Page 1
CHAPTER
09
Of all the forms of inequality, injustice in healthcare is the most shocking and
most inhuman.
—Martin Luther King Jr.
This chapter demonstrates strong positive effects on healthcare outcomes of the Pradhan
Mantri Jan Arogya Yojana (PM-JAY) – the ambitious program launched by Government
of India in 2018 to provide healthcare access to the most vulnerable sections. PM-JAY is
being used significantly for high frequency, low cost care such as dialysis and continued
to be utilised without disruption even during the Covid pandemic and the lockdown.
General medicine – the overwhelmingly major clinical specialty accounting for over half
the claims - exhibited a V-shaped recovery after falling during the lockdown and reached
pre-COVID-19 levels in December 2020. The final – but the most crucial – analysis in the
chapter attempts to estimate the impact of PM-JAY on health utcomes by undertaking a
difference-in-difference analysis. As PM-JAY was implemented in 2018, health indicators
measured by National Family Health Surveys 4 (in 2015-16) and 5 (in 2019-20) provide
before-after data to assess this impact. To mitigate the impact of various confounding
factors, we compute a difference-in-difference by comparing states that implemented PM-
JAY versus those that did not. We undertake this analysis in two parts. First, we use
West Bengal as the state that did not implement PM-JAY and compare its neighbouring
states that implemented PM-JAY – Bihar, Sikkim and Assam. Second, we repeat the same
analysis for all states that did not implement PM-JAY vis-à-vis all states that did.
PM-JAY enhanced health insurance coverage. Across all the states, the proportion of
households with health insurance increased by 54 per cent for the states that implemented
PM-JAY while falling by 10 per cent in states that did not. Similarly, the proportion of
households that had health insurance increased in Bihar, Assam and Sikkim from 2015-16
to 2019-20 by 89 per cent while it decreased by 12 per cent over the same period in West
Bengal. From 2015-16 to 2019-20, infant mortality rates declined by 12 per cent for states
that did not adopt PM-JAY and by 20 per cent for the states that adopted it. Similarly,
while states that did not adopt PM-JAY saw a fall of 14 per cent in its Under-5 mortality
rate, the states that adopted it witnessed a 19 per cent reduction. While states that did not
adopt PM-JAY witness 15 per cent decline in unmet need for spacing between consecutive
kids, the states that adopted it recorded a 31 per cent fall. Various metrics for mother and
child care improved more in the states that adopted PM-JAY as compared to those who
did not. Each of these health effects manifested similarly when we compare Bihar, Assam
and Sikkim that implemented PM-JAY versus West Bengal that did not. While some of
JAY Ho: Ayushman Bharat's Jan
Arogya Yojana (JAY) and Health
Outcomes
Page 2
CHAPTER
09
Of all the forms of inequality, injustice in healthcare is the most shocking and
most inhuman.
—Martin Luther King Jr.
This chapter demonstrates strong positive effects on healthcare outcomes of the Pradhan
Mantri Jan Arogya Yojana (PM-JAY) – the ambitious program launched by Government
of India in 2018 to provide healthcare access to the most vulnerable sections. PM-JAY is
being used significantly for high frequency, low cost care such as dialysis and continued
to be utilised without disruption even during the Covid pandemic and the lockdown.
General medicine – the overwhelmingly major clinical specialty accounting for over half
the claims - exhibited a V-shaped recovery after falling during the lockdown and reached
pre-COVID-19 levels in December 2020. The final – but the most crucial – analysis in the
chapter attempts to estimate the impact of PM-JAY on health utcomes by undertaking a
difference-in-difference analysis. As PM-JAY was implemented in 2018, health indicators
measured by National Family Health Surveys 4 (in 2015-16) and 5 (in 2019-20) provide
before-after data to assess this impact. To mitigate the impact of various confounding
factors, we compute a difference-in-difference by comparing states that implemented PM-
JAY versus those that did not. We undertake this analysis in two parts. First, we use
West Bengal as the state that did not implement PM-JAY and compare its neighbouring
states that implemented PM-JAY – Bihar, Sikkim and Assam. Second, we repeat the same
analysis for all states that did not implement PM-JAY vis-à-vis all states that did.
