i

India’s efforts to eradicate infant mortality: Janani Suraksha Yojana. Policy Analysis Exercise as partial fulfilment of requirements for the

Degree of Master in Public Policy.

By Sarah Hauser

PAE Advisor: Prof. Phua Kai Hong

Lee Kuan Yew School of Public Policy

National University of Singapore

April, 2011

ii

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ACKNOWLEDGEMENTS

I would like to thank Professor Phua Kai Hong for his advice and constant

encouragement. I would also like to thank the Indian officials, doctors and nurses

who took the time to answer my questions and who participated in the research. Not

to forget Iftikhar, who, despite having to deal with numerous students was always

very responsive and happy to help, even on weekends.

Lastly I would like to thank Jonathon Flegg for never being short of ideas and for

encouraging me when I felt overwhelmed by thousands of data points.

iv

TABLE OF CONTENTS

Acknowledgements......................................................................................................................... iii

Executive Summary ......................................................................................................................... v

List of Tables .................................................................................................................................. vi

List of Figures ................................................................................................................................ vi

Acronyms ...................................................................................................................................... vii

1. Introduction............................................................................................................................. 1

1.1. Background .................................................................................................................... 1

1.2 Why Conditional Cash Transfers? ................................................................................... 6

1.3. JSY ................................................................................................................................. 8

2. Methodology ......................................................................................................................... 12

2.1 Research Questions ....................................................................................................... 12

2.2 Data .............................................................................................................................. 13

2.3 Quantitative Research ................................................................................................... 14

2.4 Qualitative Analysis ...................................................................................................... 15

3.1. Scope and Limitations ................................................................................................... 16

3. Findings ................................................................................................................................ 18

3.2. Descriptive Statistics ..................................................................................................... 18

3.3. Research Question 1: Effect of JSY on IMR .................................................................. 20

3.2 Research Question 2: Program Intensity and LPS........................................................... 22

3.4. Research Question 3: Targeting, Cost reduction or education? ....................................... 24

3.5. Costs............................................................................................................................. 28

3.6. Interview Findings ........................................................................................................ 28

4. Recommendations ................................................................................................................. 37

4.1. Targeting ...................................................................................................................... 37

4.2. Management ................................................................................................................. 39

4.3. Long term Strategy........................................................................................................ 40

Bibliography .................................................................................................................................. 41

Appendix ....................................................................................................................................... 44

Appendix I ................................................................................................................................. 44

Appendix II ............................................................................................................................... 45

Appendix III .............................................................................................................................. 46

v

EXECUTIVE SUMMARY

This policy analysis exercise (PAE) examines the effect the JSY cash transfer

program has on infant mortality in India. This is a white paper targeted at the Indian

Ministry of Health and Family Welfare.

The Indian Ministry of Health and Family Welfare embarked on a cash transfer

scheme in 2005 in order to tackle the issue of infant mortality in a novel way – by

handing money to mothers who attend antenatal care and give birth in a hospital.

The PAE looks at how much of the decrease in infant mortality over the period from

2006 – 08 can be attributed to this scheme. Using a data from the District Level

Household Survey, the findings from this project show a correlation between

reduced infant mortality and high program uptake on a state level. The data however

also shows that poor states with high infant mortality are not necessarily those that

are being targeted the most. The survey findings indicate the main reason for

mothers do not give birth in a facility is the cost associated with it. This perception

has not changed before and after the program and is an indicator for a mismatch

between perceived and actual costs. A cost analysis shows that doubling the

program would lead to a cost of over 30 billion rupees and a benefit of a reduction in

infant mortality from 52/1000 to 36 to 42/1000. This thus proves to be a very

expensive program, and rather than continuing on the exponential growth path it is

currently on, the focus needs to be targeted on those that really need to be

incentivized to give better care to their infants. The program neglects to incentivize

quality of care, this needs to be rectified. Lastly, long term consequences of this cash

transfer scheme are unclear. A badly targeted scheme could lead to women feeling

entitled to payment upon hospital delivery.

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LIST OF TABLES

Table 1: Infant Mortality - A Country Comparison ........................................................................... 5

Table 2: Cash Transfer in LPS and HPS ........................................................................................... 9

Table 3: Descriptive Statistics ........................................................................................................ 18

Table 4: Beneficiaries, Infant deaths and Maternal deaths ............................................................... 19

Table 5: Program Intensity, Percentage and Absolute Change in IMR (2006 – 2008)....................... 23

Table 6: IMR by State, 2006 - 2008................................................................................................ 25

Table 7: Successful CCT Scheme Framework ................................................................................ 29

Table 8: Differences across states under the JSY program............................................................... 31

Table 9: Monitoring and Evaluation ............................................................................................... 33

Table 10: States by Population ....................................................................................................... 44

Table 11: Program Intensity and per capita income ......................................................................... 46

LIST OF FIGURES

Figure 1: Causes of deaths among children under age five ................................................................ 2

Figure 2: Territory size in proportion of infant deaths in 2002 ........................................................... 4

Figure 3: Absolute reduction in IMR and program intensity ............................................................ 20

Figure 4: Absolute Reduction in IMR and program intensity, excluding small states ....................... 21

Figure 5: Monthly Income (2005/ 06) and program intensity........................................................... 26

Figure 6: Barriers to Hospital Delivery ........................................................................................... 27

Figure 7: Implementation hierarchy at district level down to grass- root level .................................. 34

Figure 8: Program Intensity on IMR, excluding states with population below 1 million ................... 45

vii

ACRONYMS

ANC: Antenatal Care

ANM: Auxiliary Nurse Midwife

ASHA: Accredited Social Health Activist

BPL: Below Poverty Line

CCT: Conditional Cash Transfer

CHC: Community Health Centre

CRORE: One crore is equal to ten million (10,000,000)

DFW: Directorate of Family Welfare

DHM: District Health Mission

DLHS: District Level Household and Facility Survey

FRU: First Referral Unit

GoI: Government of India

HOD: Head of Department

I/C: In Charge

IIPS: International Institute for Population Sciences

IMR: Infant Mortality Rate

JSY: Janani Suraksha Yojana

LAKH: One lakh is equal to one hundred thousand (100,000)

LPS: Low Performing State

MDG: Millennium Development Goal

MMR: Maternal Mortality Ratio

MO: Medical Officer

MoHFW: Ministry of Health and Family Welfare

MS: Medical Superintendent

NMBS: National Maternity Benefit Scheme

NRHM: National Rural Health Mission

OSD: Officer on Special Duty

PHC: Primary Health Centre

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RCH: Reproductive and Child Health

SC: Scheduled Caste

SPSS: Statistical Package for Social Sciences

ST: Scheduled Tribe

TT: Tetanus Toxoid

UNICEF: United Nations Children‘s Fund

UNFPA: United Nations Population Fund

WHO: World Health Organization

1

1. INTRODUCTION

This introductory chapter aims to give the background information necessary to

understand the PAE problem. Infant mortality is an important issue in developing

counties, and is particularly severe in India. Comparing the country to its neighbors

and similar income countries, India is lagging behind. This is the reason the

Government has implemented a number of programs targeted at improving health

indicators. The program analyzed in this PAE is the Janani Suraksha Yojana (JSY)

cash transfer program, which incentivizes pregnant women to go for antenatal

checkups and to have a hospital delivery. The amount of money given varies

between states based on per capita income and equates to approximately one month

worth of average salaries in poor states.

