Government financing of health care in India since 2005 ... · Government Financing of Health Care...

2017

Government financing of health care in India since 2005: What was achieved, what was not, and why?

Peter Berman, Manjiri Bhawalkar, Rajesh Jha

A report of the Resource Tracking and Management Project

Harvard T.H. Chan School of Public Health

Boston, MA, USA

February 2017

Government Financing of Health Care in India since 2005: What was achieved, what was not, and why?

Table of contents

Acknowledgement ........................................................................................................................................................ III

Abbreviations .................................................................................................................................................................IV

List of figures ...................................................................................................................................................................V

List of tables ...................................................................................................................................................................VI

1. Background ...................................................................................................................................................................1

2. About the study ..........................................................................................................................................................2

2.1 Objectives and scope .................................................................................................................................................. 2

2.2 Methodology ................................................................................................................................................................. 2

2.3 Assumptions and interpretation ...............................................................................................................................3

2.4 Limitations ........................................................................................................................................................................3

2.5 Data sources ..................................................................................................................................................................4

3. The context ..................................................................................................................................................................5

3.1 Experiences of the previous decade: 2005 – 2014 ........................................................................................... 5

3.2 New government – new objectives ........................................................................................................................7

3.3 Changes in central transfers – now through Treasury instead of State Health Society ..................... 8

4. Study results .............................................................................................................................................................. 11

4.1 Resource mobilization and allocation .................................................................................................................... 11

4.2 Total government health expenditure .................................................................................................................. 13

4.3 Utilization of health budgets.................................................................................................................................... 19

4.4 An analysis of “reliability” of health budgets (treasury route) ....................................................................25

4.5 Primary care expenditure in 16 states – levels and trends over time ......................................................28

1. Primary care expenditure trends: inter-state overview ..........................................................................28

2. Central support for primary care: stimulation or substitution .............................................................. 31

5. Conclusion and policy implications .....................................................................................................................35

Annex 1 Total government health expenditure ................................................................................................37

Annex 2 NHM as a share of TGHE ......................................................................................................................38

Annex 3 Variable description ...............................................................................................................................39

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


AcknowledgementIII

Acknowledgement

This study would not have been possible without the support of the National Health Mission (NHM), Government of India and

the Bill and Melinda Gates Foundation. The authors are very grateful to the erstwhile NHM Director, Ms Anuradha Gupta for

initial policy relevant discussions that helped design the study questions. This study is financed by the Gates Foundation learning

grant – Resource Tracking and Management/India. The authors acknowledge the Senior Program Officer, Dr. Hong Wang, for

his unrelenting support and technical input. The authors are also grateful to the support from experts at the Foundation’s

India Country Office, including, Sandhya Rao, Dr. Rajeev Ahuja, and Dr. Jack Langenbrunner for their India relevant policy

advise. The authors are indebted to the Joint Secretary, Health, Mr Manoj Jhalani at the NHM for his invaluable insights and

contributions and particularly his finance team headed by Under-secretary Ms. Kavita Singh who provided the data. The study

benefited from research and statistical support from Ms. Emily Gao and Dr. Diana Bowser.

IV


Abbreviations

Abbreviations

BMSIC Bihar Medical Services Infrastructure Corporation

CHC Community Health Center

CRM Common Review Mission (of NHM)

EAG Empowered Action Group

FMR Financial Management Report (of NHM)

GDP Gross Domestic Product

GoI Government of India

GSDP Gross State Domestic Product

HLEG High Level Expert Group

MFP Mission Flexi Pool (under NHM)

NE North Eastern (states)

NHM National Health Mission

NHSRC National Health Systems Resource Center

NRHM National Rural Health Mission

PHC Primary Health Center

PWD Public Works Department

RBI Reserve Bank of India

RSBY Rashtriya Swasthya Bima Yojana

RTM Resource Tracking and Management

SHS State Health Society

SHSB State Health Society, Bihar

TGHE Total Government Health Expenditure

UHC Universal Health Coverage

UP Uttar Pradesh

V


List of Figures

List of figures

Figure 1: Resource tracking and management framework ...............................................................................2

Figure 2: Delays in transfer of payments (tranches) to the Health Societies by state treasuries ......9

Figure 3: Health care financing timeline ............................................................................................................... 10

Figure 4: State’s own tax to GSDP ratio: 2013-14 .................................................................................................11

Figure 5: Total government health expenditure (nominal) by groups of states .......................................14

Figure 6: Distribution of states’ Total Government Health Expenditure as a proportion of GSDP ....14

Figure 7: NHM as a share of TGHE across state categories ..........................................................................15

Figure 8: NHM as a share of TGHE in 2013-14 by state....................................................................................16

Figure 9: Central portion of NHM expenditure as a share of GSDP ............................................................ 17

Figure 10: Per capita total government expenditure on health in 2013-14: nominal and real ............. 17

Figure 11: Per Capita TGHE (real) growth rate ......................................................................................................18

Figure 12: Average (2005-06 to 2013-14) utilization rate of treasury budgets for health .................... 20

Figure 13: Average (2007-08 to 2014-15) utilization rate of NHM budgets for health .......................... 20

Figure 14: Impact of State Health Society utilization on the TGHE ............................................................. 22

Figure 15: Budget shares & utilization by program components: Bihar & UP ......................................... 22

Figure 16: Utilization rates of MFP budget lines for NHM in Bihar .............................................................. 23

Figure 17: Aggregate expenditure outturn score (2011-14) .............................................................................. 26

Figure 18: Trends in reliability of health budgets through treasury ............................................................ 26

Figure 19: Trends in reliability of health budgets (treasury) in EAG States & Assam.............................27

Figure 20: Level of per capita GPHCE in 2013-14 .......................................................................................................... 29

Figure 21: Trend of GPHCE per capita .................................................................................................................. 29

Figure 22: Primary care as a share of TGHE: 2013-14 .................................................................................... 30

Figure 23: Declining shares of primary care expenditure as a percent of TGHE ................................. 30

Figure 24: Cumulative growth in GPHCE & TGHE between 2005-06 and 2013-2014 ..........................31

VI


List of Tables

List of tables

Table 1: Budget support for central departments of MoHFW in the 11th

(2007-12) & 12th (2012-15) Plan projections ................................................................................................. 6

Table 2: Proportion of total state budget allocated to health over 3 years .................................................. 12

Table 3: Per capita TGHE across state categories (Nominal & Real) in Rs. ................................................... 18

Table 4: Utilization rates under NHM in Bihar .......................................................................................................... 21

Table 5: Utilization rates under NHM in UP .............................................................................................................. 21

Table 6: Quarter wise distribution of MFP funds transferred to UP districts .................................................. 24

Table 7: Treasury budget credibility scoring chart ................................................................................................. 25

Table 8: Number of states with improving & declining budget credibility ...................................................... 27

Table 9: Regression results: substitution (all states) .............................................................................................. 33

Table 10: Regression results: substitution (rich and poor states) ....................................................................... 33

1


Background

Government Financing of Health Care in India since 2005:

What was achieved, what was not, and why?

Resource Tracking for Health

29 states, India

1. Background

Improvement in the health of a country’s population, providing financial risk protection and citizen satisfaction are the three goals of health systems (Roberts et al., 2003). The availability of good quality and relevant data and evidence on the resources allocated and used to finance and deliver health services is important for developing and implementing strategies to meet those goals (Powell-Jackson et al, 2007). Systematic health resource tracking can contribute to this effort.

The government health sector in India has been on a reform path since 2005, with substantial infusion of central government funds under the National Rural Health Mission (NRHM), which in 2013-14 became the National Health Mission (NHM). NHM embodied significant reforms to the financing relationship between the center and states as well as the ways in which government funds for health were managed and used. Other noteworthy initiatives during this period include financial protection programs for health through the launch at national level of the Rashtriya Swasthya Bima Yojana (RSBY), health insurance program and a number of state level government health insurance programs. These schemes introduced a demand-side purchasing approach to public financing while embracing several innovative features in the Indian context and represented a new of way of doing business for government in terms of financing and delivery of health services in which money follows the patient. These government-sponsored schemes have become industry pioneers on at least three fronts. The first is the use of package rates to contain costs. The typical itemized fee-for-service payments used in the private sector tend to induce cost escalation. Second, they have introduced a number of IT solutions on a mass scale including the biometric enrolment, electronic preauthorization, on-line claims and payment processes, and monitoring field functionaries through video surveillance. Finally, the standard packages combined with IT innovations have resulted in timelier provider payment than their private insurance counterparts. (La Forgia et al., 2012)

Since the middle of 2014, the new Bharatiya Janata Party (BJP) led National Democratic Alliance (NDA) government is introducing other public finance reforms like increased tax devolution to the states following the 14th Finance Commission recommendations. These changes reduce direct central support to social sectors, but increase the states’ share in the central tax revenue. This allows states greater autonomy in budgeting but puts greater responsibility on them to set priorities such as those for social sectors like health. Another noteworthy change is the advancing of the union budget presentation and approval timeline by about four weeks to February of each fiscal year. This is intended to reduce delays in initial release of funds each fiscal year by enabling implementation from the very first month of a financial year (starting in April 2017)1. This is expected to improve fund utilization and reduce unspent budgets. The NDA government launched a new National Health Policy (NHP) in 2017 with a goal toward ensuring Universal Health Coverage (UHC).

This study compiles evidence on central and state resources for health, their trends, expenditure patterns and utilization and contributes some new analysis of major systemic issues that inhibit better outcomes from public funding for health.

1http://finance.indiaeveryday.in/news-cabinet-to-consider-union-budget-presentation-on-february-1-1023-2671265.htm

2


About the study

2. About the study

2.1 Objectives and scope

The Resource Tracking and Management (RTM) Project at Harvard T.H. Chan School of Public Health helps improve understanding of the financing of primary health care in Ethiopia and India and its effects on health system performance. This project was funded by a grant from the Bill and Melinda Gates Foundation. The project provides the opportunity for learning from the experience of 29 states in India, with a specific focus on more in-depth learning from Uttar Pradesh and Bihar. The project began with an initial rapid assessment (Berman et al, 2013) and consultations with India’s Ministry of Health and Family Welfare and the Gates Foundation’s India Office. It was decided that grant activities would focus on the following questions: what is the total resource envelope for health across 29 states and the resource envelope for primary health care in 16 sampled states. Project investigations also included a deeper dive into Uttar Pradesh and Bihar to track overall government budget allocations for health and primary health care and their utilization. The project also examined whether the allocation of public resources for primary care activities is well aligned with resources needed; whether there is adequate utilization of the budgeted/allocated funds; whether primary care spending is purchasing the right mix of inputs to assure delivery of maximum outputs; and what is the relationship between funds and physical inputs and program outputs.

The study used the Resource Tracking and Management (RTM) project framework presented in Figure 1 below.

Figure 1: Resource Tracking and Management Framework

ResourceMobilization

ResourceAllocation

ResourceUtilization

ResourceProductivity

ResourceTargeting

What are the determinants of total resource envelope for health at national and sub-national levels?

How are funds allocated to different programs and functions at national and sub-national levels? What factors determine the allocation to primary care?

Are the allocated funds being utilized? What factors drive successful budget execution? What are the existing bottlenecks?

How effectively are resources being translated into services? What are the effects on volume and quality?

Are inputs benefiting the intended individuals and population? Is public spending reaching the poor?