PM-JAY enhanced health insurance coverage. Across all the states, the proportion of
households with health insurance increased by 54 per cent for the states that implemented
PM-JAY while falling by 10 per cent in states that did not. Similarly, the proportion of
households that had health insurance increased in Bihar, Assam and Sikkim from 2015-16
to 2019-20 by 89 per cent while it decreased by 12 per cent over the same period in West
Bengal. From 2015-16 to 2019-20, infant mortality rates declined by 12 per cent for states
that did not adopt PM-JAY and by 20 per cent for the states that adopted it. Similarly,
while states that did not adopt PM-JAY saw a fall of 14 per cent in its Under-5 mortality
rate, the states that adopted it witnessed a 19 per cent reduction. While states that did not
adopt PM-JAY witness 15 per cent decline in unmet need for spacing between consecutive
kids, the states that adopted it recorded a 31 per cent fall. Various metrics for mother and
child care improved more in the states that adopted PM-JAY as compared to those who
did not. Each of these health effects manifested similarly when we compare Bihar, Assam
and Sikkim that implemented PM-JAY versus West Bengal that did not. While some of
JAY Ho: Ayushman Bharat's Jan
Arogya Yojana (JAY) and Health
Outcomes
287 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
INTRODUCTION
9.1 As free markets under-provision public goods, a vital role of a government is to provide
public goods to its citizens, especially to the vulnerable sections in a society. While the rich can
seek private alternatives, lobby for better services, or if need be, move to areas where public
goods are better provided for, the poor rarely have such choices (Besley and Ghatak, 2004). Thus,
provision of public goods can particularly affect the quality of living of the vulnerable sections
in a society. Yet, governments may suffer from the “horizon problem” in a democracy, where
the time horizon over which the benefits of public goods reach the electorate may be longer than
the electoral cycles (Keefer 2007 and Keefer and Vlaicu 2007). The myopia resulting from the
horizon problem may again lead to under-provisioning of public goods. Therefore, the provision
of public goods that generate long-term gains to the economy and the society represents a key
aspect of governance in a democratic polity.
9.2 As healthcare represents a critical public good, successive governments have committed
to achieve universal health coverage (UHC). However, until 2018, UHC remained an elusive
dream. In 2018, Government of India approved the A yushman Bharat Pradhan Mantri Jan Arogya
Yojana (AB-PM-JAY) as a historic step to provide healthcare access to the most vulnerable
sections in the country. Beneficiaries included approximately 50 crore individuals across 10.74
crores poor and vulnerable families, which form the bottom 40 per cent of the Indian population.
The households were included based on the deprivation and occupational criteria from the
Socio-Economic Caste Census 2011 (SECC 2011) for rural and urban areas respectively. The
scheme provides for healthcare of up to INR 5 lakh per family per year on a family floater basis,
which means that it can be used by one or all members of the family. The scheme provides
for secondary and tertiary hospitalization through a network of public and empanelled private
healthcare providers. It also provides for three days of pre-hospitalization and 15 days of post-
hospitalization expenses, places no cap on age and gender, or size of a family and is portable
across the country. It covers 1573 procedures including 23 specialties (see Box 1 for details).
AB-PM-JAY also aims to set up 150,000 health and wellness centres to provide comprehensive
primary health care service to the entire population.
9.3 The evidence provided in this chapter shows strong positive effects of PM-JAY on
healthcare outcomes despite the short time since introduction of the programme. First, PM-
JAY is being used significantly for high frequency and low cost care consisting with the general
utilisation of healthcare services. Using the distribution of claims, we find that the distribution
is a long-tailed one that peaks in the range of INR 10,000-15,000. The highest number of pre-
authorization claims received were for procedures that cost in this range. The distribution is
heavily right-tailed indicating significantly fewer claims for more expensive procedures.
these effects stemmed directly from enhanced care enabled by insurance coverage, others
represent spillover effects due to the same. Overall, the comparison reflects significant
improvements in several health outcomes in states that implemented PM-JAY versus those
that did not. As the difference-in-difference analysis controls for confounding factors, the
Survey infers that PM-JAY has a positive impact on health outcomes.
Page 3
CHAPTER
09
Of all the forms of inequality, injustice in healthcare is the most shocking and
most inhuman.
—Martin Luther King Jr.
This chapter demonstrates strong positive effects on healthcare outcomes of the Pradhan
Mantri Jan Arogya Yojana (PM-JAY) – the ambitious program launched by Government
of India in 2018 to provide healthcare access to the most vulnerable sections. PM-JAY is
being used significantly for high frequency, low cost care such as dialysis and continued
to be utilised without disruption even during the Covid pandemic and the lockdown.