1.1. BACKGROUND

According to the World Health Organization (WHO), in 2008, there were about 8.8

million deaths among children under five years of age, a mortality rate of 65 per

1000 live births. In low-income countries child mortality rates (118 per 1000) were

almost 20 times higher than those in high-income countries (7 per 1000). Infant

mortality, which is defined as deaths among children under one year old, was 45 per

1000 live births globally. They account for 68% of all deaths among children under

five.

As shown Figure 1, the main killers of children under the age of five are neonatal

causes such as preterm births, asphyxia, sepsis, pneumonia and others.

2

Figure 1: Causes of deaths among children under age five

(Source: WHO, 2010)

UNICEF (2004) states reduction of low birthweight forms an important contribution

to the Millennium Development Goal (MDG) for reducing child mortality. Low

birthweight is defined as less than 2,500 g (up to and including 2,499 g)1 and is often

caused by maternal malnutrition. A lack of maternal food intake during pregnancy

has a negative effect on the growth of fetus in utero as it leads to deficiencies of

calories and important micro-nutrients (McCormick, 1985, Black et al., 2008). In

India one in every three children is born as a low birthweight baby, whereas in

Singapore only 8% are (UNICEF, 2004). Literature suggests that low maternal

weight gain during pregnancy increases the chance of low birth weight (Kramer,

1987). Studies (Krasovec and Anderson, 1991; Strauss and Dietz, 1999) show this

effect is stronger for women whose nutritional status is poor before pregnancy and

during the second and third trimesters.

1 In 1976, the 29th World Health Assembly agreed on the following definition: “Low birthweight is a weight at birth

of less than 2,500 g (up to and including 2,499 g) irrespective of gestational age.”

3

A common way to lower mortality risk after birth in developing countries is to

breast-feed the infant. Compared to children who obtain non-breast milk liquid or

solid food during the first six months of life children who are breast-fed have a

higher survival rate(Black et al. 2008). Most cases of infant mortality can be

prevented with the right levels of nutrition, hygiene and fast recognition of

symptoms thus neonatal and also infant mortality are regarded as a sensitive

indicator of the availability, utilisation and effectiveness of health care, and it is

often used for designing and monitoring population and health programmes (The

Tribune, 2002).

Despite improvements in coverage of interventions such as nutrition, immunization,

and prevention and treatment of malaria, coverage of critical interventions such as

oral rehydration therapy for diarrhea and antibiotics for acute respiratory infections

remains inadequate; diarrhea and pneumonia still kill more than 3 million children

under five years old each year (WHO, 2010).

With over one billion people, India faces a number of health challenges. Social

inequities, great variation in accessibility of health care and a shift from rural life to

greater urbanization are only a few of these. Infant Mortality Rate (IMR) in 2005

varied from 14 in Kerala to 76 in Madhya Pradesh with rising intensity of mortality

inequality across the Indian states. There have also been some discernible time

trends in the way the inequality has been growing (Narayana, 2008).

4

Figure 2: Territory size in proportion of infant deaths in 2002

(Source: www.worldmapper.org)

Figure 2 shows the world in proportion of infant deaths worldwide in 2002. On a

national level India accounts for one in four of under-five deaths, one in three of the

poor and one in six of the population in the world. The country has the highest child

death toll in the world: 2.4 million under-five deaths (Black et al., 2003), and infant

deaths account for more than two-thirds of these (Bhalotra, 2007). Historical decline

in childhood mortality rates in today‘s industrialized countries suggests that

important drivers of improved child health are improved nutrition, public health and

medical technological progress (Fogel, 2004; Cutler and Miller, 2005; Cutler et al.,

2006). When comparing infant mortality in India to countries with a similar GDP

per cap (Table1), one realizes that, despite substantial national improvements from

83 infants per 1000 in 1990 to 52 infants in 2008, the country has been lagging

behind countries like Vietnam, the Philippines, the Solomon Islands, and even much

poorer countries such as Laos. Indeed there seems to be the case that both India and

Pakistan have worse health outcomes than similar income countries in other regions.

5

Sri Lanka is a remarkable example of a neighbour with very low – nearly developed

country standard – infant mortality. The main takeaway from Table 1 is that India as

well as Pakistan, can do better in terms of infant health.

Table 1: Infant Mortality - A Country Comparison

Infant Mortality per 1000

Country Nominal GDP per

cap in USD (2008)

1990 1995 2000 2006 2008

Sri Lanka 2,364 23 21 17 15 13

Bhutan 2,042 91 79 68 59 54

Philippines 2,011 42 33 28 27 26

Papua New

Guinea

1,358 67 61 57 54 53

Solomon Islands 1,269 31 31 30 30 30

India 1,176 83 75 68 58 52

Vietnam 1,155 39 33 24 15 12

Pakistan 1,049 101 94 85 76 72

Laos 984 108 82 64 53 48

Cambodia 795 85 86 80 73 69

(Source: IMF and PRB World Population Datasheet)

In response to poor health indicators and a predominantly rural population that is

suffering, India embarked on the National Rural Health Mission (NRHM) in order to

strengthen its health systems. As shown in Table 1 in 2008 infant mortality rate was

53 per 1000 livebirths which in the National Population Policy (2000) and the

NRHM was targeted to be lowered to be less than 30 per 1000.

The NRHM was introduced by the Government of India (GoI) in 2005-06 to provide

health care to the rural population effectively and with special attention focused on

states with poor health outcomes and inadequate public health infrastructure. The

primary focus of the mission is to improve access for rural people, especially women

and children, to equitable and affordable primary health care. The main goals of

NRHM are a reduction in Infant Mortality Rate and Maternal Mortality Ratio

6

(MMR) by promoting new born care, immunization, antenatal care, institutional

delivery and post partum care (IIPS, 2010).

The NRHM relies on community involvement, making rural primary health care

accountable to the local community and giving authority to the District Health

Mission to make decisions regarding drinking water, sanitation, hygiene and

nutrition. The crucial link between the community and the public health system at

the village level is the Accredited Social Health Activist (ASHA), a female health

volunteer, who receives compensation based on their performance for the promotion

of universal immunization, referral and assistance services for Reproductive and

Child Health (RCH), construction of household toilets, and other health care

delivery programs (IIPS, 2010). To promote institutional delivery, the cash incentive

program of Janani Suraksha Yojana (JSY) has been made an integral component of

NRHM.

1.2 WHY CONDITIONAL CASH TRANSFERS?

The Government of India states the move to an extensive use of cash transfer

schemes is a response to two key problems in traditional development, Firstly, the

cost of reaching people through traditional development programs is often very high.

Secondly, those with the greatest needs are not always getting the benefits. The GoI

has rightly assessed these problems in giving development assistance, however cash

transfer programs do not necessarily solve either issue. In fact, JSY itself can be

seen as an expensive program, which does not necessarily succeed in targeting poor

mothers. Also the impact of many development programs is ambiguous. For

example, the absolute number of poor in India has remained the same for the past

three decades (Mahapatra, 2009).

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There are benefits to cash transfer schemes, if they are implemented correctly and

efficiently, that do not necessarily hold for more traditional development programs.

