. However, in case women availed all three maternal services from private health center in post NHM period, they are more likely to incur CHS.

These findings suggest that the NHM has been successful in increasing deliveries in public health centres and reduced the CHS in India. Increase in continuation of services in public health centres and reduction in switching from public to private healthcare providers is indicative of improvement in public health services on maternal care in India. The decline in OOPE from public health centres for the less educated and poor mothers may be attributed to the JSY under NHM. However, the use of pre-natal and post-natal has not recorded similar increase as that of institutional delivery in the post NHM period. This is possibly because the program priority under JSY was on increasing institutional delivery. The reduction of CHS is a reflection of the success of the program. Decline in CHS may be attributed both to the NHM and improvement in the economic well-being of the households. On the other hand, the differentials in OOPE among public and private health centres are large and there has been overall increase in OOPE on delivery care. This is possible because of increasing incidence of caesarian deliveries across the states of India.

We acknowledge some limitations of the study. First, a time series analyses could not be feasible due to data constraint. The NSS health survey was conducted in interval of 10 years; 2004 and 2014. No health survey of NSS was conducted in intervening period and so the time series analysis is ruled out. Similarly, the difference in difference analyses is not feasible as NHM was implemented in 18 poor performing states for initial few years and then expanded to advanced states. Getting control group may not feasible, as there were large differentials between poor performing and advanced states of India. Second, the analyses could not be performed separately for caesarian deliveries and normal delivery as the type of delivery (normal/caesarian) was not recorded in the survey. Third, the quality of maternal care that is often linked to cost were not collected in the survey and could not be analyzed. The indirect cost on hospitalization has not been estimated. Besides, improvement in health infrastructure in the post NHM period is beyond the scope of the study.

Conclusion

Based on these findings, we conclude that the NHM is effective in increasing in utilization, continuation of services in public health centres and reducing OOPE and CHS in public health centres on maternal care. We suggest that the cash incentive under NHM should continue and private health care providers should be regulated with respect to pricing and quality of care. The program should focus on improving the quality of services in public health centres. Besides, we recommended that the forthcoming health survey (NSS) should integrate an abridged version of the consumption schedule, question on expenditure on home delivery and a separate code for caesarian and normal delivery is recommended.

Footnotes
1

The population of India are generally categorized into four caste groups: Scheduled Tribe (ST); Scheduled Caste (SC); Other Backward Caste (OBC) and others. Conventionally, the ST population are socially and economically the poorest section of the population followed by SC and OBC. Based on this classification, the central. State and local government provides reservation on education, employment and other benefits to ST, SC and OBC population.

 

Abbreviations

ASHA: 

Accredited social health activist

CHS: 

Catastrophic health spending

CTP: 

Capacity to pay

EAG: 

Empowered action group

JSSK: 

Janani Shishu Suraksha Karyakram

JSY: 

Janani Suraksha Yojana

MPCE: 

Monthly per-capita consumption expenditure

NHM: 

National health mission

NRHM: 

National rural health mission

NSS: 

National sample survey

OOPE: 

Out-of pocket expenditure

Pl: 

Poverty line

SDG: 

Sustainable development goals

Declarations

Acknowledgments

Authors would like to thank editor and two anonymous reviewers for their valuable suggestions and comments on earlier version of the paper. Authors thank Dr. Laxmi Kant Dwivedi for his useful suggestion on statistical analyses of the paper.

Funding

Not Applicable.

Availability of data and materials

Data used in this paper is publicly available.

Authors’ contributions

Both authors conceptualised, analysed data, wrote and approved the draft.

Authors’ information

Sanjay K Mohanty is Professor at International Institute for Population Sciences, Mumbai. He has 17 years of teaching and research experience at post-graduate level. He teaches health economics and fertility at IIPS, Mumbai. His research interest includes health financing, multidimensional poverty and economics of ageing.

Anshul Kastor is doctoral student at International Institute for Population Sciences, Mumbai. He is pursuing his doctoral work on “Health financing transition and its linkages with health outcomes in India”.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

All authors declare that they have no competing interest.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Department of Fertility Studies, International Institute for Population Sciences (IIPS)
(2)
Research Scholar, International Institute for Population Sciences