This report focuses on the first three components of the framework: mobilization, allocation and utilization including understanding if central support to states for primary care has a substitution effect on states’ own allocation to primary care. Other project reports provide the results of more in-depth work in Uttar Pradesh and Bihar.

2.2 Methodology

The study was primarily based on secondary data (budgets, allocations and expenditures, outputs). The scope of this report is limited to public sector financing at the state level (29 states) in India, and does not include private sector or household expenditures on health.

Budget and expenditure data were analyzed for nine years (from financial year 2005-06 to 2013-14). This includes

3


About the study

central and state government financing through the budget (the “treasury” route) and funds channeled from central and state sources through the “society” route. The treasury route utilized the usual public financial management process for Indian government expenditures. The society route passes government funds to government-linked societies which are not subject to all the usual government financial management rules and processes. This mechanism was employed to reduce bottlenecks to effective public spending.

Analysis was undertaken at three different levels:

a. Aggregate budget and expenditure analysis for all 29 states.

b. Detailed analysis to look at primary care expenditure in 16 of these 29 states. These 16 states included seven of the eight “empowered action group” (EAG) states (Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, and Uttar Pradesh) which are mainly the larger poorer states, eight non-EAG states (Andhra Pradesh, Gujarat, Karnataka, Kerala, Maharashtra, Punjab, Tamil Nadu and West Bengal) and one North Eastern state (Assam).

c. More in-depth analysis of budget and expenditure by cost inputs and functions in Bihar and Uttar Pradesh to arrive at an understanding of the systemic issues that affect utilization of funds in low-income states. (Whereas detailed findings from Bihar and UP are available as separate state-specific reports, we draw upon these reports to reflect upon reasons for under-utilization of health resources in this report to contextualize the expenditure levels and utilization rates across different states in the country).

For analyzing trends over time we categorized the 29 states into three categories: (a) EAG + 1 states – this included Assam, (b) Non-EAG States, and (c) North Eastern (NE) states. We analyzed inter-category and intra-category variations to identify expenditure and utilization patterns.

To better understand how primary care is financed and its trends, panel data from financial years 2005-06 to 2013-14 in the 16 sampled states was analyzed to estimate the association between changes in central grants for primary care and changes in states’ own spending for primary care, adjusting for changes in GSDP and ratio of total health spending to total state expenditures. For further details on the method of substitution analysis, refer to Section 4.5(2) of this report. State financial data was disaggregated into levels of care (primary, secondary, tertiary, medical education and administration) based on the categories used by the National Health Systems Resource Center in the Budget Tracking Toolkit (NHSRC).

2.3 Assumptions and interpretation

The Budget Tracking Toolkit (NHSRC-MOHFW) was used for classifying budgets and expenditure into levels of care. Wherever there was a conflict between category to be assigned to a particular budget code as per the NHSRC toolkit and the description of the budget line, we used the budget line description to assign the level of care. In all such cases primary care was assigned only when the budget line explicitly stated that the expenditure is at the level of sub-center, Primary Health Center (PHC) or a Community Health Center (CHC). For the purpose of this study, CHC was considered as primary care facility. NHM budgets and expenditure are treated as 100 percent primary care. All budget figures included in the analysis are “Revised Estimates” and expenditures are ‘Accounts’ figures, unless stated otherwise. Total state government expenditure is sum of the total Development and Non-development expenditure as available in the Reserve Bank of India (RBI) records.

2.4 Limitations

The estimation of primary care expenditures is limited to only 16 states. Due to the time lag in the availability of expenditure data for FY 2014-15 the latest year in the study is 2013-14. For estimating primary care, we included only the budget and expenditure line items assigned under the following Major Codes: 2210, 2211, 4210 and 4211 routed through Medical, Health and Family Welfare related Departments of different states, except for Assam and Tamil Nadu.

4


About the study

a) Tamil Nadu: In addition to the four Major Codes mentioned above, we included the Major Code 2235 (Social Security and Welfare) under Demand 19 (Health and Family Welfare Department) as large funds for Family Welfare activities are booked under this Major Code.

b) In Assam Grant 29 Medical & Public Health does not reflect any capital expenditure on health under the Major Codes 4210 or 4211. Capital expenditure 4210 is booked under Grant 17 of Public Works Department and this has been included in our estimates.

Budget and expenditure in Jharkhand on RBI records are the same for the years 2005-06 to 2010-11.

2.5 Data sources

All budget and expenditure figures for health and family welfare and for the entire state are sourced from RBI for all the 29 states. For primary care analysis for 16 sampled states we have used the state budget books of respective years. All GSDP figures are from the Ministry of Statistics and Plan Implementation, Government of India and population figures are Registrar General of India projections. NHM budget figures have been sourced from Record of Proceedings available on the NHM website and expenditure figures are sourced from NHM office of Government of India and external audit reports and balance sheets of the State Health Societies in Bihar and UP. Apart from the above, some of the other documents we have reviewed include audit reports (for Bihar and UP) of the Comptroller and Auditor General of India, Indian Public Finance Statistics and State Finances – Study of Budgets (RBI).

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The Context

3. The context

3.1 Experiences of the previous decade: 2005 – 2014

Over the last decade, India experienced dramatic changes in how government health care is financed. Starting with the first term of the United Progressive Alliance (UPA) government in 2004, followed by its second term (2009-2014), government made an enhanced commitment to financing the health sector with more active engagement from the central government. (The current NDA government has begun changing this approach by reducing the central government role in financing specific schemes and granting more fiscal autonomy to the states, devolving to them greater responsibility to prioritize social sectors including health.)

Supply side financing efforts:

With a goal of providing “accessible, equitable and affordable healthcare”, the UPA government provided more central government funds to states to improve health indicators, such as child and maternal mortality, and to boost capacity of the government health care delivery system under the NRHM established in 2005. The UPA government had also committed itself to Universal Health Coverage (UHC). Subsequently, NRHM was subsumed under an umbrella initiative called NHM along with the National Urban Health Mission (NUHM) as a sub-set of the NHM. NRHM/NHM’s announced goal to increase public financing of health care from 1 percent to 2-3 percent of GDP by 20122 (Berman et al 2010) was an ambitious but somewhat unrealistic one. To achieve this commitment or even substantial movement towards it, both central and state governments would have needed to increase health spending at an unprecedented pace.

One of the key reasons for a shortfall in increasing government funding for health is that the funding from the states own revenues, the primary financiers of government health spending, increased at a much slower pace than the center and was much lower than planned. Despite a substantial increase in central funding, states spending on health continued to be in the range of 3 to 5 percent of their revenue spending and to meet the target of 2-3 percent of GDP, states would have to increase their proportion of health spending to 8 percent (Rao, 2017). A recent WHO study on 26 low income countries, including India, reported that, even with favorable economic growth and an expanding tax base many of these countries found it difficult to increase public funding on health due to the constraints posed by a large informal sector and rural population (Durairaj et al, 2010). In spite of years of strong economic growth, India’s public health expenditure didn’t begin to increase until there was a strong political commitment. An analysis by the authors in an earlier paper found a significant difference between the elasticity of central health spending versus aggregate state health spending to GDP in India: the former is much higher at 1.15 and close to the average for low-income countries, while the latter is only about 0.87, implying that state health spending has grown at a lower rate than GDP growth (Berman et al, 2010).

In spite of not meeting its health expenditure targets, NRHM was instrumental in improving some of the programmatic outputs, such as, an increase in institutional deliveries or decline in the Infant Mortality Rate (IMR). In 2012, at the end of the Eleventh Plan, the scope of NRHM was expanded to cover the urban poor, particularly those residing in slums and it was renamed as the National Health Mission (NHM). The NHM was designed to afford greater flexibility to the states to make multi-year plans for systems strengthening, and addressing threats to health in both rural and urban areas through interventions at primary, secondary and tertiary levels of care.

A Planning Commission report from the Eleventh Plan period (2008-12) noted that the multiplicity of Central Sector and Centrally Sponsored Schemes addressing individual diseases, through siloed funding channels fragmented service delivery and led to duplication and redundancies, such as central government paying for transport charges of community workers, but states struggling to meet high end costs. This constrained the flexibility of the states

2 Government health spending in India – Political Weekly

6


The Context

to make need-based plans or deploy their resources in the most efficient manner. Resources are spread thin and programs are unable to reach their maximum potential (Planning Commission, 2011a).

Toward the end of the UPA government, the High Level Expert Group (HLEG) report on Universal Health Coverage for India proposed a revised strategy for health reflected in part in the Twelfth Five-Year Plan. It intended to roll out a process to advance towards UHC. To finance this effort, the Twelfth Plan projections envisaged increasing total public funding, plan and non-plan, on core health from 1.04 per cent of GDP in 2011–12 to 2.5 per cent of GDP by the end of the Twelfth Plan. To achieve this, the funding in the Central Plan would have to increase to 3 times the Eleventh Plan levels involving an annual rate of increase of 34 per cent.

Table 1: Budget Support for Central Departments of MoHFW in the 11th (2007-12) & 12th (2012-15) Plan Projections

Central Departments of MoHFW11th Plan

Expenditure12th Plan

OutlayPercentage

increaseDoHFW 834,070 2,685,510 322%

Dept of Ayush 29,940 100,440 335%

Dept of Health Research 18,700 100,290 536%

AIDS Control 13,050 113,940 873%

Total MoHFW 895,760 3,000,180 335%All figures are in million Rs

Source: 12th Five Year Plan, Gol-health chapter

Demand side financing efforts:

NRHM/NHM included several innovative schemes to incentivize and support better use of health services. The most visible of these is Janani Suraksha Yojana (JSY), which provided incentives to village level workers called Accredited Social Health Activists (ASHA) and pregnant women to deliver their babies in health facilities. The schemes, similar to conditional cash transfer approaches, were funded and implemented through the enhanced society route created at state, district, and facility levels by the NRHM/NHM.

New health insurance schemes were also created during this time. Until the Eleventh Plan, government-funded health insurance was available primarily to government employees and workers in the formal sector nationally, although some state-level schemes provided broader coverage. Private health insurance coverage has been limited to formal sector and higher income citizens. 86 percent of rural and 82 percent of urban population has been estimated not covered by any type of health insurance (GoI, 2015). The poor have little access to any risk pooling and risk catastrophic out of pocket payments in the event of a serious illness. A recent analysis conducted by the National Institute of Public Finance and Policy (NIPFP) reported that only 9 percent of government health expenditure benefited the poorest quintile, while 40 percent of the government spending benefited the richest income quintile (Chakraborty et al., 2012).

The ‘Rashtriya Swasthya Bima Yojana’ (RSBY) was introduced in 2008 by the central government to meet the health insurance needs of the poor3. The scheme covers only hospitalization expenses including maternity benefit, and preexisting conditions. RSBY was originally limited to Below Poverty Line (BPL) families but was later extended to building and other construction workers, Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) beneficiaries, street vendors, beedi workers, and domestic workers. The scheme is currently being implemented in

3RSBY provides for ‘cash-less’, smart card based health insurance cover of Rs. 30,000 per annum to each enrolled family, comprising up to five individuals. The beneficiary family pays only Rs. 30 per annum as registration/renewal fee.