Firstly a cash transfer scheme allows national governments to forge a direct

relationship with poor families, seeking to foster co-responsibility by requiring

families to assume responsibility for the appropriate use of the cash grants

(Rawlings and Rubio, 2005). Cash transfers can be an efficient and flexible way to

avoid price distortions and creation of secondary markets that are often associated

with in-kind transfers.

“Conditional cash transfer programs address both future

poverty, by fostering human capital accumulation among

the young as a means of breaking the intergenerational

cycle of poverty, and current poverty, by providing income

support for smoothing consumption in the short run”

(Rawlings and Rubio, 2005. Pg. 33)

Whether a cash transfer scheme reaches its targets is often reliant on good technical

program design features, including explicit poverty targeting criteria. This can be

based on proxy-means tests, and strong monitoring and evaluation systems

(Rawlings and Rubio, 2005).

Based on the most reviewed cash transfer programs, that include the Progresa in

Mexico, Bolsa Escola in Brazil, Red de Proteccion Social in Nicaragua, and

Subsidio Unico Familiar in Chile (De Janvry and Sadoulet, 2006), theory suggests

that the main channel though which such schemes work is through lowering

economic costs. For example Progresa in Mexico is a cash transfer scheme to pay

poor families to send their children to school, instead of making them work to

subsidize family income.

8

As JSY was initially introduced to reduce maternal mortality, we cannot assume the

money is spent on the child. The benefit of the program to the child should only be

measured in terms of hospital delivery and antenatal care received, not in terms of

what the money was spent on.

1.3. JSY

Janani Suraksha Yojana (JSY) which literally translated from Hindi means

‗Pregnant Women Safety Scheme‘, under the overall umbrella of national Rural

Health Mission was proposed as a way of modifying the National Maternity Benefit

Scheme (NMBS). While the existing scheme is concerned with providing better

nutrition to mothers, the JSY scheme integrates ―cash assistance with antenatal care

during pregnancy, institutional care during delivery and immediate post-partum

period in a health centre by establishing a system of coordinated care by field level

health workers.‖ (JSY Guidelines, 2005).

The overall goal of the scheme is to reduce overall maternal and infant mortality and

to increase institutional deliveries in Below Poverty Line (BPL) families. The target

group are all pregnant women belonging to such BPL households and who are 19

years or older, and the scheme is focused on the first two live births.

Eligibility criteria are differentiated for 10 selected Low-Performing States (LPS),

that were chosen based on poor economic performance indicators, such as low

income per capita (UNPF, 2009). The LPS are Assam, Bihar, Chhattisgarh, Jammu

and Kashmir, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh and

Uttarakhand. In these states all pregnant women delivering in government health

centres are eligible. Poor women, those who are BPL or from a special caste, can

also deliver in accredited private institutions.

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In all other states only pregnant women from BPL households, aged 19 years and

above, delivering in government health or accredited private institutions, are

eligible. Furthermore all SC and ST women of any age, delivering in a government

health centre or general wards of district and state hospitals or accredited private

hospitals. Lastly, cash assistance for institutional delivery would be limited to two

live-births.

The features of the scheme, shown in Table 2, are that LPS get higher cash benefits

than High Performing States.

Table 2: Cash Transfer in LPS and HPS

Category

of States

Rural Area Urban Area

Assistance

Package to

mother

Package

for the

Accredited

Worker

Total Assistance

Package

to mother

Package

for the

Accredited

Worker

Total

LPS 1400 600 2000 1000 200 1200

HPS 700 NIL 700 600 NIL 600

(Source: MoHFW, 2005)

Special assistance is given if complications arise, for example additional payments

are made to cover the cost for a caesarean section and for tubectomy/laparscopy.

The need for quick cash transfer was highlighted by the MoHFW and thus it was

suggested that the disbursing authority would arrange to provide the money of Rs.

5000 to every health worker and authorize him/her to make the payment subject to

the conditions that the beneficiary fulfills all eligibility conditions and has

completed the procedure. This was later changed in some states, as the cash was

10

often given to nurses and midwives, as mothers felt pressured to thank them for their

help. Now the money is given in check form.

Cash assistance is linked to institutional delivery and as an added incentive; cash

assistance is given to both mothers and ASHAs in LPS. The incentive for health

workers should lead to greater involvement in rural communities. Their incentive in

rural areas is approximately equivalent to half the average monthly salary in these

states. The role of the ASHA is to identify pregnant women and, if they are not self

reporting to a health clinic, to report and register them. Furthermore the ASHA is to

assist the woman throughout the pregnancy. This includes assistance in obtaining the

BPL certificate, providing three ANCs, scheduling institutional delivery, assist

receiving two TT injections. After delivery the ASHA is responsible for arranging

an immunization appointment for the infant within the first 10 weeks, registering

birth or death of mother or child, a post natal visit within 7 days of delivery and

finally it is the ASHA‘s duty to teach the mother how to breastfeed within one hour

of delivery and encourage to continue for 3 – 6 months.

The term ―skilled health worker‖ refers to ―an accredited health professional - such

as a midwife, doctor or nurse - who has been educated and trained to proficiency in

the skills needed to manage normal (uncomplicated) pregnancies, childbirth and the

immediate postnatal period, and in the identification, management and referral of

complications in women and newborns‖ (WHO, 2008).

At the district level the District Health Mission (DHM) is responsible for the

implementation of JSY. However the assistance under JSY is part of the overall fund

of the NRHM.

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An important factor that impacts the success of the program is public awareness.

JSY is the largest conditional cash transfer program in the world in terms of

beneficiaries (Lim et al., 2010). Other similar programs have been implemented in

low-income and middle-income countries such as Latin America, Bangladesh,

Indonesia and Nepal to incentivize the use of health services (Attanasio et al., 2005;

Morris et al., 2004; Powel-Jackson et al., 2009; MoHFW Bangladesh, 2007; Govt.

of Nepal, 2005). There is very little evidence to suggest that these programs have

resulted in better health outcomes or if their effects can be generalized across

different settings (Rawlings and Rubio, 2005).

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2. METHODOLOGY

Secondary and primary research was conducted for this PAE. An extensive literature

review was conducted to obtain background information about infant mortality, the

JSY program and analysis that had been carried out on cash transfer programs in

general and on the JSY program specifically.

Primary research was done in two stages. Publicly available District Level

Household Survey data provided the foundation for data analysis to answer whether

JSY had an impact on infant mortality on a state level. It was also used to analyze

the cost and information barriers to mothers that, despite the cash transfer program,

decide not to give birth in hospitals.

Semi-structured interviews with Indian JSY officers and hospital staff were

conducted in order to assess the scheme based on ADB guidelines for successful

cash transfer schemes. The scheme meets some of the criteria of needs assessment of

the target population, the transfers are made on conditional basis, are monitored and

the scheme does have some political support.

2.1 RESEARCH QUESTIONS

The aim of the project is to find out whether the JSY scheme had an impact on the

target population, how it different across the various states. Once these findings are

clear policy recommendations about whether to continue with the scheme and how

to modify it can be made.

1. Has the JSY cash transfer scheme reduced infant mortality?

2. Have Low Performing States benefited from having greater access to the

scheme?

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3. Was the program effective as a cash- transfer scheme of as a tool to educate

mothers?

2.2 DATA

For the quantitative part of this PAE data was sourced from round two and three of

the India District Level Household Survey (DLHS), carried out by the International

Institute for Population Sciences in Mumbai. DLHS are health surveys, asking

participants about maternal and child health, family planning, use of contraceptives

and reproductive health and use of health-care services at the district level.