General medicine – the overwhelmingly major clinical specialty accounting for over half
the claims - exhibited a V-shaped recovery after falling during the lockdown and reached
pre-COVID-19 levels in December 2020. The final – but the most crucial – analysis in the
chapter attempts to estimate the impact of PM-JAY on health utcomes by undertaking a
difference-in-difference analysis. As PM-JAY was implemented in 2018, health indicators
measured by National Family Health Surveys 4 (in 2015-16) and 5 (in 2019-20) provide
before-after data to assess this impact. To mitigate the impact of various confounding
factors, we compute a difference-in-difference by comparing states that implemented PM-
JAY versus those that did not. We undertake this analysis in two parts. First, we use
West Bengal as the state that did not implement PM-JAY and compare its neighbouring
states that implemented PM-JAY – Bihar, Sikkim and Assam. Second, we repeat the same
analysis for all states that did not implement PM-JAY vis-à-vis all states that did.
PM-JAY enhanced health insurance coverage. Across all the states, the proportion of
households with health insurance increased by 54 per cent for the states that implemented
PM-JAY while falling by 10 per cent in states that did not. Similarly, the proportion of
households that had health insurance increased in Bihar, Assam and Sikkim from 2015-16
to 2019-20 by 89 per cent while it decreased by 12 per cent over the same period in West
Bengal. From 2015-16 to 2019-20, infant mortality rates declined by 12 per cent for states
that did not adopt PM-JAY and by 20 per cent for the states that adopted it. Similarly,
while states that did not adopt PM-JAY saw a fall of 14 per cent in its Under-5 mortality
rate, the states that adopted it witnessed a 19 per cent reduction. While states that did not
adopt PM-JAY witness 15 per cent decline in unmet need for spacing between consecutive
kids, the states that adopted it recorded a 31 per cent fall. Various metrics for mother and
child care improved more in the states that adopted PM-JAY as compared to those who
did not. Each of these health effects manifested similarly when we compare Bihar, Assam
and Sikkim that implemented PM-JAY versus West Bengal that did not. While some of
JAY Ho: Ayushman Bharat's Jan
Arogya Yojana (JAY) and Health
Outcomes
287 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
INTRODUCTION
9.1 As free markets under-provision public goods, a vital role of a government is to provide
public goods to its citizens, especially to the vulnerable sections in a society. While the rich can
seek private alternatives, lobby for better services, or if need be, move to areas where public
goods are better provided for, the poor rarely have such choices (Besley and Ghatak, 2004). Thus,
provision of public goods can particularly affect the quality of living of the vulnerable sections
in a society. Yet, governments may suffer from the “horizon problem” in a democracy, where
the time horizon over which the benefits of public goods reach the electorate may be longer than
the electoral cycles (Keefer 2007 and Keefer and Vlaicu 2007). The myopia resulting from the
horizon problem may again lead to under-provisioning of public goods. Therefore, the provision
of public goods that generate long-term gains to the economy and the society represents a key
aspect of governance in a democratic polity.
9.2 As healthcare represents a critical public good, successive governments have committed
to achieve universal health coverage (UHC). However, until 2018, UHC remained an elusive
dream. In 2018, Government of India approved the A yushman Bharat Pradhan Mantri Jan Arogya
Yojana (AB-PM-JAY) as a historic step to provide healthcare access to the most vulnerable
sections in the country. Beneficiaries included approximately 50 crore individuals across 10.74
crores poor and vulnerable families, which form the bottom 40 per cent of the Indian population.
The households were included based on the deprivation and occupational criteria from the
Socio-Economic Caste Census 2011 (SECC 2011) for rural and urban areas respectively. The
scheme provides for healthcare of up to INR 5 lakh per family per year on a family floater basis,
which means that it can be used by one or all members of the family. The scheme provides
for secondary and tertiary hospitalization through a network of public and empanelled private
healthcare providers. It also provides for three days of pre-hospitalization and 15 days of post-
hospitalization expenses, places no cap on age and gender, or size of a family and is portable
across the country. It covers 1573 procedures including 23 specialties (see Box 1 for details).
AB-PM-JAY also aims to set up 150,000 health and wellness centres to provide comprehensive
primary health care service to the entire population.