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The Context

24 States/Union Territories. 41.3 million families have been registered as of March 2016. Key feature of RSBY is that it allows for private health service providers to be included in the system, if they meet certain minimum standards and agree to provide cash-less treatment which is reimbursed by the insurance company. This has the advantage of giving patients a choice between alternative service providers where such alternatives are available. Several State Governments (such as those of Andhra Pradesh, Karnataka, Kerala, and Tamil Nadu) have introduced their own health insurance schemes, which often have a more generous total cover but are competing for the same scarce resources at the state level.

3.2 New government – new objectives

The overarching goal of health care, as stated in the BJP party’s election manifesto, is to provide

“health assurance to all Indians and to reduce the out-of-pocket spending on health care” with the help of state governments. In addition, the party promised to focus on key determinants of health—sanitation and drinking water—to reduce water-borne diseases, along with increased engagement with the private sector.

The first initiative to translate these promises into reality came in October 2014, in the form of a national campaign to end open defecation by 2019 – Swachh Bharat Mission. It is financed by an earmarked tax of 0.5 percent of all taxable services. The Swachh Bharat Cess is collected in the Consolidated Fund of India to pay for its initiatives. The second initiative was the new National Health Policy (NHP) approved in 2017. It does not commit to any increase in public spending on health—currently approximately 1.2 percent of GDP, but emphasizes sourcing of care from the private sector. A blueprint of this public-private collaboration is yet to be drafted. The current administration’s policy clearly deviates from the Congress led UPA government’s, which emphasized more central government support.

In early 2015, the 14th Finance Commission (FC) recommended a greater devolution of central government tax revenues to states, shifting some funds that had earlier been spent through a variety of centrally sponsored schemes. The FC recommendations are implemented in FY 2015-16. This policy reflects an expectation that states will spend the increased funds better. There are concerns about this policy expressed by some experts because states’ health system performance and their capacity to absorb additional funds varies, as reflected in wide disparities in outcomes. There is also a concern that even if more funds are available to states, they may not further prioritize health. “While giving a greater share of taxes to states may seem like strengthening state autonomy, we have seen that historically states with the poorest health indicators invest the least in health. This trend will not reverse without any explicit directions or guidance from the central government”, said Abhijit Das, Director of the Centre for Health and Social Justice in New Delhi (Sharma, 2015).

As many as 15 of the health ministry’s national programs, including tobacco control, mental health, prevention of blindness, trauma care, elderly care, and human resource development have not been allocated separate funds, and have been merged with NHM, which appears to have stagnated between 2013-14 (expenditure of Rs. 182,110 million) and 2016-17 (BE Rs. 190,000 million) (NHP 2016).

The new government’s stated plan to set up a National Health Assurance Mission to reduce out of pocket spending has not yet materialized. In its place it was decided that RSBY should be restructured and expanded. The government is considering a new IT-supported implementation platform for this insurance scheme that would integrate other social and health schemes that address health and its determinants, such as Janani Shishu Suraksha Yojana, in order to avoid duplication. The central government is still in the process of working out what schemes will be covered and what would be the ceiling for individual procedures. States could add to both by paying for additional coverage. This expanded and restructured RSBY, possibly under a new name, is expected to be rolled out by the financial year 2017-18 (Ghosh, 2016).

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The Context

The current administration has also continued investing in establishing six new All India Institutes of Medical Sciences (AIIMS) at Bhopal, Bhubaneshwar, Jodhpur, Patna, Raipur and Rishikesh, which are part of the Pradhan Mantri Swasthya Suraksha Yojana launched under the previous Congress government. A plan to set up four more AIIMS-like institutions in Andhra Pradesh, West Bengal, Vidarbha in Maharashtra and Poorvanchal in Uttar Pradesh is under consideration.

The abolition of the Planning Commission, which had the authority to allocate money to states for specific sectors, may be another important factor affecting future health financing. In its place, in 2015, the National Institution for Transforming India (NITI Ayog) was established as a policy think tank for the Government of India. One of the objectives of the NITI Ayog is to become a platform for the GoI to coalesce support from the states in order to reinforce common national interest and thereby foster Cooperative Federalism. This idea is especially relevant for the health sector, as health is a state subject, and in the past, the central government’s promise to increase health expenditure to 2-3 percent of GDP was not borne out by sufficiently increased state allocations. The implications of NITI Ayog for the health sector are still unclear.

3.3 Changes in central transfers – now through Treasury instead of State Health Society

Establishment of NHM consolidated all vertical program specific societies under umbrella health societies, one at the state and the other at the district level, except the state/district AIDS Control Society. This rearrangement was intended to improve operational efficiency and autonomy, as the GoI made direct transfers to the State Health Society (SHS). However, in mid 2014, the central government changed the modality of NHM transfers from the center to the states in order to enhance the supervision of NHM funding. Instead of direct transfers to the SHS in respective states, funds are now channeled to the societies through the state treasuries, with the condition that the state treasury transfer the NHM funds to the SHS within 15 days of receipt of the funds. However, in the initial implementation of this change no state treasury released the funds to the designated health societies within a stipulated 15-day period, with delays running into months in some cases. More than $180 million was still to be released as of February 2015 (Kalra, 2015). See Figure 2.

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The Context

Figure 2: Delays in transfer of payments (tranches) to the Health Societies by state treasuries

15


Source: https://amers1.proxy.cp.thomsonreuters.com/graphics/15/indiahealth/index.html

Finally, a brief chronology of policy milestones related to health and health care financing is capturedbelow. See Figure 3.

15




15





Finally, a brief chronology of policy milestones related to health and health care financing is captured below. See Figure 3.


10

Figure 3: Health Care Financing Timeline

The Context

11


Study Results

4. Study results

4.1 Resource mobilization and allocation

Public health care is financed by states and the Center. The states typically contribute two-thirds of the total resources for health, and the Center provides the remaining one-third, and the policy direction for the health sector.

The central government supports the states through statutory transfer of (income) tax receipts that contribute to the state’s fiscal space. It also finances sector specific initiatives like Centrally Sponsored Schemes; central assistance to state plans; and special plan schemes to even out the diversity in social sector outcomes among the states. The NHM is an example of such a scheme in the health sector. Though there have been several criticisms related to proliferation of large number of schemes and the need for more transparency in such transfers (Planning Commission, 2011c), central schemes like the NHM have contributed to increased levels of public expenditure on health in states. In addition to the statutory transfers from the Center, the states generate their own tax revenue from including sales and corporate taxes and excise duties.

Our analysis of state’s own taxes as a share of Gross State Domestic Product (GSDP) over time confirmed that the non-EAG states have significantly higher capacity to mobilize taxes than other 2 groups of states - the North Eastern (NE) states, and the EAG+1 states. The average states’ own tax to GSDP ratio in 2013-14 for non-EAG states is 8.3 percent, the same is 6.8 and 3.3 percent for EAG+1 and North East states respectively. Resource mobilization capacity is very varied among the 29 states, with Andhra Pradesh (15.61 percent) and Nagaland (1.96 percent) at two opposite ends of the spectrum. This resource mobilization ability is a reflection of their level of economic activity and how streamlined and efficient their tax collection systems are. See Figure 4.

Figure 4: State’s own tax to GSDP ratio: 2013-14

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Own Tax to GSDP ratio: 2013-14

Non-EAG States EAG States + Assam NE States

The current central government has recently introduced the Goods and Services Tax (GST) bill that is a comprehensive indirect tax on manufacture, sale, and consumption of goods and services throughout India, to replace taxes levied by the central and state governments. Administrative responsibility is expected to rest with a single authority to levy tax on goods and services. This GST is planned to be rolled out in July 2017, and is expected to transform and improve the indirect tax collection system for the states and the central government.

Following the 14th Finance Commission recommendation and the fiscal devolution, the central government now puts increased onus on the states to determine how much to invest in the health sector and therefore has fewer resources for sector specific support, including health. Some of the less developed states like, Chhattisgarh,

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Study Results

Jharkhand, Madhya Pradesh and Rajasthan have prioritized social sector one year since the 14th FC; however, in other states, particularly Bihar, it is observed that the total levels of investment in social sectors was reduced in the year following the FC 14th recommendations (Kapur et al., 2016).

One measure of whether a state is prioritizing health is the share of total state budget allocated to health. Almost all the states, except Delhi and Tripura, allocate less than 6 percent of their total state budgets for health. Delhi budget share for health through the treasury route has remained consistently higher than other states ranging between 8 and 11 percent between 2005-06 and 2013-14 possibly, due to Delhi’s “city-state” character, with a higher density of state hospitals. It is counter intuitive to observe that economically advanced states like Maharashtra, Karnataka, and Haryana do not prioritize health. One of the main reasons cited at least for Karnataka’s low prioritization of health (and education) sector is because of the 5th and 6th pay commission implemented by the central government that caused a substantial increase in the salaries of all government employees and consuming a higher proportion state budget (Prabhu 2016). See Table 2.

Table 2: Proportion of total state budget allocated to health over 3 years

States 2012-13 2013-14 2014-15BELOW 6 PERCENT

Andhra Pradesh 4.72% 4.79% 4.39%

Arunachal Pradesh 3.97% 4.06% 6.04%

Assam 4.6% 4.31% 5.19%

Bihar 3.7% 3.64% 4.12%

Chattisgarh 4.36% 4.54% 5.35%

Goa 5.78% 5.78% 5.79%

Gujarat 5.07% 5.09% 5.96%

Haryana 4.02% 3.92% 4.32%

Himachal Pradesh 5.73% 5.73% 6.21%

Jammu & Kashmir 5.40% 5.36% 5.61%

Jharkhand 4.17% 3.9% 5.02%

Karnataka 4.28% 4.62% 5.18%

Kerala 5.99% 5.70% 6.87%

Madhya Pradesh 4.87% 4.55% 4.82%

Maharashtra 4.08% 4.29% 5.05%

Manipur 4.66% 5.17% 6.01%

Meghalaya 5.35% 4.81% 5.14%

Mizoram 3.82% 3.87% 6.17%

Nagaland 4.01% 3.86% 5.57%

Odisha 4.03% 3.73% 5.19%

Punjab 5.66% 5.55% 5.01%

Rajasthan 5.07% 5.54% 6.16%

Sikkim 5% 4.82% 5.48%

Tamil Nadu 4.86% 4.8% 5.22%

Uttar Pradesh 5.49% 5.21% 5.3%

Uttarakhand 6.56% 5.44% 6.14%

West Bengal 4.52% 5.54% 5.05%

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Study Results

ABOVE 6 PERCENT Delhi 9.98% 9.73% 12.87%

Tripura 6.75% 7.36% 7.22%

Our elasticity analysis show that there is no statistically significant relationship between fiscal capacity (as measured by tax to GSDP ratio) and health expenditure levels, but there is a statistically significant and positive relationship between tax-to-state budget ratio and health expenditures; a 1 percent increase in this ratio leads to a 1.85 percent increase in state health expenditure. These results illustrate the point that while an increase in GSDP and tax revenue is a necessary condition, it is not sufficient to actually increase health spending. Deliberate prioritization of health, by allocating additional funds made available because of the expanded fiscal space, is critical.

The NHM was established as a financing mechanism to mitigate the health financing and outcome disparities between states. The states that had low health outcomes – primarily the EAG states and the northeastern states because of their unique political status and geography, received larger proportions of central government support through NHM as compared to the rest of the states. However, it has been observed that some of the poorer states have difficulty to absorb these resources from the center. More discussion and evidence of low absorption is included in a subsequent section.