DLHS was introduced in 1998 in order to monitor the ongoing health and family

welfare programs. The present District Level Household and Facility Survey

(DLHS-3) is third in the series preceded by DLHS-1 in 1998-99 and DLHS-2 in

2002-04. DLHS-3 is one of the largest demographic and health surveys carried out

in India (IIPS, 2010). DLHS-3 additionally provides information related to the

programs under the NRHM, including JSY. Unlike other two rounds in which

currently married women aged 15-44 years were interviewed, DLHS-3 interviewed

ever-married women and unmarried women.

In round two 620107 households were sampled between 2002 and 2004 by use of

multistage stratified sampling. In round three a total of 720320 households, were

sampled between 2007 and 2009 with multistage stratified sampling.

All three rounds include demographic information and socioeconomic

characteristics including asset ownership. It was also noted whether the mother died

during delivery or immediately after and if the most recent pregnancy resulted in a

livebirth, stillbirth, spontaneous or induced abortion.

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One question addressed women who did not give birth in hospitals, asking for the

main barriers to institutional delivery.

2.3 QUANTITATIVE RESEARCH

In order to choose the right methodology, research was conducted on previous

studies analyzing the JSY cash transfer scheme. Lim et al. (2010) find that JSY had

a positive impact on number of hospital deliveries in 2007 – 08. They also find that

overall the program has directly impacted the reduction of maternal and infant

mortality, however it does not reach the poorest and least educated women are not

necessarily those who benefit the most. Despite using the same dataset as I have for

this research, Lim et al. (2010) estimate much higher program intensity – between 5

and 44%. This has been critiqued by Das et al. (2011) as the question in the survey

is worded as follows: ―Did you receive any government financial assistance for

delivery care under the Janani Suraksha Yojana (JSY)/State specific Scheme‖? This

question is not only ambiguous, Das et al. (2011) also argue that a positive answer

to this question was obtained from many women who last delivered babies in 2004

and 2005, which was 2 years before the JSY scheme became operational. JSY was

announced in April, 2005, yet separate budgetary allocations took place until April,

2006 and uptake and expenditure only started in FY 2007–08 (MoHFW, 2010).

I thus used estimated program intensity based on mothers, who had given birth to

either one or two children, and whether they received JSY at all during this period.

This is likely to give a lower estimate, as mothers who received JSY for two

children, will only be counted once. This methodology was used as a response to

critique Lim et al. (2010) received, and also because it gives a better estimate of the

15

population covered, rather than being driven by single individuals receiving the

benefits twice.

The methodology used in this paper is correlation between program intensity, based

on the criteria outlined above and reduction in infant mortality on a state level. For

this only DLHS-3 data was used.

A before and after comparison was conducted in order to answer the question about

barriers to hospital delivery. In this case responses to the same question in DLHS-2

and DLHS-3 are being compared. This was done on a national level, as there were

some changes in states between the two rounds, thus a state by state before and after

comparison would have given a distorted result.

2.4 QUALITATIVE ANALYSIS

The qualitative analysis consisted of semi- structured interviews with a JSY state

nodal officer, doctors and nurses and a hospital visit to a Delhi hospital. The main

aim of the interviews and the hospital visit was to tease out whether the program

corresponds with the ADB (2008) guidelines for a successful cash transfer program.

The interview was thus focused on gathering information about whether the GoI had

correctly assessed the needs of the population, their current institutional capacity and

key constraints to low outcomes in human capital. The second criterion was to find

out if conditionality was linked to actual needs, and whether monitoring of

operations and evaluation are were being carried out. Lastly, and less importantly so

for this program, the interviews aimed at teasing out whether political and financial

support is available, and whether it flows through from top – level to grass roots, or

whether bottlenecks can be identified.

16

The hospital visit was carried out on an ad hoc basis; it thus did not give hospital

staff the time to prepare for the visit. This was beneficial, as it conveys a less biased

picture of reality. Apart from the nodal officer, neither doctors nor nurses were

informed about the visit. This was important as they could not prepare for questions,

thus their real knowledge about the JSY scheme and about the monitoring process

could be revealed.

3.1. SCOPE AND LIMITATIONS

The scope of this PAE is to assess whether cash transfer, and economic incentive, is

an efficient way to improve the infant mortality rate in India. The PAE touches on

some of the barriers to hospital delivery and analyzes the effectiveness of the

scheme based on management guidelines. Further research is needed to analyze the

epidemiological effect of the program as this PAE only establishes a link between

the program and reduced infant mortality, due to lack of data, it was not possible to

find out the main epidemiological drivers of this decrease in disease.

One of the major limitations to this PAE is that it is heavily reliant on DLHS data, as

there is no other household level data available to the researcher at this point, the

quality of the data is unclear. All major research published on the effectiveness of

the scheme has been based on DLHS data, and thus there is no balanced evidence to

rely on.

Due to time and resource limitation this study focuses only on differences on the

state level. In order to get a better understanding of the conditions that drive JSY

uptake, differences between urban and rural regions should be investigated.

17

Another limitation is the reliance of the study on correlations. The correlation

between program intensity and infant mortality does give a good first indication

about program effectiveness, but in order to get a clearer understanding of the causal

links, more sophisticated econometric techniques should be used for data analysis.

Te qualitative analysis was based on a small number of interviews and should be

extended by targeted interviews in LPS to better understand the barriers to hospital

delivery in these states.

Lastly, this study does not go deeper into what cultural factors, such as differences

in religion or caste, but in order to gain a holistic view of the problem and to form

balanced policies, this is an important factor that should be explored in further study.

18

3. FINDINGS

This section presents the findings from the quantitative and, qualitative analysis. The

main statistical analysis was done by finding correlations between program intensity

and absolute change in IMR. Depending on inclusion or exclusion on states that I

identified as outliers the correlations suggest there is a 1/1000 reduction in IMR with

every 6 – 10% increase in program intensity. Furthermore findings on perceptions of

barriers to hospital delivery are presented in Figure 6. Findings from qualitative

research are presented in Section 3.6. Broadly, the JSY scheme seems to correspond

to the ADB guidelines, however issues have been discovered in targeting, long- term

vision and incentive structure.

3.2. DESCRIPTIVE STATISTICS

Table 3: Descriptive Statistics

Descriptive Statistics

DLHS 2 DLHS 3

no. of households actually interviewed 620107 720320

beneficiaries in last one year-JSY - 20562

heard about program-JSY - 26987

Table 3 shows the number of households interviewed in survey rounds, the amount

of beneficiaries, who received cash under the JSY scheme at least once between

2007 and 2009 and the number of people who are aware about the program.

19

Table 4: Beneficiaries, Infant deaths and Maternal deaths

The correlations in Table 4 show a positive correlation between JSY beneficiaries

and number of infant deaths during last year, number of new born deaths, and

number of maternal deaths. This does not imply that because of the JSY program

such increases occur, but it suggests that JSY beneficiaries have worse health

outcomes than the average Indian population.