References

  1. United Nations. UN sustainable goals summit 2015. New York City: United Nations; 2015.Google Scholar
  2. Whitehead M, Dahlgren G, Evans T. Equity and health sector reforms: can low-income countries escape the medical poverty trap? Lancet. 2001;358:833–6.View ArticlePubMedGoogle Scholar
  3. Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJ. Household catastrophic health expenditure: a multicounty analysis. Lancet. 2003;362:111–7.View ArticlePubMedGoogle Scholar
  4. Knaul FM, Arreola-Ornelas H, Méndez-Carniado O, Bryson-Cahn C, Barofsky J, Maguire R, Miranda M, Sesma S. Evidence is good for your health system: policy reform to remedy catastrophic and impoverishing health spending in Mexico. Lancet. 2006;368:1828–41.View ArticlePubMedGoogle Scholar
  5. Li Y, Wu Q, Xu L, Legge D, Hao Y, Gao L, Ning N, Wan G. Factors affecting catastrophic health expenditure and impoverishment from medical expenses in China: policy implications of universal health insurance. Bull World Health Organ. 2012;90:664–71.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Arsenijevic J, Pavlova M, Groot W. Measuring the catastrophic and impoverishing effect of household health care spending in Serbia. Soc Sci Med. 2013;78:17–25.View ArticlePubMedGoogle Scholar
  7. Bonu S, Bhushan I, Rani M, Anderson I. Incidence and correlates of “catastrophic” maternal health care expenditure in India. Health Policy Plan. 2009;24:445–56.View ArticlePubMedGoogle Scholar
  8. Chandrasiri J, Anurango C, Wickramasinghe R. The impact of out-of-pocket expenditures on poverty and inequalities in use of maternal and child health services in Bangladesh: evidence from the household income and expenditure surveys 2000–2010. Manila: Asian Development Bank; 2012.Google Scholar
  9. Van Doorslaer E, O'Donnell O, Rannan-Eliya RP, Somanathan A, Adhikari SR, Garg CC, et al. Effect of payments for health care on poverty estimates in 11 countries in Asia: an analysis of household survey data. Lancet. 2006;368(9544):1357–64.View ArticlePubMedGoogle Scholar
  10. 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;24:116–28.View ArticlePubMedGoogle Scholar
  11. Elgazzar H, Raad F, Arfa C, Mataria A, Salti N, Chaaban J, Majbouri M. Who pays. Out-of-pocket health spending and equity implications in the Middle East and North Africa. Washington DC: World Bank; 2010.Google Scholar
  12. Afsana K, Rashid SF. The challenges of meeting rural Bangladeshi women’s needs in delivery care. Reprod Health Matters. 2001;9:79–89.View ArticlePubMedGoogle Scholar
  13. Levin A, Dmytraczenko T, McEuen M, Ssengooba F, Mangani R, Van Dyck G. Costs of maternal health care services in three anglophone African countries. Int J Health Plann Manag. 2003;18:3–22.View ArticleGoogle Scholar
  14. Borghi J, Ensor T, Somanathan A, Lissner C, Mills A. Mobilising financial resources for maternal health. Lancet. 2006;368:1457–65.View ArticlePubMedGoogle Scholar
  15. Perkins M, Brazier E, Themmen E, Bassane B, Diallo D, Mutunga A, et al. Out-of-pocket costs for facility-based maternity care in three African countries. Health Policy Plan. 2009;24:289–300.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Honda A, Randaoharison PG, Matsui M. Affordability of emergency obstetric and neonatal care at public hospitals in Madagascar. Reprod Health Matters. 2011;19:10–20.View ArticlePubMedGoogle Scholar
  17. Wennerholm P, Scheutz AM, Zaveri-Roy Y. India's Healthcare system-overview and quality improvements. Stockholm: Swedish Agency for Growth Policy Analysis; 2013.Google Scholar
  18. MoHFW. National Rural Health Mission (2005–12), mission document. New Delhi: MoHFW; 2005.Google Scholar
  19. MoHFW. Framework for implementation of National Health Mission, 2012–17. New Delhi: MoHFW; 2012.Google Scholar
  20. Kapur A, Srinivas V. Budget brief 2015–16: National Health Mission Accountability Initiative [internet]. New Delhi; 2016. Available from: http://www.cprindia.org/research/reports/budget-brief-2017-18-national-health-mission-nhm.
  21. MoHFW. National Health Policy 2017. New Delhi: Government of India; 2017.Google Scholar
  22. ORGI. Sample registration system, Vol. 41 (1). SRS Bulletin New Delhi; 2006.Google Scholar
  23. ORGI. Sample registration system. SRS Bulletin: New Delhi, Vol. 49 (1); 2014.Google Scholar
  24. ORGI. Special bulletin on maternal mortality in India 2004–06. New Delhi: ORGI; 2009.Google Scholar
  25. [Internet] Available from: http://www.censusindia.gov.in/vital_statistics/mmr_bulletin_2011-13.pdf. [cited 2016 Jul 9].
  26. IIPS. National Family and health survey. 2015–16. State fact sheet [internet]. Mumbai: IIPS; 2016. Available from: http://rchiips.org/NFHS/factsheet_NFHS-4.shtml.
  27. Lim SS, Dandona L, Hoisington JA, James SL, Hogan MC, Gakidou E. India’s Janani Suraksha Yojana, a conditional cash transfer programme to increase births in health facilities: an impact evaluation. Lancet. 2010;375:2009–23.View ArticlePubMedGoogle Scholar