Key messages

• States’ ability to mobilize own tax revenue varies significantly across the country. Richer states are better able to mobilize own tax revenue than poorer states.

• Evidence suggests that there is a positive significant relationship between the tax revenue to state budget ratio and health expenditure, implying – for every one percent increase in the tax revenue to state budget ratio there is a 1.85 unit increase in the state’s health expenditure.

• Most states do not prioritize health and allocate less than 6 percent of its state budget to health, except Delhi and Tripura. It is interesting to note that even some of the richer states consistently have allocated less than 6 percent, including Tamil Nadu or Maharashtra.

4.2 Total government health expenditure

This section compares Total Government Health Expenditure (TGHE) over time across categories of states, followed by the role NHM plays in government health expenditure – its trend over time and the extent to which states depend on it. Finally, trends and levels of per capita TGHE are discussed.

In 2005, India embarked on a concerted effort to increase government health spending. The goal, expressed by the Prime Minister and Finance Minister that year, was to increase government health spending from less than 1 percent of GDP to 2-3 percent of GDP in 7 years. One result of this commitment was the impressive 262 percent nominal increase in TGHE over the 8 years, from Rs. 241.2 million to Rs 873.5 million (See Figure 5) . However, as noted in Figure 6, by 2013-14, other than the North Eastern states and Jammu & Kashmir, none of them exceeded the 2 percent of GSDP threshold. More than half the states (15/29) spend less than 1 percent of their GSDP on health, including some of the better off states like Maharashtra, Gujarat, Karnataka.

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Study Results

Figure 5: Total Government Health Expenditure (Nominal) by Groups of States

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100,000

200,000

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2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

Total government health expenditure by groups of states (in Rs. million)

EAG+1 NE Non-EAG 29 states

Figure 6: Distribution of states’ total government health expenditure as a proportion of GSDP

0.00%

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TGHE as proportion of GSDP (2013-14)

Non-EAG States EAG States + Assam NE States

3.5 %

3%

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1.5%

1%

0.5%

0%

In 2015, government health spending was reportedly around 1.2 percent of GDP. This goal was reiterated in 2012 by the High Level Expert Group on Universal Health Coverage, which recommended achieving 2.5 percent of GDP by the end of the 12th Five-Year Plan (Planning Commission, 2011b).

There are several reasons explaining the failure to meet the goal of 2-3 percent of GDP on health. First, the goal itself was arbitrary and not based on any clear statement of outcomes. Second, while the center increased its contributions,

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Study Results

the states did not contribute what was expected of them and states account for about 70 percent of total health spending. Third, the financial crisis in 2009-10 shrunk the fiscal capacity of the central and state governments, derailing the momentum towards the goal. Shortfalls in the states’ contributions are due to both their limited fiscal capacity and their low prioritization of health over other development needs. The central government, through NHM and other channels, increased its contribution to health over time. But this contribution was not sufficient to achieve the goal and slowed in the latter years.

National Health Mission expenditures trends and levels

Majority of the central funds earmarked for health (in contrast to general revenue sharing) are channeled through the NHM so it is important to look at it more closely. NHM was intended to incentivize the states to increase their own resource envelope for health while also favoring the poorer states. For example, the center would contribute up to 85 percent of the NHM allocation with only 15 percent matching requirement from EAG states. This ratio is 60:40 in non-EAG states. As noted in Figure 7 below, NHM on an average constitutes about 35 percent of TGHE in EAG states for the last several years. In Bihar, the NHM made up 44 percent of the TGHE in 2013-14. See Figure 8.

Figure 7: NHM as a share of TGHE across state categories

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

NHM as share of TGHE

EAG + 1 States NE States Non-EAG States 29-states (mean)

For state-wise shares of NHM in the TGHE for each of the study years, refer to Annex 2.

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Study Results

Figure 8: NHM as a share of TGHE in 2013-14 by state

44%

41%40%

37% 36%35%

32%

30%

26%25%

24% 23%22% 22% 22% 22% 21% 21%

20%19% 18% 17% 17% 17% 16% 16%

15%13%

6%4%

NHM as a share of Total Government Health Expenditure TGHE in 2013-14

Non-EAG States EAG States + Assam NE States 29-State Mean

While NHM central contributions constitute one-third or more of total health funding by EAG states, an analysis of central contributions through NHM as a proportion of the GSDP, however, shows a fairly modest proportion of GSDP even in the poorest of states. In some of the better off states like Kerala, Tamil Nadu and Goa, it is less than 0.15 percent of the GSDP. See Figure 9. By spreading central funding across all states, the resources are spread thin, thereby diluting its impact. In some of the better states, the NHM resources are a comparatively smaller proportion of the overall health resource envelope, and therefore not sufficient incentive to increase state’s own allocation, and as a result raise the following questions.

a. Is it better value for money for NHM to concentrate in a few states with poor outcomes than spreading its investments thinly across all 29 states? It is conceivable that these better off states can mobilize funds equivalent to what they receive from the central government.

b. What is the transaction and administrative cost of NHM borne by the states and the central government? By concentrating in a few states, can this transaction cost also be potentially reduced?

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Study Results

Figure 9: Central portion of NHM expenditure as a share of GSDP0.

79%

0.61

%

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%

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%

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%

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%

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Central Government portion of NHM expenditure as a share of GSDP

Non-EAG States EAG States + Assam NE States 29-State Mean

Per Capita TGHE

After ten years of NHM support, the EAG states still constitute seven out of ten states with the lowest per capita TGHE. This reinforces the view that NHM alone has not been effective in narrowing the gap, between the better off and the weaker states, see Figure 10 and Table 3. The mean per capita TGHE across 29 states in 2013-14 was Rs 1305 (Rs 719 at 2004-05 prices), with wide inter-state variations reflected in a 13-fold difference between Sikkim (Rs 4258) and Bihar (Rs 339). While in nominal terms the increase in per capita TGHE between 2005 and 2013 is substantial, in real terms the increase is less than 100 percent in each of the categories. The 29-state average increase in real terms is 88 percent, where as it is 78 percent EAG+1 states. See Table 3.

Figure 10: Per capita total government expenditure on health in 2013-14 (nominal and real)

4,258

3,023

2,562

3,222

1,771 1,819 1,745 1,551

1,745

1,287 1,572

1,157 1,122 978 907

714 801 767 758 788 755 788 750 592 615 583

432 461 339

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Per capita TGHE in 2013-14 - Real and Nominal (in Rupees)

Nominal Real

29-states mean:Rs 1,305 (at nominal prices)Rs 719 (at 2004-05 constant Rs.)

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Study Results

Table 3: Per capita TGHE across state categories (Nominal & Real) in Rs.

State Categories

Type 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

EAG+1 states

Nominal 211 261 300 360 414 484 515 586 659Real 199 231 249 276 298 319 313 336 355

NE StatesNominal 685 821 1,009 1,367 1,666 1,777 2,159 2,195 2,419Real 660 758 887 1,117 1,271 1,244 1,378 1,297 1,314

Non-EAG States

Nominal 375 418 478 596 739 846 944 1,041 1,154Real 359 382 410 463 539 574 596 630 651

29-state mean

Nominal 399 466 551 709 862 958 1,104 1,179 1,306Real 382 426 475 563 641 657 697 700 719

Several factors contribute to these differences in per capita health spending across states. Governance factors in each state determine how much is allocated to health and how effectively it is utilized. The population growth rate, which also varies substantially among states, also determines the extent to which increased total spending actually increases per capita spending. The 2011 census reveals that collectively the population growth rate in EAG states is much higher than the national or the non-EAG states average, which mitigates the impact of the overall increased health expenditure. (Source: GOI 2011).

The graph below on the growth rate of the per capita TGHE across the states highlights two main points – overall declining trend in the per capita TGHE growth rate, but also the erratic trajectory overtime. This volatility in health spending overtime reflects the poor planning and budget execution capacity among the states. See Figure 11.

Figure 11: Per capita TGHE (real) growth rate

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Study Results

Key messages

• The TGHE as percent of GDP after 10 years of NHM is still very short of what was promised. This reflects several factors including the financial crisis of 2009-10, lower allocations from the states to the health sector, and weak utilization of budgeted resources. Achieving much higher government spending will not likely be possible unless these two latter factors can be addressed.

• Ten years since the NHM was launched the imbalance in health spending and health outcomes between the states persists, despite the substantial support to EAG states through NHM. They received between 30 and 35 percent of their total health spending through NHM for the last 5 years, with Bihar receiving the highest proportion. The same ratio is about 18 percent for Non EAG states. But the better-off states with better budget utilization capacities and lower population figures, contribute to the persistent inter-state disparities.

• The per capita TGHE of 29 states is very low - Rs 1305 per capita (nominal) and Rs. 719 per capita (real). Seven out of ten states that have the lowest per capita health spending are EAG states.

• Overall growth rate of per capita health expenditure across all categories of states appears to be on a decline. This is partly due to a slowdown in government spending from central and state sources. It is also partly due to higher population growth in EAG states.

4.3 Utilization of health budgets

The preceding sections have reported evidence on actual spending the first 10 years of NHM. The section below examines how well budgets have been translated into actual spending for both the treasury and the society routes of spending.

Overall, data from 29 states over 8 years shows that on an average budget utilization is about 90 percent and 85 percent for treasury and NHM respectively. The state contribution is typically in the form of salaries, which tend to have a higher utilization rate. For the society route, utilization of budgets is lower and more uneven. It is also worse in some of the poorer states, which ironically, depend more on NHM funds. Reasons for the underutilization are explained in the section below.

Between 2005-06 and 2013-14, the mean utilization rate of health budgets through the treasury route across states is 90 percent. There are only three states below the 29-state-mean in the non-EAG category of states as compared to seven (out of 9) states including Assam in the EAG + 1 state category. Utilization of treasury budget for health in Tripura (72%) is the lowest among all 29 states and deserves attention. See Figure 12.

Even though allocations to states are made according to the state’s need, the actual releases depend on fulfilling certain conditionalities, such as Utilization Certificate (UCs). Ironically, the poorer states plagued with several systemic constraints underutilize their share, which is then eventually redistributed to the better off states that can fulfill these conditions and have a better utilization capacity. (Rao 2017)

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Study Results

Figure 12: Average (2005-06 to 2013-14) utilization rate of treasury budgets for health across states

Non-EAG StatesMean

budget utilization

EAG + 1StatesMean

budget utilization

NE StatesMean

budget utilization

Gujarat 99% Rajasthan 94% Meghalaya 101%Himachal Pradesh 97% Madhya Pradesh 91% Nagaland 98%Kerala 97% 29-states mean 90% Sikkim 96%Jammu and Kashmir 96% Jharkhand 88% Manipur 94%Tamil Nadu 96% Uttar Pradesh 86% Mizoram 93%Karnataka 95% EAG+1 states mean 85% Arunachal Pradesh 91%West Bengal 94% Odisha 83% 29-states mean 90%Maharashtra 94% Uttarakhand 83% NE States mean 90%Non-EAG states Mean 94% Bihar 79% Tripura 72%Delhi 93% Chattisgarh 78%Andhra Pradesh 92% Assam 75%29-states Mean 90%Goa 89%Haryana 88%Punjab 79%

Mean utilization = ∑ expenditure 'tween 2005-06 and 2013-14 / ∑ budgets 'tween 2005-06 and 2013-14

Utilization of NHM budgets is a reasonable representation of the budget effectiveness overall of the society route, since NHM funds constitute majority of the society resources. For 29 states, the mean utilization rate of approved NHM budgets is 85 percent. More number of EAG+1 states are doing better job utilizing NHM budgets than the treasury budget.