Correlations

Beneficiaries -

JSY

Number of

infant deaths

during last year

Number of new

born deaths

during last year

Number of

maternal deaths,

during last year

Beneficiaries - JSY Pearson

Correlation

1 .075** .070** .065**

Sig. (2-

tailed)

.000 .000 .002

N 17479 17086 17125 2281

Number of infant

deaths during last

year

Pearson

Correlation

.075** 1 .728** .237**

Sig. (2-

tailed)

.000

.000 .000

N 17086 17601 17552 2329

Number of new born

deaths during last

year

Pearson

Correlation

.070** .728** 1 .207**

Sig. (2-

tailed)

.000 .000

.000

N 17125 17552 17641 2339

Number of maternal

deaths, during last

year

Pearson

Correlation

.065** .237** .207** 1

Sig. (2-

tailed)

.002 .000 .000

N 2281 2329 2339 2355

**. Correlation is significant at the 0.01 level (2-tailed).

20

3.3. RESEARCH QUESTION 1: EFFECT OF JSY ON IMR

In order to establish whether there is an effect of JSY on IMR, we need to assess

whether the two are correlated.

Figure 3: Absolute reduction in IMR and program intensity

Figure 3, including all Indian states, apart from the outlier Mizoram, shows IMR is

negatively correlated with program intensity. It suggests that a 10% increase in

program intensity is correlated with a 1/1000 reduction in IMR. As this is a simple

correlation, the effect is likely to be underestimated. The results are also likely to be

driven by outliers as the effects by small states are given the same weight as large

states. Figure 4 thus estimates the effect of JSY on reduction in IMR based on large

states. The findings are that a 6% increase in program intensity is correlated with a

1/1000 IMR reduction.

y = -10.976x - 1.4076R² = 0.0832

-10

-8

-6

-4

-2

0

2

4

6

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Absolute Change in Infant

Mortality

Program Intensity

Absolute IMR Change

absolute IMR change Linear (absolute IMR change)

21

Figure 4: Absolute Reduction in IMR and program intensity, excluding small states

Small states are defined as states that have less than 0.99% of India‘s total

population, based on 2003 census figures. Information about these states can be

found in Appendix I. Excluding states that were below 0.99% of the population was

chosen because of its relatively high explanatory power (R2

= 0.3317), alternative

definitions, and the correlations with IMR can be found in Appendix II.

These correlations give a positive answer to the first research question: Program

intensity and infant mortality are correlated. An inverse relationship was to be

expected, as the program has been very successful in terms of uptake, growing to 9.5

million beneficiaries in 2009/10.

Interesting is the size of the magnitude. These correlations suggest that a 6 - 10%

increase in program intensity will lead to a 1/1000 drop in IMR rate. We can thus

suggest the program is effective, in order to make recommendations one must

however look at how costly this program is, which will be done in Section 3.5.

y = -6.2807x - 2.7116R² = 0.3317-7

-6

-5

-4

-3

-2

-1

0

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Reduction in Infant Mortality

Program Intensity

Absolute Reduction in Infant Mortality (excluding small states)

Absolute IMR Change Linear (Absolute IMR Change)

22

3.2 RESEARCH QUESTION 2: PROGRAM INTENSITY AND LPS

Research Question 2 is concerned with program targeting. To find out whether the

poor, defined as LPS, receive most of the benefits, program intensity was analyzed

on a state level basis.

Table 5 shows the level of program intensity by state, as well as the absolute

reduction of IMR of the period from 2006 – 2008. Shaded cells represent Low

Performing States.

23

Table 5: Program Intensity, Percentage and Absolute Change in IMR (2006 – 2008)

State Program

Intensity

Percentage IMR

Change

Absolute IMR

Change

Madhya Pradesh 26.09% -5.4% -4

Mizoram 23.58% 48.0% 12

Orissa 23.03% -5.5% -4

Tamil Nadu 23.02% -16.2% -6

Sikkim 21.75% 0.0% 0

Rajasthan 20.95% -6.0% -4

Andhra Pradesh 20.80% -7.1% -4

Assam 18.83% -4.5% -3

West Bengal 12.41% -7.9% -3

Karnataka 12.25% -6.3% -3

Kerala 10.97% -20.0% -3

Pondicherry 10.48% -10.7% -3

Tripura 9.79% -5.6% -2

Gujarat 7.91% -5.7% -3

Uttarakhand 7.61% 2.3% 1

Maharashtra 7.13% -5.7% -2

Chhattisgarh 7.08% -6.6% -4

Bihar 6.89% -6.7% -4

Arunachal Pradesh 5.76% -20.0% -8

Andaman &

Nicobar Islands 5.09% 0.0% 0

Himachal Pradesh 5.02% -12.0% -6

Manipur 4.99% 27.3% 3

Dadra & Nagar

Haveli 4.17% -2.9% -1

Haryana 4.01% -5.3% -3

Uttar Pradesh 3.49% -5.6% -4

Lakshadweep 3.02% 24.0% 6

Delhi 2.62% -5.4% -2

Meghalaya 2.59% 9.4% 5

Jharkhand 2.43% -6.1% -3

Punjab 2.41% -6.8% -3

Jammu & Kashmir 2.30% -5.8% -3

Goa 1.98% -33.3% -5

Daman & Diu 1.95% 10.7% 3

Chandigarh 1.01% 21.7% 5

Some of the most program intensive states, like Madhya Pradesh with 26.09% and

some of the least intense states like Jammu and Kashmir with 2.30% are considered

24

Low Performing States. There does not seem to be a correlation between program

intensity and being a Low Performing State.

In practice this means that targeting currently aimed at these states with poor health

outcomes is not working. In LPS all mothers above the age of 19 are eligible to

receive JSY, yet in some states as little as 2.30% are beneficiaries. This finding

suggests that monetary incentives may not be enough for some of these states to

break down cultural barriers or a lack of knowledge about the importance of ante-

natal check-ups and hospital delivery. Further research should be undertaken on low

intensity, Low Performing States in order to find out the specific barriers. These

should then be targeted, not necessarily with a greater cash incentive, but by

addressing cultural barriers to hospital delivery. Kumar et al. (2008) find in a

randomized trial in Uttar Pradesh that neonatal mortality can be reduced

significantly by teaching mothers targeted safe care practices such as wiping the

infant after delivery, initiation of skin-to-skin care within 24 hours, and covering the

baby after birth and during massage.

3.4. RESEARCH QUESTION 3: TARGETING, COST REDUCTION

OR EDUCATION?

Research Question 3 is concerned with the barriers to effective targeting. The

findings of the research suggest that the poor do not necessarily benefit the most

from cash transfers. This question is trying to tease out some of the reasons for this.

The firstly this section addresses the targeting of the poor, concluding that GoI has

not selected LPS based on low health indicators, but based on low economic

indicators. Secondly barriers to hospital delivery are investigated, focusing on costs

and information.

25

The selection of LPS correlates with high initial infant mortality rates in 2006 (Table

6). Shaded cells represent LPS states, which are also amongst the states with highest

infant mortality. However it is not a perfect match.

Table 6 is important because it shows clearly that targeting was not done based on

high infant mortality, and it can thus be concluded that the GoI is not addressing the

problem in the most effective way.