  28. Khan ME, Hazra A, Bhatnagar I. Impact of Janani Suraksha Yojana on selected family health behaviors in rural Uttar Pradesh. J Fam Welf. 2010;56:9–22.Google Scholar
  29. Gupta SK, Pal DK, Tiwari R, Garg R, Shrivastava AK, Sarawagi R, et al. Impact of Janani Suraksha Yojana on institutional delivery rate and maternal morbidity and mortality: an observational study in India. J Health Popul Nutr. 2012;30:464–71. Google Scholar
  30. Carvalho N, Thacker N, Gupta SS, Salomon JA. More evidence on the impact of India’s conditional cash transfer program, Janani Suraksha Yojana: quasi-experimental evaluation of the effects on childhood immunization and other reproductive and child health outcomes. PLoS One. 2014;9:e109311. Public Library of ScienceView ArticlePubMedPubMed CentralGoogle Scholar
  31. Govil D, Purohit N, Gupta SD, Mohanty SK, Xu L, Liu X, et al. Out-of-pocket expenditure on prenatal and natal care post Janani Suraksha Yojana: a case from Rajasthan, India. J Health Popul Nutr. 2016;35:15. Google Scholar
  32. Mohanty SK, Pathak PK. Rich-poor gap in utilization of reproductive and child health services in India, 1992-2005. J Biosoc Sci. 2009;41:381–98.View ArticlePubMedGoogle Scholar
  33. Paul VK, Sachdev HS, Mavalankar D, Ramachandran P, Sankar MJ, Bhandari N, et al. Reproductive health, and child health and nutrition in India: meeting the challenge. Lancet. 2011;377:332–49.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Saradiya M, Aditya S, Rakesh C. Maternity or catastrophe: a study of household expenditure on maternal health care in India. Health (Irvine Calif). 2013;5:109–18. Google Scholar
  35. Mohanty SK, Srivastava A. Out-of-pocket expenditure on institutional delivery in India. Health Policy Plan. 2013;28:247–62.View ArticlePubMedGoogle Scholar
  36. Leone T, James K, Padmadas S. The burden of maternal health care expenditure in India: multilevel analysis of National Data. Matern Child Health J. 2013;17:1622–30. Google Scholar
  37. Modugu HR, Kumar M, Kumar A, Millett C. State and socio-demographic group variation in out-of-pocket expenditure, borrowings and Janani Suraksha Yojana (JSY) programme use for birth deliveries in India. BMC Public Health. 2012;12:1. BioMed CentralView ArticleGoogle Scholar
  38. Goli S, Moradhvai, Rammohan A, Shruti, Pradhan J. High spending on maternity care in India: what are the factors explaining it? PLoS One. 2016;11:e0156437.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Selvaraj S, Karan AK. Deepening health insecurity in India: Evidence from National Sample Surveys since 1980s. Econ Polit Wkly. 2009;44:55–60. Google Scholar
  40. Balarajan Y, Selvaraj S, Subramanian SV. Health care and equity in India. Lancet. 2011;377:505–15.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Mohanty SK, Ladusingh L, Kastor A, Chauhan RK, Bloom DE. Pattern, growth and determinant of household health spending in India, 1993–2012. Aust J Public Health. 2016;2016:1–15.Google Scholar
  42. NSSO. Morbidity, health care and the condition of the aged, Report no. 507 (60/25.0/1). New Delhi: NSSO; 2006.Google Scholar
  43. NSSO. Key indicators of social consumption in India: health 2014, Report no. (71/25.0). New Delhi: NSSO; 2015.Google Scholar
  44. Central Statistical Office (CSO). Ministry of Statistics and Program Implementation. New Delhi: Government of India; 2015.Google Scholar
  45. Planning Commission. Report of the expert group to review the methodology for measurement of poverty. New Delhi: Planning Commission; 2014.Google Scholar
  46. Berki SE. A look at catastrophic medical expenses and the poor. Health Aff. 1986;5:138–45.View ArticleGoogle Scholar
  47. Van Doorslaer E, O’Donnell O, Rannan-Eliya RP, Somanathan A, Adhikari SR, Garg CC, et al. Catastrophic payments for health care in Asia. Health Econ. 2007;16:1159–84.View ArticlePubMedGoogle Scholar
  48. Rashad AS, Sharaf MF. Catastrophic and impoverishing effects of out-of-pocket health expenditure: new evidence from Egypt. Am J Econ. 2015;5:526–33.Google Scholar
  49. Su TT, Kouyaté B, Flessa S. Catastrophic household expenditure for health care in a low-income society: a study from Nouna District. Burkina Faso Bull World Health Organ. 2006;84:21–7.View ArticlePubMedGoogle Scholar
  50. Nair H, Panda R. Quality of maternal healthcare in India: has the National Rural Health Mission made a difference. J Glob Health. 2011;1:79–86.PubMedPubMed CentralGoogle Scholar
  51. Planning Commission. Evaluation study of National Rural Health Mission (NRHM) in 7 states. New Delhi: Government of India; 2011.Google Scholar
  52. Prasad AM, Bhatia S, Agrawal R. The effect of the National Rural Health Mission on health services and outcomes for childbirth in India: a retrospective analysis of survey data. Lancet. 2013;382:11.View ArticleGoogle Scholar

Copyright

© The Author(s). 2017