Nine of the 14 states that are below the 29-States average have less than 80 percent utilization. See Figure 13.

Figure 13: Average (2007-08 to 2014-15) utilization rate of NHM budgets for health

Non-EAG StatesMean

budget utilization

EAG + 1StatesMean

budget utilization

NE StatesMean

budget utilization

Tamil Nadu 110% Uttarakhand 95% Sikkim 96%Kerala 105% Madhya Pradesh 94% Mizoram 91%Himachal Pradesh 103% Rajasthan 93% Arunachal Pradesh 86%Haryana 96% Assam 87% 29-states mean 85%Gujarat 91% Uttar Pradesh 86% NE States mean 78%Maharashtra 91% 29-states mean 85% Nagaland 77%Punjab 90% EAG+1 states mean 84% Manipur 74%29-states Mean 85% Odisha 81% Tripura 72%Non-EAG states Mean 88% Bihar 80% Meghalaya 67%West Bengal 83% Chattisgarh 77%Goa 82% Jharkhand 51%Jammu & Kashmir 82%Andhra Pradesh 77%Karnataka 73%Delhi 46%

Mean utilization = ∑ expenditure 'tween 2007-08 and 2014-15 / ∑ budgets 'tween 2007-08 and 2014-15

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Study Results

Understanding underuse of NHM budgets: case studies in UP and Bihar

A more in-depth study in Uttar Pradesh and Bihar was carried out to better understand the systemic issues that affect utilization rates for NHM budgets.

Tables 4 and 5 below present evidence on budget utilization in the two states. Two figures are provided – against “approved budget” and against “available funds”. The distinction is important. Unlike in the treasury route where unused funds at different departments lapse at the end of the fiscal year and are returned to the treasury, NHM funds using society route rules can be carried over from one year to the next, with the balances retained in the societies’ bank accounts; however, subsequent allocation from the center are reduced to the extent of unspent uncommitted balances. The figures against approved budget show the utilization of budgeted funds in that year. The figures against available funds show the percentage of total balances used in that year. When this latter number remains high, it indicates a persistent inability to effectively use budgeted and available funds.

In 2013-14 we see almost 50 percent of the total available funds under the NHM in Bihar remain unutilized, where as in UP in 2014-15, this percentage is slightly better, with 39 percent of the total funds available remain unspent to be carried over to the next year.

Table 4: Utilization rates under NHM in Bihar

Amounts in million Rs2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

NHM approved budget 9,786 12,547 12,739 13,452 20,371 20,169

Total funds available* under NHM 17,172 17,463 20,709 22,755 33,239 30,736

Total expenditure under NHM 10,927 7,839 14,186 11,074 13,589 15,306

Budget Utilization Percentages

Utilization against approved budget 112% 62% 111% 82% 67% 76%

Utilization against available funds 64% 45% 69% 49% 41% 50%

*Total funds available includes unspent balance and interests earned

Table 5: Utilization rates under NHM in UP

Amounts in million Rs2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15

NHM approved budget 18,469 29,005 27,935 25,952 43,524 37,081 38,322

Total funds available+ under NHM 24,430 32,619 33,905 33,384 42,725 65,941 61,792

Total expenditure under NHM 14,999 22,006 26,493 19,877 33,372 31,191 37,716

Budget Utilization Percentages

Utilization against approved budget 81% 76% 95% 77% 77% 84% 98%

Utilization against available funds 61% 67% 78% 60% 78% 47% 61%+Total funds available includes unspent balance and interests earned

In resource constrained states like UP and Bihar where NHM as a share of TGHE is substantial, such high levels of under-utilization of funds by the SHSs have a significant effect on the levels of health expenditure. Our calculation shows that if 100 percent of funds available were utilized in one particular year, the TGHE in Bihar and UP would have increased by 49 percent and 26 percent respectively. See Figure 14.

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Study Results

Figure 14: Impact of State Health Society Utilization on the TGHE

34,036

119,550

50,595

150,370

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Bihar 2013-14 UP 2014-15

Impact of SHS utilization on TGHE (in Rs. Million)

Current TGHE TGHE if SHS spent 100%

Reasons for budget under utilization based on findings from UP and Bihar

Reasons for such low levels of fund utilization based on the deep dives conducted in Bihar and UP can be classified into two broad types of challenges: (A) NHM design and relevant capacity, and (B) operational issues. The deep dives included a qualitative component (Focus Group Discussion, Key Informant Interviews) in addition to budget and expenditure assessment.

A. NHM design and relevant capacity issues:

• Insufficient capacities and leadership to design and implement innovations has been one of the major reasons for budget underutilization in the NHM program, which for the first time in the health sector provided the space and the resources to the states to innovate and be responsive to its specific needs. The pool of funds that affords management and financial flexibility under NHM is called the Mission Flexi Pool (MFP) Component. Figure 15 below shows allocations to the MFP component constituted between a third to almost half of the total approved NHM budget in Bihar and UP. But the mean budget utilization rate between 2011-12 and 2013-14 for the MFP was only 46 percent and 32 percent in Bihar and UP respectively.

Figure 15: Budget shares & utilization by program components: Bihar & UP

51%

36%

8% 5%

69%

46%

59%

45%

RCH Flexipool Mission Flexipool Immunization and PP Disease Control

Budget Shares & Utilization by NHM Program ComponentsBIHAR: Mean (2011-12 to 2013-14)

Budget Share Budget Utilization

42% 45%

7% 6%

63%

32%

106%

53%

RCH Flexipool Mission Flexipool Immunization and PP Disease Control

Budget Shares & Utilization by NHM Program ComponentsUTTAR PRADESH: Mean (2011-12 to 2013-14)

Budget Share Budget Utilization

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Study Results

Analysis highlights that utilization rates are higher of budget items where the purpose of the expenditures is explicit, but the budget lines that require discretion in the optimal use of funds tend to remain underutilized. This assertion becomes more evident when we analyze the MFP budget lines4 of Bihar. See Figure 16.

Figure 16: Utilization rates of MFP budget lines for NHM in Bihar

0%10%20%30%40%50%60%70%80%90%

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Mission Flexipool Utilizations

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Corpus DAP PRI AYUSH IEC/BCC


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MMU RT PPP INNO' PIMPROCUREMENT

MIssion Flexipool UtilizationsMission Flexipool Utilizations Mission Flexipool Utilizations Mission Flexipool Utilizations

PIM PROCURE-MENT

Fluctuating low utilization rates over the last three years in budget lines like hospital strengthening, annual maintenance grants to health facilities innovations, communication efforts, diminish the uniqueness of NHM which was expected to transform the way healthcare services are delivered in the states.

• Risk averse attitudes of lower level leadership seems to have become a risk in itself. Typical administrative delays in sending the relevant expenditure guidelines to the lower levels of governance entities stall even the routine spending contributing to low budget utilization. Following the NHM corruption episode in UP, most financial managers, at the lower levels in particular, have adopted a very risk averse behavior.

• Power dynamics and inter-personal relationships between the Village Health, Sanitation, and Nutrition Committees (VHSNC) at the grassroots level limited the opportunities for convergence with local bodies (Panchayats). These power dynamics play a significant role in what initiative gets financed and who gets paid first, contributing to under-utilization of funds allocated for the VHSNCs.

• Significant delays in civil works in Bihar contributed significantly to the overall budget underutilization. Only 5 out of 298 construction work could be completed till March 2015, 35 are incomplete and 258 projects were yet to start despite the State Health Society Bihar transferring Rs 4,461.7 million to the Bihar Medical Services and Infrastructure Corporation (BMSIC) between April 2011 and February 2014. The BMSIC was set up in 2010 as an independent corporation with the aim of streamlining procurement and supply of drugs. It was also entrusted with the responsibility of civil work to expedite and bring about efficiency to the tardy pace of progress under the Public Works Department (as per 7th CRM report PWD could complete only 29 percent of the work assigned to it) (NHM, 2013). Utilization of budget allocated for new construction/renovation was merely 39 percent in 2011-12, plummeted to 7 percent in 2012-13 and remained at the same level in 2013-14. Lack of foresight and planning is evident here as BMSIC was a new institution without the systems and structures and the district level reach that the Public Works Department has with its cadre of engineers and staff in each of the districts. A few-member infrastructure cell within the Corporation along with a 2-3 member cell within the SHSB could not substitute the technical capacity that PWD had and transform the way civil work projects were implemented in the health sector.

4 UF: Untied Funds; AMG: Annual Maintenance Grants; HS: Hospital Strengthening; Civil: New Constructions/Renovation/setting up; Corpus: Corpus Grants to Rogi Kalyan Samities; DAP: District Action Plans (including block & village plans; PRI: Panchayati Raj Institutions; AYUSH: Alternative Systems of Medicine; MMU: Mobile Medical Units; RT: Referral Transport; INNO’: Innovations; PIM: Planning, Implementation & Monitoring

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Study Results

• Access to medicines - Procurement and supply chain systems for ensuring availability of drugs continue to remain one of the major challenges in spite of the formation of the BMSIC. It was set up to reform and streamline the drug procurement and supply chain system. Five years since its establishment, it still lacks the systems and the capacity to fulfill its mission, which is a reflection of misplaced priorities and poor governance. Absence of accountability mechanisms and processes and systems within the new structure resulted in problems that had already saddled the drug procurement system earlier. Delays in supply of drugs were widespread and audit reports reveal delays up to 418 days in Madhubani district, 337 days in Gaya district, 168 days in East Champaran and 165 days in Kishanganj.

B. Key Operational issues

• Delays in the approval process: Analysis of the time lag between the start of the financial year to the date of issue of the approval by Government of India (date of which the Record of Proceedings letter as available on the NHM website) show an average delay of 51 days, that is 14 percent of the plan period across 29 states in 2013-14. Further analysis in UP reveal 38 percent delay in 2015-16. Delays in central government approvals have an exacerbating effect on state allocations and fund releases to districts, blocks and at facility level.

• Delays in releases of funds: In addition to the delays in spending because of the delays in accompanying expenditure guidelines, the recent change in the routing of the funds through the state treasury instead of directly to the State Health Societies has already resulted in substantial delays in releases. The 93rd Parliamentary Standing Committee for the Department of Health and Family Welfare has already recorded significant delays in onward transfer of central funds from the state treasuries to the Societies across states (GOI, 2016).

• MFP is least prioritized by SHS in UP, and districts received 64 and 73 percent of their total allocations in the last quarter of fiscal year 2013-14 and 2014-15 respectively, allowing very little time for implementation. See Table 6.

Table 6: Quarter wise distribution of MFP funds transferred to UP districts

Quarterly distribution of MFP funds released to UP districts

2012-13 2013-14 2014-15

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

4% 29% 25% 42% <1% 15% 12% 73% 2% 12% 22% 64%

Key messages

• The 29-state average utilization rate against budget for treasury budget is 90 percent and 85 percent for NHM

• Low NHM budget utilization in some of the poorer states significantly reduces resources available for health and especially for primary health care.