Table 6: IMR by State, 2006 - 2008

Infant Mortality Rate

State 2006 2007 2008

Madhya Pradesh 74 72 70

Orissa 73 71 69

Uttar Pradesh 71 69 67

Assam 67 66 64

Rajasthan 67 65 63

Chhattisgarh 61 59 57

Bihar 60 58 56

Haryana 57 55 54

Andhra Pradesh 56 54 52

Meghalaya 53 56 58

Gujarat 53 52 50

Jammu & Kashmir 52 51 49

Himachal Pradesh 50 47 44

Jharkhand 49 48 46

Karnataka 48 47 45

Punjab 44 43 41

Uttarakhand 43 48 44

Arunachal Pradesh 40 37 32

LPS were instead picked based on the lowest monthly income, as shown in

Appendix III.

One recommendation is thus to re-classify Low Performing States as those that are

low performing on various health indicators, such as high IMR, MMR and access to

26

health centers, rather than on low income. The GoI has to keep in mind that that the

goal of this program is to reduce infant and maternal mortality rather than to

increase income.

Despite the poorest states not necessarily being the most program intensive. Figure 5

shows a strong correlation between low income and higher program intensity.

Figure 5: Monthly Income (2005/ 06) and program intensity

This finding suggests that a cash transfer of 1400 rupees, which in most low income

states is roughly a one month salary, does seem to make an impact on the decision to

give birth in a hospital. It is however important to note that in the poorest state,

Bihar, where the cash transfer is greater than two months worth of salary, still has

very low program intensity. This leads to the conclusion that a greater relative cash

transfer is an important incentive to get mothers to deliver in a hospital, cash alone,

however is not enough. It is thus important to look at other barriers to antenatal care

and hospital delivery.

y = -6926.4x + 3215R² = 0.1526

0

2000

4000

6000

8000

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Monthly income in rupees

Program Intensity

Monthly per capita income

Monthly per capita income Linear (Monthly per capita income)

27

Figure 6: Barriers to Hospital Delivery

The main reasons for mothers not accessing hospital care when giving birth, which

are:

- Cost of delivery.

- Access: in rural areas distance to health clinics is often greater than 10km.

- Social: In India traditionally female in-laws and low Dais, who are

community, unskilled birth assistants who help mothers during pregnancy

and at the time of delivery. The family does not always allow a non-

traditional delivery method.

- Transportation: especially if hospitals or health centers are far, the poor can‘t

afford transport to the hospital

- Quality of care is often questioned. Within an extended family or village the

information about low quality care or bad treatment travels fast. This

variable is made up from perceptions of the patients, and also of an actual

lack of care quality. Also unfriendly low-skilled staff is often reason for

women not to return.

0%5%

10%15%20%25%30%35%

Why did you not seek to deliver your child in a hospital?

2002-04 Survey 2007-09 Survey

28

- Education: Often women aren‘t aware of the importance of ante-natal check-

ups, the presence of qualified staff during delivery

Among non users the program has failed to reduce the perceived overall costs

involved in having a pregnancy in a hospital (Figure 6). The information barrier to

hospital pregnancy has dropped dramatically. This is a crucial finding, suggesting

that the economic incentive hypothesis of cash transfer schemes does not seem to

hold for some people. Mothers that still do not give birth in hospitals because of

high costs either see the benefit of JSY as being too small, or are not aware about the

availability of the benefit.

3.5. COSTS

The amount of JSY beneficiaries has risen from 750,000 mothers in 2005 to 9.4

million in 2009/2010. Total costs amount to 15.4 billion rupees, which is an

estimated amount of 1620 rupees per beneficiary.

According to the findings, if the scheme was doubled, infant mortality could be

reduced to 36 – 43/10000 at a cost of over 30 billion rupees. This is not only a very

large sum of money; it is not addressing the real issues: the inefficiencies in the

system and the cultural barriers that are yet to be targeted in the very poor states.

3.6. INTERVIEW FINDINGS

Interviews with government officials, in charge of provincial management of the

JSY program, as well as with doctors and a field trip to a hospital in Delhi were

scheduled in order to assess whether the program meets the criteria outlined by the

Asian Development Bank (2008) for successful CCT projects.

29

(i) Assessment of the current level of human capital outcomes and

identification of key constraints to low outcomes in human capital;

(ii) Conditionality is a key aspect that is necessary but not automatically

sufficient increase human capital outcomes significantly;

(iii) Rigorous monitoring of operations and evaluation are essential to ensure

effectiveness of the program;

(iv) Political support and good governance at all levels for the program play

an important role in the successful implementation of a CCT program.

Table 7: Successful CCT Scheme Framework

Needs

Assessment

Conditionality Monitoring and

Evaluation

Political

Support

MMR

IMR

Assessment in human capital outcomes by the GoI is problematic. Despite being

aware of both IMR and MMR, the main problem is that Indian officials do not seem

to be clear about what their main target in human capital improvement is. Official

documents state JSY is a cash transfer program in order to reduce MMR and IMR.

During the interviews it was however conveyed that the original reason for the start

of the program was high MMR in India which was at 523 per 100,000 in 1990, and

has since reduced to 254 in 2008. The stated goal is to reduce it to less than 100 by

2012. Reduction of infant mortality seemed to be somewhat of an afterthought and

thus no specific targets were put in place for that measure. However the Government

does measure progress made in that category.

30

Both hospital staff, and nodal officer interviewed were aware of the main barriers to

access to hospital delivery, which are cost, access and transportation, education,

customs and quality of care.

The cost barrier is addressed by informing mothers about the availability of JSY and

by the actual cash transfer. The access and transportation issue is responded to by

the GoI by providing free transport to and from the hospital for women in labor.

Auxiliary Nurse Midwives (ANM) are dispatched to periphery postings, to areas

where MMR is particularly high to educate the population on the importance of

antenatal care and a safe birth. This is done to break down some of the educational

and cultural barriers.

In summary the GoI has identified the main problems associated with hospital

delivery and is addressing the issues with targeted policies. The effectiveness and

actual occurrence of some of the policies cannot be evaluated here. It is for example

questionable if mothers really receive free transport to the health facility, given

capacity constraints and ambulance availability.

Lastly, the target put in place by the GoI, of achieving a maternal mortality rate of

less than 100 by 2012 is not realistic, as the 1990 – 2008 annual rate of reduction

was 3.5%. India would have to achieve a 60% reduction in less than 5 years in order

to achieve the target. (Statistics: IHME, 2008) The Government thus needs to re-

assess its goals and put in place more realistic measures that it can than actually

work towards achieving.

Conditionality of the cash transfer program is also problematic. In Delhi, for

example, women receive Rs 600, if they attend the requested number of screening at

the health center or hospital and give birth in an accredited institution. They receive

31

Rs 500 if they give birth at home. Thus the difference of Rs 100 (around SGD 2.8) is

hardly going to be a big enough incentive for women to give birth at the hospital.

The rationale behind this action is that women, who give birth at home, are attended

by an accredited health worker, and that they also get the education and information

about the JSY scheme. In low income states the difference between these two

amounts increases. Also the total amount of cash given to the mother is bigger if she

gives birth at the hospital, thus it can be assumed the incentive will be bigger in

those states where it is needed the most. As seen in the quantitative analysis, cash

transfer may not be enough of an incentive in states with low education and high

cultural barriers. The GoI thus needs to implement innovative solutions that

incorporate traditional methods with safe delivery.

The vast differences between states in terms of benefits and conditionality pose a

major problem to evaluating the scheme on a nation-wide level.

Table 8: Differences across states under the JSY program

LPS HPS

Chattisgarh Orissa Karnataka Maharashtra

Eligibility

Criteria

All women if they

deliver at home or

in public

facilities.