9.3 The evidence provided in this chapter shows strong positive effects of PM-JAY on
healthcare outcomes despite the short time since introduction of the programme. First, PM-
JAY is being used significantly for high frequency and low cost care consisting with the general
utilisation of healthcare services. Using the distribution of claims, we find that the distribution
is a long-tailed one that peaks in the range of INR 10,000-15,000. The highest number of pre-
authorization claims received were for procedures that cost in this range. The distribution is
heavily right-tailed indicating significantly fewer claims for more expensive procedures.
these effects stemmed directly from enhanced care enabled by insurance coverage, others
represent spillover effects due to the same. Overall, the comparison reflects significant
improvements in several health outcomes in states that implemented PM-JAY versus those
that did not. As the difference-in-difference analysis controls for confounding factors, the
Survey infers that PM-JAY has a positive impact on health outcomes.
288 Economic Survey 2020-21 V olume 1
9.4 Second, general medicine has been the overwhelmingly major clinical specialty used
since 2018 with its share continuously growing. It is followed by general surgery, obstetrics
and gynaecology. These three categories combine to account for more than half of the claims
received on average. Dialysis – high frequency, low cost procedure that is life-saving for patients
with renal difficulties – accounts for a large chunk (30 per cent) of the general medicine category
claims under PM-JAY .
9.5 Third, the claims for dialysis did not diminish due to Co VID-19 or because of the lockdown
in March-April 2020 even while we can observe a steep fall in claims under the overall general
medicine category during the lockdown. This highlights the users’ reliance on PM-JAY for the
life-saving dialysis procedure. Thus, the critical, life-saving health procedures such as dialysis
seem to have not been severely affected during the Co VID-19 pandemic.
9.6 Fourth, general care-seeking as seen in the PM-JAY claims exhibited a V-shaped recovery
after falling during the lockdown and has reached the pre-Co VID-19 levels in December 2020.
9.7 The final, but the most crucial, analysis in the chapter attempts to estimate the impact of
PM-JAY on health outcomes by undertaking a difference-in-difference analysis. We compare
the health indicators measured by National Family Health Survey 4 (NFHS 2015-16) and the
National Family Health Survey 5 (NFHS 2019-20) to undertake this analysis. As PM-JAY was
implemented in 2018, these two surveys provide before-after data to assess the impact of PM-
JAY with the NFHS-4 serving as the baseline to compare the changes using NFHS-5. To mitigate
the impact of various confounding factors, including but not limited to secular improvements in
health indicators across the country, we undertake this analysis by calculating a difference-in-
difference.
9.8 This analysis is undertaken in two parts. In the first part, we use West Bengal as the state
that did not implement PM-JAY and compare the before-after difference in health outcomes to
its neighbouring states that have implemented PM-JAY – Bihar, Sikkim and Assam. Apart from
all these states being contiguous to each other and therefore being similar on socio-economic
dimensions, we show that the baseline characteristics of these two groups of states were similar.
In the second part, we repeat the same analysis for all states that did not implement PM-JAY
vis-à-vis all states that implemented PM-JAY. o f course, the heterogeneity across the entire
group of states in the country is large. The second analysis is less of a like-for-like comparison
than the first one. Combining the findings from both these comparisons ensures that the findings
are robust not only to a more localised, and therefore, more careful comparison but also to a
comparison that spans all the major states in the country. The findings from this analysis are
summarised as follows:
1. The proportion of households that had health insurance increased in Bihar, Assam and
Sikkim from 2015-16 to 2019-20 by 89 per cent while it decreased by 12 per cent over the
same period in West Bengal. When comparing across all the states over this time period, we
find that the proportion of households with health insurance increased by 54 per cent for the
states that implemented PM-JAY while falling by 10 per cent in the states that did not adopt
PM-JAY . Thus, PM-JAY enhanced health insurance coverage.
2. From 2015-16 to 2019-20, infant mortality rates declined by 20 per cent for West Bengal and
by 28 per cent for the three neighbouring states. Similarly, while Bengal saw a fall of 20 per
cent in its Under-5 mortality rate, the neighbours witnessed a 27 per cent reduction. Thus,
Page 4
CHAPTER
09
Of all the forms of inequality, injustice in healthcare is the most shocking and
most inhuman.
—Martin Luther King Jr.
This chapter demonstrates strong positive effects on healthcare outcomes of the Pradhan
Mantri Jan Arogya Yojana (PM-JAY) – the ambitious program launched by Government
of India in 2018 to provide healthcare access to the most vulnerable sections. PM-JAY is
being used significantly for high frequency, low cost care such as dialysis and continued
to be utilised without disruption even during the Covid pandemic and the lockdown.