• Release of funds depends on utilization of funds and submission of utilisation certificates, which is lower/delayed among EAG states, which results in redistribution of central funds to better off states over time.

• Because funding through the society route allows unused funds to be carried over to subsequent years, the underutilization of NHM funds is significantly lower than it appears from a single budget year accounting. After taking into account the opening balances or total available funds with the state at the start of the year, the utilization rates for NHM in UP and Bihar were 61 and 50 percent respectively.

• If 100 percent of funds available with SHS were utilized, in one particular year the TGHE in UP and Bihar would have increased by 26 percent and 49 percent respectively.

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Study Results

• We see better utilization rates where the purpose of the expenditures is explicit, and budget lines that require discretion in the optimal use of funds mostly remains underutilized.

• Causes for underutilization can be categorized as NHM design and relevant capacity, and key operational issues

o NHM design and relevant capacity include:

Lack of leadership to conceive and implement innovations;

Risk averse attitudes of the leadership;

Power dynamics at the grassroots level limited efforts to facilitate convergence of local bodies; and

Weak accountability and capacity of Public Works Department and procurement and supply chain systems and resulting delays in civil works and drug procurements.

o Key operational issues:

Delays in budget approval processes have cascading effect on fund releases and utilization; and

Mission Flexipool seems to have lowest priority in fund releases – in 2014-15 nearly 64 percent of releases to districts in UP were made in the last quarter.

4.4 An analysis of “reliability” of health budgets (treasury route)

Adapting the Public Expenditure Financial Assessment (PEFA) framework 2016, we measured actual spending as a share of original approved budget (BE) to score the reliability of health budgets. Whereas the PEFA framework assigns grades based on average scoring method over the last three years, we extended this to assign scores for each grade (maximum A = 4 and minimum D = 1). See Table 7.

Table 7: Treasury Budget Credibility Scoring Chart

Grade Expenditure outturn ScoreA Between 95% - 105% 4

B Between 90% - 110% 3

C Between 85% - 115% 2

D Performance is less than required for a C Score 1

We compared the last eight years (2005-06 to 2012-13) average score with the last three years (2011-12 to 2013-14) to assess whether the reliability of health budgets has improved across states. Budget estimates, revised estimates and accounts data for each of the states were sourced from RBI.

Based on the last three years (2011-12 to 2013-14) budget estimates and actual expenditure data, Maharashtra, Tamil Nadu and Sikkim top the list of 29 states on the budget-reliability index, with Bihar and Jharkhand health budgets showing least reliability. A higher score implies more realistic planning, optimal allocation of resources and efficient delivery of services (budget utilization in this case) See Figure 17.

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Study Results

Figure 17: Aggregate expenditure outturn score (2011-14)

-

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

Expenditure Out-turn: Average 3-year (2011-12 to 2013-14) aggregate score

Budgets of Assam, North-Eastern states and the non-EAG states reflect increased reliability in the last three (2011-12 to 2013-14) years as compared to the overall mean in the last nine years (2005-06 to 2013-14). The overall reliability of health budgets in EAG states have declined in the last three years (2.31 to 2.08). Health budgets in Assam have shown the maximum improvement. See Figure 18.

Figure 18: Trends in reliability of health budgets through treasury

1.63

2.31

2.92

2.542.33

2.08

3.21

2.67

Assam EAG states Non-EAG states NE states

Rel

iabi

lity

Scor

e

Trends in Reliability of Health Budgets (Treasury)

9 years average score (2005-06 to 2013-14) 3 years average score (2011-12 to 2013-14)

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Study Results

Whereas overall 20 out of 29 states show an improving trend in reliability, this improvement can be observed only in 3 of the 8 EAG states. In majority of the non-EAG states we see improving budget reliability except Punjab and Delhi (Figure 19).

Table 8 : Number of states with improving & declining budget credibility

StatesNo. of states where Reliability of Health Budgets "Total

States"Improving DecliningAssam 1 0 1

EAG states 3 5 8

Non-EAG States 11 2 13

NE States 5 2 7

Total States 20 9 29

Over time it appears that 5 of the EAG states have declining budget reliability. Bihar, Madhya Pradesh, and Jharkhand show a significant decline, whereas the health budgets in Odisha show a maximum improvement. See Figure 19.

Figure 19: Trends in reliability of health budgets (treasury) in EAG States & Assam

1.63 1.75

1.25

2.88

3.50

1.88

3.25

2.25

1.75

2.33

1.00

1.67 2.00

3.00

2.33

3.00

2.33

1.33

-

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

REL

IABI

LITY

SC

OR

E

Trends in Reliability of Health Budgets (Treasury)EAG + 1 States

9 years average score (2005-06 to 2013-14) 3 years average score (2011-12 to 2013-14)

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Study Results

Key messages

• Budget “reliability” is another measure of effective utilization. As expected the treasury budget reliability of EAG+1 states is weak, as more number of EAG+1 states have below average treasury budget utilization.

• 20 out of 29 states show improvement in making realistic budgets for health; however, this improvement is reflected in only 3 out 8 EAG states.

• Within the EAG states there is also variability. The reliability score of health budgets in Odisha increased 24 percent, in Bihar it declined by 43 percent.

4.5 Primary care expenditure in 16 states – levels and trends over time

1. Primary care expenditure trends: inter-state overview

Evidence suggest a strong primary health care systems is linked to quality and cost effectiveness of overall health system (De Maeseneer et al., 2008) and is a determinant of improved health of the population overall (Kringos et al., 2013). Multiple studies have shown that investment in primary care can reduce health care costs by reducing the need for more expensive hospitalization or tertiary care (Starfield et al., 2005; Kruk et al., 2010; Baicker et al., 2004; Franks et al., 1998; Welch et al., 1993). The Government of India has invested in primary care by establishing the NHM, almost entirely focused on improving primary care. The UHC conversation in India since 2011, has renewed a call for investing in primary health care as a key strategy towards UHC (Marten et al., 2014).

This study further analyzed data from 16 states over multiple years to explore public financing flows associated with primary care. Since government primary care spending is a part of total government health spending, it is subject to similar governance and process constraints. Primary care expenditures are low and insufficient to provide an adequate level of PHC.

Normative cost estimates of primary care range from a minimum recommended $32 per capita per year to $67 per capita per year (Deolalikar et al., 2008; GoI, 2005; WHO, 2001; World Bank, 1995; Prinja et al., 2012), to cover a modest package of primary care services. Today in India the current levels of expenditure on primary care are far below the normative recommendations without even taking into account inflation and exchange rate changes. Government spending on primary care is especially low in some of the poorer states.

The figure below highlights the wide range of per capita primary care expenditure among the 16 states. There is no discernible expenditure pattern in the distribution of states in the sample. Per capita Government Primary Care Expenditure (GPCE) in Chattisgarh is more than twice that of Bihar and Karnataka, and 34 percent higher than even Kerala. This asymmetry of spending and outcomes begs for a deeper investigation. A variety of factors may explain these differences such as government priority setting, growth of the non-primary care sector in better off states, greater out-of-pocket spending on primary care, etc.

29


Study Results

Figure 20: Level of Per capita Government Primary Health Care Expenditure (GPHCE) in 2013-14

578 544 514

480 431

378 360 347 328 312 278 276 274 272

236 222

-

100

200

300

400

500

600

700

Per capita TGHE on primary care: 2013-14in nominal Rs.

Non-EAG States EAG States + Assam

The trend of the GPHCE per capita for all states in the sample shows a strong upward trajectory in nominal terms. In 2007-08, all states started off with under Rs 150 GPHCE per capita; however, in 5 years, the difference between Bihar and the rest of the states has widened substantially and seem to converge at Rs. 350. There is no significant difference between EAG and non-EAG states. Both UP and Bihar continue to lag behind among the EAG states. The EAG average has improved because of states like Chattisgarh and Rajasthan. See Figure 21.

Figure 21: Trend of GPHCE per capita

2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

Bihar 111 150 132 176 179 204 222

Uttar Pradesh 175 218 235 235 286 274

EAG 93 194 213 247 247 313 365

Non-EAG 136 179 220 260 260 355 363

All States 116 183 218 254 254 334 364

0

50

100

150

200

250

300

350

400

In N

omin

al R

s

Trend of GPHCE per capita

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Study Results

Notably, the better-off states in 2013-14 spent less on primary care as a proportion of the TGHE than the poorer states. The figure below shows, Karnataka, Punjab, Kerala spent 38 percent or less on primary care as in 2013-14 as compared to a high of 74 percent in Chhatisgarh. The high spending in the EAG states may reflect the larger share of NHM expenditures in TGHE in those 8 states. It may also represent a relatively larger share to non-primary health care related to a more developed hospital sector and higher levels of health human resources in those better-off states. See Figure 22.

Figure 22: Primary care as a share of Total Government Health Expenditure: 2013-14

74% 72% 71%65%

62% 62% 61% 58% 56%51%

48% 46%41% 38% 36%

29%

Primary care as a share of TGHE: 2013-14

Non-EAG States EAG States + Assam

However, despite the emphasis on primary care in the last 10 years, the primary care expenditure as a percent of TGHE appears to have either plateaued or on a downward trajectory for the last 3-4 years in 11 out of 16 states. See Figure 23.5 It is not clear why this may be happening. Central government support for primary health care through NHM has slowed and perhaps states are not making up the difference.

Figure 23: Declining shares of primary care expenditure as a percent of TGHE

0%10%20%30%40%50%60%70%80%90%

Assam Bihar Chattisgarh Jharkhand MP Odisha Rajasthan UP

Primary Care as a share of Total Government Health Expenditure(EAG + 1 states)

2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

Andhra P Gujarat Karnataka Kerala Maharashtra Punjab Tamil Nadu West Bengal

Primary Care as a share of Total Government Health Expenditure(Non EAG states)

2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14

Figure 24 compares the cumulative growth of TGHE and GPHCE. An impressive growth of 294 percent in the GPHCE can be observed between 2005-6 and 2013-14 in EAG states, however, it should be borne in mind that the starting point for the EAG states is much lower than most states, and while this growth is commendable, it is not sufficient to substantially reduce the health outcome disparities across the states. In the absence of central government incentives, the GPHCE in non-EAG states lagged behind the cumulative growth in TGHE. Significant disparities persist in both measures across these groups of states.

5 Declining arrows indicating downward trend; red star: lowest share of primary care among the 16 states.

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Study Results

Figure 24: Cumulative growth in GPHCE & TGHE between 2005-06 and 2013-2014

213% 201%

264%231%222%

251%

294%

220%

Bihar UP EAG+1 Non EAG

Growth in TGHE and GPHCE between 2005-06 and 2013-14

Growth in TGHE Growth in GPHCE

Key messages

• Primary care spending is very low overall and not sufficient to finance an adequate package of primary health care.

• Better off states spend a smaller proportion of their total health spending on primary care, less than 30 percent for Karnataka in 2013-14.

• Most states (11/16) in the sample show a plateaued or declining trend of primary care expenditure as a proportion of total government health, and the difference between the EAG and non-EAG states is widening over time.

• There is a 294 percent cumulative increase in the GPHCE for the EAG+1 states during the study period; state’s own growing contribution in addition to NHM has made this impressive increase possible. But it is still not sufficient to greatly reduce differences across the states.