In private

facilities, only

poor women

qualify

All women

who deliver at

home or in

public

facilities

Only poor

women and

only for the

first two

deliveries

Poor women or

women of

scheduled caste

Proof and

Forms

No proof if the

woman delivers in

a government

facility. BPL card

and discharge

summary for

private hospitals

ANC and JSY

form

Income

certificate

ANC and

JSY form

A photo of

the parents

and the baby

BPL card, Proof

of residence,

ANC check- up

details, proof of

age, discharge

summary , JSY

form

(Adapted from Devadasan et al., 2008)

32

Table 8 gives a snapshot of the different criteria and forms of proof required in

different states. A more lenient system of checks could lead to an inflated number of

beneficiaries, in the state. This could be due to mothers in border towns and villages

traveling to the closest hospital, which may be in the neighboring state or it may be

due to misrepresentation, for example of the number of children. Especially

problematic is the inclusion of mothers in the cash transfer scheme that deliver at

home. Despite the reasoning being that these mothers are still reached through

education, this may not always be the case. The ASHA, who receives money based

on every mother she includes in the scheme, has an incentive to include as many

women in JSY as possible, whether they actually receive antenatal care and

information about aftercare or not, is questionable.

There are two policies the GoI needs to put in place to rectify this; firstly, all LPS

and all HPS should have the same eligibility criteria within their groups. Mothers

who do not give birth in health facilities need to either be excluded from the scheme

or the incentive for the ASHA needs to be tied more closely to antenatal care and

informational sessions with the mother, than to delivery itself. This is however very

problematic to monitor, thus the first solution is more realistic. Secondly, regular

checks on whether the forms have been filled out truthfully need to be carried out.

Monitoring and Evaluation is being carried out rigorously. Reporting occurs on a

monthly, annual and quarterly basis, on various levels as shown in the table below.

33

Table 9: Monitoring and Evaluation

In addition the Senior Chief Medical Officer of the Directorate of Family Welfare

(DFW) is monitoring the scheme in the field from State. Chief District Medical

Officer/ Nodal District Officer, JSY is monitoring at the District Level.

Strict registers are being kept at the hospitals about the number of pregnant women

who are eligible for the JSY cash benefit and the number of actual hand-outs. This

register is also being used to forecast. The biggest incentive to lie is on the hospital

and possibly on the state level, however as payment has been switched from a cash –

payment to a check it has been made more difficult for the hospital to misuse the

money. On the state level, it is also being flagged if a hospital predicts birth-rates

that vary greatly from the persisting trend. Thus the checks are there, at different

levels. The states have some incentive to inflate their birth numbers, however as the

BPL card is issued by a department, other than the health department, it is difficult

for them to artificially increase the number of the beneficiates in a state.

Monthly

From Hospital to Chief District

Medical Officer

From Chief District Medical Officer to

OSD RCH

Quarterly

From Chief District Medical officer to

OSD RCH

From OSD RCH to Ministry of Health &

Family Welfare, Govt. of India

Annual

OSD RCH to Ministry of Health & Family Welfare,

Govt. of India

34

Figure 7: Implementation hierarchy at district level down to grass- root level

(Source: JSY State Nodal Officer, Delhi)

The process of funds flow, as shown in the diagram above starts at the Government

of India central level; there it is being given to the State Health Departments who

predict the amount of funds needed based on hospital and district forecasts. Then

money is distributed from the Officer on Special Duty (OSD) RCH to Chief District

Medical Officer and from there to Medical Superintendent (MS) of the Hospital to

Head of the Department, from there on to Gynecology & Obstetrics. There it is

given to the beneficiary in check form by either the RCH Medical Officer or the

RCH Auxiliary Nurse Midwife.

Chief District Medical Officer

Medical Superintendent

(MS)

HOD Gynae

RCH Medical Officer

RCH ANM

Beneficiary

Medical Officer in Charge - Maternity

Home MDC

RCH ANM

Beneficiary

MO I/C Dispensary

RCH ANM

Beneficiary

35

Once the money is disbursed from the chief medical officer, it goes through various

stages until it reaches the mother. Bottlenecks such as signatories of checks have

been identified and are being addressed on a rolling basis. Of the total amount of

money given to the state, 7% of the fund released to the state is utilized for

administration and monitoring. Out of that 4% is used for the district authorities, 1%

for the state and 2% for the Nodal Ministry at the GoI level.

To ensure sustainability and legitimacy of the scheme political support at the top is

needed. The cash transfer scheme, as part of the NRHM and in place since 2005 has

the necessary political backing from the central government, and the funding in

order to be successful. Some funding is made available to the Indian Government by

the World Bank, IMF, DfID, and other aid organizations. It is thus in India‘s interest

to demonstrate the success of the program to ensure long-term funding. Also, India

is placing great importance of health education, which is visible around the country.

Evidence of support for the scheme at the highest level was demonstrated by an

address of the President of India Smt. Pratibha Devisingh Patil, to the Parliament on

21. February 2011.

“During the last five years, my government has […]

approved the appointment of more than 53,500 health

workers in the health sub- centers in 235 districts

considered extremely deficient in respect of health

services. The coverage of beneficiaries of Janani Suraksha

Yojana has increased from around six lakh [600,000] in

2005-06 to nearly one crore in 2009-10. The benefits are

already getting reflected in a decline in infant mortality

rates.”

(President of India, 2011)

36

Cash transfer schemes for the poor are very popular politically, however due to

some bottlenecks they receive some criticism in the Indian media. Main criticism

has been received for difficulty in obtaining or renewing BPL Certificate by

beneficiary as they are being handed out by a different ministry. Reluctance on part

of Medical Superintendent of Central Government Hospital in taking money from

Chief District Medical Officer has been observed.

These are legitimate critiques, which to some extent have been addressed since the

start of the program in 2005.

37

4. RECOMMENDATIONS

The findings suggest that an increase in program intensity is correlated with some

reduction in IMR, they also outline, that by just increasing the program and not by

improving its efficiency, will become a very costly policy. In order to achieve the

stated goal of 80 per cent institutional deliveries, more capacity in the health systems

must be created to meet the needs of the JSY-induced demand. This section will

cover three main suggestions to the GoI: The first recommendation regards better

selection of low performing states. Currently these are chosen based on economic

indicators, the government should redefine LPS based on high infant mortality and

health indicators instead. More research is needed to identify the barriers of hospital

delivery in LPS states with low program intensity, then these can be targeted with

programs specific to those problem states. This section also highlights the need for

improved efficiency in the management of the program and concludes with

recommendations for the long term. Due to the high costs the program is not

sustainable in the long run, the GoI needs to set a timeframe and needs to ensure that

in the long run only those mothers benefit, that could not otherwise afford to give

birth in a hospital.

4.1. TARGETING

There are two key issues concerning targeting of the scheme, firstly Low Performing

States were selected on a low income per capita basis, which does not correlate with

the highest amount of infant mortality in all cases. Thus some states that should be

receiving more attention, such as Haryana, Andhra Pradesh and Meghalaya, with

IMR rates well above 50/1000, are not being targeted due to relatively higher

income. I recommend reviewing the initial selection criteria and target states based

38

on a number of health indicators, including MMR, IMR and neonatal mortality.