• No discernable pattern in the distribution of GPHCE per capita among the 16 states. Per capita GPHCE expenditure in Chattisgarh (Rs 578) is more than twice of Bihar and Karnataka and higher than even Kerala or Gujarat, even though its primary health outcomes are far lower than in the better off states.

2. Central support for primary care: Stimulation or substitution

Based on available international costing norms, India is clearly not financing primary health care services at a level sufficient to provide a sizable package of services to its citizens. While the burden of financing health care is primarily placed upon the states, the central government engages in targeted grants for primary care in order to supplement state spending, especially in the poorer states. In the following section, an analysis is conducted using the multi-state panel data to obtain estimates of whether funds from the central government is acting as a substitute or stimulant of primary care spending at the state level. A recent study showed that total health expenditure experiences substitution when central government grants increase, but there exist no econometric estimates of the extent of substitution or stimulation for primary care spending in India (Rao et al, 2012). Looking specifically at

32


Study Results

the effect on primary health care spending, we find a similar trend, a one percent increase in the per capita central grants to primary health is associated with 0.292 percent reduction in subsequent investments to primary health care by each state. This substitution effect is even more pronounced in the non-EAG states.

Within Indian states, increases in funding for primary care can come from either sources internal or external to the state. Internally, increases in government spending on primary care can be a result of an increase in the overall resources of the state as tax revenues augmented by GSDP or an increase in allocation of government resources towards primary health care or both. External increases are almost entirely due to transfers from the central government directed at primary care. Official development assistance (ODA) is not a very significant part of health financing in India and much of it is channeled through central government assistance. Given this, we used available state level panel data from 2005-06 through 2013-14 in 16 sampled states to estimate the association between changes in central grants for primary care and changes states’ own spending for primary care, adjusting for changes in GSDP, ratio of total health spending to total state expenditures, and state’s own tax revenue collection. We used a model that captured the level of central allocation to primary health care in Indian Rupees in state i at time t , and measured its impact on state’s own contribution to spending on primary health care in state i at time t, according to:

stateownit=α+β1 centralit+β2

GSDPit+β3 priorityit+β4

revit+fi+dt+εit

Where centralit was the central level allocations to each state for primary health care, stateownitwas state’s own contribution to primary health care, GSDPitrepresented the per capita GSDP in each state at time t, priorityit

represented the ratio between state health spending and total state health expenditures, and revit represented each state’s own tax revenue,

jf were state fixed effects,

td were nationwide time dummies, and eit was an error term.

Fixed effects was used as the statistical method in order to control for time-invariant unobservable characteristics of each state and to estimate the coefficient of interest. The benefits of using this model was that characteristics of states that may influence the relationship between central spending on primary health and state’s own spending on primary health but were difficult to measure could be proxied through a fixed effects estimator for each state thereby eliminating across state variation which was a potential source of omitted variable bias. A limitation was that if the model did not capture all factors that influence state health spending on public health at the state level, then it could worsen remaining bias. The time dummies

td allowed for changes in state’s own health spending on public health rates over time. We estimated this equation over eight years and hence 7 one year intervals (2007-08 to 2013-14) at the level of 16 Indian states. The error term itε may be correlated over time and we therefore clustered the standard errors at the state level in our reported results. See Annex 3 for variable description.

Table 9 reports the fixed effects estimator for the relationship between the log of central allocations to primary health care and the log of each state’s own per capita primary health care investments. According to the model, a one percent increase in the per capita central grants to primary health is associated with 0.292 percent reduction in subsequent investments to primary health care by each states (p<0.05), controlling for per capita GSDP ratio of state health spending on primary health care to total health expenditures in each state; state revenues from taxes, as well as state fixed effects and time trends. How much each state prioritizes primary health care, as a ratio of total health care spending, has a significant positive impact on state’s own health care spending per capita. There is no relationship between GSDP and state revenue per capita and primary health care spending.

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Study Results

Table 9: Regression results: substitution (all states)

Log of state’s own primary health spending per capita (2005 Rs)

Log central allocations primary health spending per capita

-0.292 (0.133)**

GSDP per capita 0.0001 (0.0001)

Ratio of state health spending on PHC/total state health spending

2.497 (0.638)***

State revenue per Capita 0.0001 (0.0001)

Constant 3.306 (0.336)***

N 142

States 16

R2 0.70

* p<0.1; ** p<0.05; *** p<0.01, cluster robust standard errors in parentheses

Table 10 reports the fixed effects estimator for the relationship between the log of central allocations to primary health care and the log of each state’s own primary health care investments per capita, divided into “rich” (non- EAG) and “poor”(EAG+1) states. According to the model, a one percent increase in the per capita central grants to primary health is associated with a 0.435 percent reduction in subsequent investments to primary health care by each state (p<0.05) in “rich” states. There is no significant relationship in “poor” states.

Table 10: Regression results: substitution (rich and poor states)

Log state’s own primary health spending per capita, (2005 Rs)EAG=1 (poor)

Log state’s own primary health spending per capita, (2005 Rs)EAG=0 (rich)

Log central allocations primary health spending per capita

-0.175 (0.240) -0.435 (0.086)***

GSDP per capita 0.0001 (0.0001) 0.0001 (0.0001)

Ratio of state health spending on PHC/total state health spending

2.224 (0.892)** 3.446 (1.016)**

State revenue per capita 0.0001 (0.0001) 0.0001 (0.0001)*

Constant 2.538 (0.540)*** 3.417 (0.327)***

N 72 70

States 8 8

R2 0.62 0.85

* p<0.1; ** p<0.05; *** p<0.01, cluster robust standard errors in parentheses

In order to accurately discuss our results, it is important to note that they are subject to limitations of data availability and data quality. Our estimates are valid for the 16 states included in our sample and may not be generalizable to other states in India. By introducing a fixed effects model, we are able to control for all state level effects that are constant by year and all year level effects that are constant by state, which eliminates the burden of these types of omitted variables. However, as a result of these modeling choices, the estimated relationships should not be applied

34


Study Results

to any single state in any single year but rather be taken as a look at homogenous effects across states and years. Finally, our analysis should not be taken as the detection of a causal effect between predictors and outcome. Without randomized trial or natural experiment, we cannot confidently identify the direction of causal connection, though we believe that our findings are in line with basic economic theories as well as past research on substitution in total health expenditure as well as the fungibility of other types of aid. Bearing in mind all of the above issues, it is important to consider our key findings as a first step in exploring the fungibility of central grants to primary care.

Key messages

First, our findings suggest that after adjusting for other factors, increases in GSDP alone do not explain much of the increase in states’ own spending on primary health care. States must follow this general increase in resources with additional steps involving a decision to allocate those increased resources into health care, into primary health, and, as we have seen earlier, spend budgeted amounts effectively.

Unsurprisingly, we found that increases in states allocations to health as a percent of total state government expenditure were linked to increases in state spending for primary care. This suggests that states that put a higher priority on health spending over the previous year are also likely to have a higher level of spending on primary care specifically as compared to the previous year.

While greater priority to health may also increase spending on primary health care, it is still not sufficient to finance an adequate package. Relative differences in allocations are not sufficient to overcome absolute differences in spending capacity. Poorer states are likely to allocate more of their internal resources to health, but they are also the states that are most likely to be spending the lowest absolute amount of money of health (Rao et al, 2012). Central assistance to primary health care, focused on the poorer states, does not seem to have any effect on state’s primary health care spending. Where as in the richer states, there is a statistically significant substitution effect.

If the central government is concerned with equity and with engaging in pro-poor policies, it may need to reconsider the structures and methods through which they give money to states for primary care. This study shows on average the richer states within our sample are diverting about 4.3% away from primary health for every 10% increase in the central government grant, year over year. If this is true, it essentially mitigates the policy objective of targeted support for primary care and will not help India reach spending targets that provide a basic package of primary care to all citizens.

35


Conclusion and Policy Implications

5. Conclusion and policy implications

The RTM analysis has reiterated the fact that, government funding for health and for primary health care in India is clearly insufficient. The study highlights that low levels of resource mobilization is only part of the problem when it comes to improving the health outcomes in India. Problems in resource allocation and resource utilization also affect the adequacy of financial resources for health. Effective allocation and utilization is constrained by public financial management design, operational processes, and governance factors.

In 2005, conditions were conducive for increasing government financing for health in India with a buoyant economy. The politics was aligned in support of a big push to improve health outcomes and strengthen government health care. Looking back, repeated promises to increase health expenditure to 2-3 percent of GDP have not been realized. States did not prioritize health to same extent as the Center. The financial crisis of 2009-10 reduced fiscal space and the appetite for social spending. The total government health expenditure in the 29 states increased (nominally) by 262 percent to Rs. 873.5 million in 8 years. The central government’s investment through NHM increased substantially, but states’ own contributions did not keep pace. A result of the asymmetry in the constitutional division of power and responsibilities between central and state government contributes to their divergence on a common agenda like health. The states are responsible for ensuring the welfare of its citizen, while the center has the resources (Rao 2017). Despite some success, NHM has not sufficiently narrowed the gap in total government spending per capita or government primary care spending per capita between the non-EAG states and the EAG states.

On an average 10 percent of treasury health budgets and 15 percent of NHM budgets remained unused among all states. The budget utilization rates are typically lower for the EAG states, which further reduces their total government and primary health care expenditure. A simple simulation for one year estimated that if 100 percent of the funds available were utilized in UP and Bihar, the TGHE would increase by 26 and 49 percent respectively.

A deeper dive into causes of budget under utilization in Bihar and UP reveal that much of this underutilization can be attributed to weaknesses in governance, financial systems design, and operational capacities of the central and state governments. We observe health financing and governance problems at both ends of the resource flow spectrum that contribute to low utilization in some of the weaker states. Upstream, both GoI and state level approvals are not streamlined and are time-consuming. These delays have a cascading effect on the timing of fund releases and their use. In addition, the arbitrary manner of imposing cuts on fund releases impedes the capacity of the public health system to delivery services. Downstream, the local/community level is impaired with low capacity to fully benefit from the flexible funding; the lack of convergence of other determinants of health; and the capacity of PRIs to implement local solutions as intended by the NHM design. These impediments are mutually reinforcing at multiple levels and exacerbate underutilization. Most states have low budget reliability implying there is limited capacity to plan the resources accurately and strategically. Weaknesses in government are reflected in weak budgeting and planning capacity. The budget reliability in EAG states has in fact weakened over time.

The primary care expenditures measured in our sample of 16 states are too low to assure a decent package of services when compared with international benchmarks. The per capita primary care expenditure ranges from Rs 222 and Rs 578 (nominal) in the sample. The growth rate of primary care spending is either on the decline or plateauing in most states and the better off states spend less as a proportion of total health on primary care than worse off states. There is a 294 percent increase in GPHCE between 2005-06 and 2013-14 in the EAG+1 states, contributed largely by the states’ own funding, in addition to the NHM. No clear pattern is discernible for the distribution of GPHCE per capita among states – per capita expenditures in Assam, Chattisgarh and Rajasthan (poorer states) are higher than Karnataka, Kerala or Punjab.

36


Conclusion and Policy Implications

This study also found concerning evidence that central government funding for primary care has a substitution effect in richer states. The results show that on average the richer states within our sample are diverting about 4.3 percent away from primary health for every 10 percent increase in the grant from the central government, year over year. If the central government is concerned with equity and with engaging in pro-poor policies, it may need to reconsider the structures and methods through which they give money to states for primary care.

Significant changes in India’s fiscal and health policies are underway with the change in the central government in 2014. The central government is putting in place some fundamental changes in how funds in general are mobilized, and particularly how health care is financed and delivered. The 14th Finance Commission has increased the central tax revenue sharing ratio from 32 to 42 percent, which gives states more autonomy in their budgeting, but runs the risk of whether states will prioritize health in the absence of direct requirement and financial incentives from the central government. Abolishing the Planning Commission at the end of the 12th FYP will have implications for the prior practice of “Plan” budget allocations. The NITI Ayog, a think-tank like alternative to the Planning Commission, is expected to support more fiscal devolution while promoting cohesion around national policy goals. This approach is particularly relevant for a sector such as health where the central government makes and promotes national policy but its implementation and financing is mostly a responsibility of states. The new practice of presenting the Union Budget one month earlier in February can have a real impact on expediting budget approvals and funds releases downstream and reduce delays, one of the key contributors to underutilization of funds.

It is a positive change to see sanitation and other determinants of health being specifically targeted through initiatives like the Swachh Bharat Mission. However, sanitation alone, without the sustained investment in primary health care that the previous central government had initiated, is unlikely to be sufficient to reach the desired health outcomes. The government has also discussed new initiatives to strengthen the RSBY and increase its base as well as the basic benefits and to engage more with the private sector in service delivery. There are strong economic arguments to invest in health in India, as the “Global Health 2035” Lancet Commission findings for India estimate that a $1 investment in health will yield $10 increase in GDP by 2035 (Jamison et al, 2013).

These developments may suggest to some that the analysis reported here is no longer representative of the situation with new policies and programs in the offing. Optimism of that sort would be misplaced. The evidence from the experience of the last decade is that public financial management systems were not ready and able to capitalize on new financing opportunities, especially in the states most in need. New policies and programs may face the same challenges in new form, unless the government takes up more seriously how to get “more health for the money”. The time is ripe to reflect on a different modality on how the government should finance and administer health care to its citizens. If India wants to capitalize on its demographic dividend, investment in the health of its citizens should be a primary objective.

The supply side interventions have had only limited success so far. The key policy questions that confront the government and other stakeholders are:

• How to advocate for more funds for health overall, but more specifically, how to advocate for increased prioritization of health to a very diverse group of states. It is clear, that these advocacy messages have to be nuanced for each context.

• What processes and mechanisms should be instituted to ensure better utilization of the treasury and society budgets, including improved budget planning and management at the state and lower levels. What alternatives to the “society route” could be developed to improve use of funds?

• Investigate why GPHCE is so variable and whether this makes a difference in population health outcomes.

• What mechanisms need to be in place to enable central government funds to achieve better additionality as a means to remedy inter-state disparities in health spending?

37


Annex 1: Total Government Health Expenditure

Annex 1 Total Government Health Expenditure (in Rs million)

States 2005-06 2006-07 2007 -08 2008-09 2009-10 2010 -11 2011 -12 2012 -13 2013 -14

EAG+1 states AssamBiharChattisgarhJharkhandMadhya OdishaRajasthanUttar PradeshUttarakhand

NE States (Mean)Arunachal PradeshManipurMeghalayaMizoramNagalandSikkimTripura

Non-EAG States Andhra DelhiGoaGujaratHaryanaHimachal Jammu & KarnatakaKeralaMaharashtraPunjabTamil NaduWest Bengal

29-states (Mean)

38


Annex 2: NHM as a share of TGHE

Annex 2 NHM as a share of TGHE

States 2005-06 2006-07 2007-08 2008-09 2009-10 2010- 11 201 1- 12 2012 -13 2013- 14

EAG+1 18% 21% 28% 34% 32% 38% 34% 35% 35%Assam 19% 29% 50% 49% 38% 49% 47% 50% 40%Bihar 17% 19% 26% 56% 42% 62% 41% 45% 45%Chattisgarh 27% 35% 33% 24% 27% 31 % 35% 33% 41 %Jharkhand 14% 9% 12 % 23% 18% 27% 34% 35% 37%Madhya Pradesh 17% 26% 37% 38% 36% 36% 31% 33% 36%Odisha 25% 27% 32% 29% 40% 39% 40% 37% 35%Rajasthan 16% 20% 29% 35% 34% 36% 28% 27% 26%Uttar Pradesh 17% 15% 21 % 28% 32% 35% 27% 35% 32%Uttarakhand 11% 11% 14 % 23% 24% 25% 24% 23% 22%

NE 15% 20% 24% 29% 25% 27% 25% 24% 21 %Arunachal Pradesh 20% 21% 30% 25% 25% 26% 25% 23% 22%Manipur 17% 18% 22% 30% 25% 19% 15% 19% 16%Meghalaya 9% 15% 19% 26% 27% 26% 28% 22% 15 %Mizora m 19% 28% 40% 25% 20% 36% 34% 32% 30%Nagaland 14% 23% 24% 31% 29% 28% 31% 29% 25%Sikkim 13% 16% 18% 39% 24% 20% 13% 14% 17 %Tripura 12% 16% 18% 26% 25% 33% 27% 30% 21 %

Non-EAG 9% 11% 14 % 17% 19% 17 % 17% 18% 17 %Andhra Pradesh 13% 19% 19% 20% 20% 15 % 13% 19% 16%Delhi 3% 3% 4% 3% 4% 4% 3% 4% 4%Goa 2% 3% 4% 4% 6% 5% 7% 7% 6%Gujarat 12% 18% 21 % 26% 23% 21 % 21% 17% 18%Haryana 11% 14% 16% 22% 26% 23% 20% 21% 22%Himachal Pradesh 10% 12% 12 % 16% 22% 18% 17% 25% 13 %Jammu & Kashmir 3% 7% 8% 11% 12% 15 % 15% 16% 19%Karnataka 13% 14% 14 % 18% 26% 22% 20% 19% 17 %Kerala 10% 3% 11 % 19% 20% 17 % 14% 19% 17 %Maharas htra 10% 9% 19% 22% 23% 24% 24% 25% 22%Punjab 9% 12% 14 % 20% 21% 24% 21% 21% 20%Tamil Nadu 12% 18% 20% 20% 18% 18% 19% 17% 21 %West Bengal 12% 15% 17 % 23% 21% 21 % 21% 25% 24%

13% 16% 21 % 25% 24% 26% 24% 25% 23% Mean (29-states)

39


Annex 3: Variable Description

Annex 3 Variable DescriptionMean and Standard Deviation (in parenthesis) of Model Variables

Variable 2007 2008 2009 2010 2011 2012 20138,297.30 12,536.28 14,717.48 17,282.53 18,752.05 21,614.63 23,804.13

(5732.14) (7,459.16) (9,298.27) (10,023.38) (9,679.08) (12,860.32) (13,012.50)

(15) (16) (16) (16) (16) (16) (16)

6,999.59 9,774.51 10,725.51 11,552.37 11,632.38 12,536.70 12,921.23

(4,870.40) (5,838.36) (6,637.48) (6,690.31) (6,076.32) (7,468.70) (7,173.38)

(16) (16) (16) (16) (16) (16) (16)

123 155.35 168.27 182.13 185.93 192.8 197.9

(38.12) (43.32) (45.20) (53.80) (53.50) (57.89) (60.00)

(15) (16) (16) (16) (16) (16) (16)

3,194.50 5,352.13 6,410.66 8,090.05 7,190.31 8,024.39 9,238.73

(1942.69) (3117.14) (4134.70) (5055.04) (3762.04) (6162.27) (4156.77)

(16) (16) (16) (16) (16) (16) (16)

2,687.41 4,166.60 4,660.68 5,384.34 4,457.69 4,643.33 4,994.65

(1640.93) (2402.02) (2912.97) (3308.59) (2360.11) (3536.42) (2252.67)

(16) (16) (16) (16) (16) (16) (16)

46.4 66.35 73.6 84.72 72.7 70.86 80.2

(30.72) (29.52) (29.67) (35.61) (29.82) (37.93) (29.65)

(16) (16) (16) (16) (16) (16) (16)

6210.27 8369.68 10056.81 11898.19 14294.36 16971.3 18809.48

(4214.24) (5383.83) (6525.93) (7088.05) (7594.58) (9706.82) (10879.19)

(15) (16) (16) (16) (16) (16) (16)

4826.05 5607.91 6064.83 6168.03 7174.69 7893.37 7926.58

(3437.39) (3833.10) (3939.00) (3935.84) (4026.31) (4462.81) (5080.00)

(15) (16) (16) (16) (16) (16) (16)

76.28 89 94.67 97.41 113.24 121.94 117.7

(22.79) (29.28) (27.16) (32.15) (34.28) (34.95) (37.04)

(15) (16) (16) (16) (16) (16) (16)

1.95 2.07 2.24 2.45 2.6 2.76 2.95

(1.37) (1.41) (1.54) (1.72) (1.80) (1.93) (2.07)

(16) (16) (16) (16) (16) (16) (16)

0.032 0.033 0.035 0.038 0.04 0.042 0.044

(0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02)

(16) (16) (16) (16) (16) (16) (16)

12,937.34 16,838.83 19,118.59 20,783.78 21,353.65 23,072.48 24,547.76

(8517.04) (9405.95) (10839.28) (11555.79) (10739.28) (12395.74) (12766.37)

(16) (16) (16) (16) (16) (16) (16)

0.53 0.59 0.57 0.58 0.57 0.56 0.54

(0.20) (0.13) (0.12) (0.14) (0.14) (0.15) (0.14)

(16) (16) (16) (16) (16) (16) (16)

145,731.15 149,659.63 155,997.86 179,847.59 200,558.94 225,728.09 240,657.35

(108661.22) (107847.91) (111596.80) (133166.32) (147488.24) (163808.23) (170782.46)

(14) (16) (16) (16) (16) (16) (16)

2,261.65 2,377.69 2,445.74 2,793.02 3,078.04 3,439.39 3,621.35

(1185.59) (1237.09) (1226.07) (1509.09) (1643.17) (1848.99) (1901.56)

(14) (16) (16) (16) (16) (16) (16)

65,205,313 66,115,375 67,015,500 67,905,813 68,786,250 69,656,938 70,517,750

(41314683.00) (42080400.00) (42848511.00) (43616137.00) (44380155.00) (45142351.00) (45905117.00)

(16) (16) (16) (16) (16) (16) (16)

State Primary Health Spending,

Rs. millions (Nominal)

State Primary Health Spending,

millions (2005 Rs)

State Primary Health Spending

per capita, (2005 Rs)

Central Primary Health

Spending, Rs millions (Nominal)

Central Primary Health

Spending, millions (2005 Rs)

Central Primary Health Spending

per capita, (2005 Rs)

State’s Own Contribution to

Primary Health Spending Rs

millions (Nominal)

Ratio State Health Spending on

PHC/Total State Health Spending

State Own Revenue, millions

(2005 Rs)

State Revenue per Capital, (2005

Rs)

Population

State’s Own Contribution to

Primary Health Spending,

millions (2005 Rs)

State’s Own contribution to

Primary Health Spending Per

capita (2005 Rs)

GDSP, millions (2005 Rs)

GDSP per capita, (2005 Rs)

Total State Health Spending,

millions (2005 Rs)

40


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