Secondly, the findings show that LPS does not necessarily correlate with high

program intensity. It is therefore key to increase hospital delivery in those LPS with

low program intensity. Further research is required on a state level to find out the

reasons for an LPS state having low program intensity. Based on the case of Bihar,

where the cash incentive is over twice the average person‘s monthly income, we can

assume that the bottleneck to hospital delivery is either of cultural or institutional

nature. Policy should thus address this, either via education or by ensuring mothers,

who go to the hospital, actually do receive quality care, and the cash transfer they

are entitled to. Free transport to health centers is one option to ensure mothers gain

access; this can however be costly on the government and is likely to be putting

serious constraints on ambulance capacity.

Secondly, further research should establish why IMR decreased with hospital

delivery, and thus the scheme can incentivize the most effective hospital practices.

The study findings indicate that neither incentives for the mother nor the health

workers are uniform across the country. The different definitions of whether a

household belongs to the BPL category can lead to distorting behavior across,

especially near state borders. The optimum engagement of ASHAs is yet to be

achieved. There are variations across the state in disbursement of payment to them

and there is a need to have uniform charter of performance-based reimbursement

prominently displayed for ASHAs.

39

4.2. MANAGEMENT

My findings are in line with previous studies (UNPFA, 2009), suggesting that JSY

management needs strengthening. This will include preparing JSY plans (facility,

district and state) based on available data, periodic monitoring of functioning of all

the components of the scheme, developing sound communication activity plan for

community mobilization and strong financial planning and monitoring. In addition,

enhancing quality of care is an important area which needs to be focused. Currently

there is no incentive for health workers to deliver quality of care in either ante-natal

visits or during hospital delivery. It is also not clear whether in any given health

facility doctors were ready and equipped to manage obstetric complications. Das et

al. (2011) argue the facilities‘ ability to provide safe delivery services and quick

referrals for emergency obstetric care is crucial to achieve lower IMR and MMR. In

some states with the highest number or MMR, the data shows that although most

primary health centers are open 24 h per day, only few had referral systems to higher

levels of care or newborn care services. The ability to do caesarean sections and

blood transfusion are paramount to prevent maternal and infant mortality (Das et al.,

2011).

This issue can be addressed by closer monitoring of hospital staff, or by changing

the incentive structure. The other dimension to this issue is patient perception of

hospital care. The findings show that a considerable number of patients believe they

can get better care at home or that hospitals can‘t deliver on quality. This issue can,

and should only be addressed after improvements in the health sector have been

made.

40

4.3. LONG TERM STRATEGY

Long term consequences of this program are unclear. The government is trying to

achieve a target of low infant mortality, with an immensely costly program. In the

short term it is certainly adequate to continue with JSY but as mentioned above, to

improve its efficiency. In the long run, the scheme, if continued, needs to be very

targeted, and be based on means testing, in order to contain costs. It is uncertain

whether women will continue going to the hospital when they don‘t get a cash

transfer anymore, or whether they feel they should be paid to give birth at the

hospital. To avoid this, the educating aspect of JSY is of great importance. Women

should go to antenatal check-ups and give birth in hospitals because they understand

it will reduce the risk of complications, and will increase the likelihood of the baby

surviving, not because they receive a check at the end.

In conclusion, the scheme should be continued but improvements in the efficiency

need to be made. In the medium term attention needs to be addressed to states with

high infant and maternal mortality, rather than low income states. A long-term

continuation and further expansion of the cash transfer scheme at a current rate is

not feasible due to high costs. Long term, the strategy needs to shift to a more

selective approach in terms of cash assistance. Cultural barriers and gaps in

education about infant care also need to be overcome, in order to achieve an infant

mortality rate that resembles more the one of a developed country, rather than a

developing one.

41

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44

APPENDIX

APPENDIX I

Indian States by population.

Table 10: States by Population

State Population % of Population

Lakshadweep 60,650 0.01%

Daman and Diu 158,204 0.02%

Dadra and Nagar Haveli 220,490 0.02%

Andaman and Nicobar Islands 356,152 0.03%

Sikkim 540,851 0.05%

Mizoram 888,573 0.09%

Chandigarh 900,635 0.09%

Puducherry 974,345 0.09%

Arunachal Pradesh 1,097,968 0.11%

Goa 1,347,668 0.13%

Nagaland 1,990,036 0.19%

Manipur 2,166,788 0.21%

Meghalaya 2,318,822 0.23%

Tripura 3,199,203 0.31%

Himachal Pradesh 6,077,900 0.59%

Uttarakhand 8,489,349 0.83%

Jammu and Kashmir 10,143,700 0.99%

Delhi 13,850,507 1.35%

Chhattisgarh 20,833,803 2.03%

Haryana 21,144,564 2.06%

Punjab 24,358,999 2.37%

Assam 26,655,528 2.59%

Jharkhand 26,945,829 2.62%

Kerala 31,841,374 3.10%

Orissa 36,804,660 3.58%

Gujarat 50,671,017 4.93%

Karnataka 52,850,562 5.14%

Rajasthan 56,507,188 5.49%

Madhya Pradesh 60,348,023 5.87%

Tamil Nadu 62,405,679 6.07%

Andhra Pradesh 82,210,007 7.41%

West Bengal 90,176,197 7.79%

Bihar 102,998,509 8.07%

Maharashtra 110,878,627 9.42%

Uttar Pradesh 193,977,661 16.16%

India 1,206,610,328 100.00%

45

APPENDIX II

Figure 8 shows the effect of Program Intensity on IMR excluding small states,

defined as states with population of less than 1 million people. The results are in line

with the correlations between IMR and all states and IMR and above 1% states,

though the explanatory power (R2 = 0.0718) is lower due to the inclusion of some

outliers.

Figure 8: Program Intensity on IMR, excluding states with population below 1 million

y = -9.2422x - 2.0645R² = 0.0718

-10

-5

0

5

10

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Absolute Change in IMR

Program Intensity

Absolute IMR change (excluding states with population < 1 mio)

absolute IMR change Linear (absolute IMR change)

46

APPENDIX III

Table 11: Program Intensity and per capita income

State Program Intensity

Monthly per capita

income

Bihar 6.89% 656

Uttar Pradesh 3.49% 1105

Madhya Pradesh 26.09% 1304

Orissa 23.03% 1359

Rajasthan 20.95% 1489

Assam 18.83% 1550

Jammu & Kashmir 2.30% 1553

Jharkhand 2.43% 1589

Chhattisgarh 7.08% 1679

Manipur 4.99% 1694

Mizoram 23.58% 1868

Meghalaya 2.59% 1952

Arunachal Pradesh 5.76% 1982

Uttarakhand 7.61% 2049

Tripura 9.79% 2059

West Bengal 12.41% 2102

Andhra Pradesh 20.80% 2184

Sikkim 21.75% 2201

Karnataka 12.25% 2274

Tamil nadu 23.02% 2497

Kerala 10.97% 2556

Himachal Pradesh 5.02% 2817

Gujarat 7.91% 2846

Andaman & Nicobar Islands 5.09% 2904

Punjab 2.41% 3063

Maharashtra 7.13% 3090

Haryana 4.01% 3236

Pondicherry 10.48% 4040

Delhi 2.62% 5140

Goa 1.98% 5843

Chandigarh 1.01% 7219

Dadra & Nagar Haveli 4.17% N/A

Daman & Diu 1.95% N/A

Lakshadweep 3.02% N/A