General medicine – the overwhelmingly major clinical specialty accounting for over half
the claims - exhibited a V-shaped recovery after falling during the lockdown and reached
pre-COVID-19 levels in December 2020. The final – but the most crucial – analysis in the
chapter attempts to estimate the impact of PM-JAY on health utcomes by undertaking a
difference-in-difference analysis. As PM-JAY was implemented in 2018, health indicators
measured by National Family Health Surveys 4 (in 2015-16) and 5 (in 2019-20) provide
before-after data to assess this impact. To mitigate the impact of various confounding
factors, we compute a difference-in-difference by comparing states that implemented PM-
JAY versus those that did not. We undertake this analysis in two parts. First, we use
West Bengal as the state that did not implement PM-JAY and compare its neighbouring
states that implemented PM-JAY – Bihar, Sikkim and Assam. Second, we repeat the same
analysis for all states that did not implement PM-JAY vis-à-vis all states that did.
PM-JAY enhanced health insurance coverage. Across all the states, the proportion of
households with health insurance increased by 54 per cent for the states that implemented
PM-JAY while falling by 10 per cent in states that did not. Similarly, the proportion of
households that had health insurance increased in Bihar, Assam and Sikkim from 2015-16
to 2019-20 by 89 per cent while it decreased by 12 per cent over the same period in West
Bengal. From 2015-16 to 2019-20, infant mortality rates declined by 12 per cent for states
that did not adopt PM-JAY and by 20 per cent for the states that adopted it. Similarly,
while states that did not adopt PM-JAY saw a fall of 14 per cent in its Under-5 mortality
rate, the states that adopted it witnessed a 19 per cent reduction. While states that did not
adopt PM-JAY witness 15 per cent decline in unmet need for spacing between consecutive
kids, the states that adopted it recorded a 31 per cent fall. Various metrics for mother and
child care improved more in the states that adopted PM-JAY as compared to those who
did not. Each of these health effects manifested similarly when we compare Bihar, Assam
and Sikkim that implemented PM-JAY versus West Bengal that did not. While some of
JAY Ho: Ayushman Bharat's Jan
Arogya Yojana (JAY) and Health
Outcomes
287 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
INTRODUCTION
9.1 As free markets under-provision public goods, a vital role of a government is to provide
public goods to its citizens, especially to the vulnerable sections in a society. While the rich can
seek private alternatives, lobby for better services, or if need be, move to areas where public
goods are better provided for, the poor rarely have such choices (Besley and Ghatak, 2004). Thus,
provision of public goods can particularly affect the quality of living of the vulnerable sections
in a society. Yet, governments may suffer from the “horizon problem” in a democracy, where
the time horizon over which the benefits of public goods reach the electorate may be longer than
the electoral cycles (Keefer 2007 and Keefer and Vlaicu 2007). The myopia resulting from the
horizon problem may again lead to under-provisioning of public goods. Therefore, the provision
of public goods that generate long-term gains to the economy and the society represents a key
aspect of governance in a democratic polity.
9.2 As healthcare represents a critical public good, successive governments have committed
to achieve universal health coverage (UHC). However, until 2018, UHC remained an elusive
dream. In 2018, Government of India approved the A yushman Bharat Pradhan Mantri Jan Arogya
Yojana (AB-PM-JAY) as a historic step to provide healthcare access to the most vulnerable
sections in the country. Beneficiaries included approximately 50 crore individuals across 10.74
crores poor and vulnerable families, which form the bottom 40 per cent of the Indian population.
The households were included based on the deprivation and occupational criteria from the
Socio-Economic Caste Census 2011 (SECC 2011) for rural and urban areas respectively. The
scheme provides for healthcare of up to INR 5 lakh per family per year on a family floater basis,
which means that it can be used by one or all members of the family. The scheme provides
for secondary and tertiary hospitalization through a network of public and empanelled private
healthcare providers. It also provides for three days of pre-hospitalization and 15 days of post-
hospitalization expenses, places no cap on age and gender, or size of a family and is portable
across the country. It covers 1573 procedures including 23 specialties (see Box 1 for details).
AB-PM-JAY also aims to set up 150,000 health and wellness centres to provide comprehensive
primary health care service to the entire population.
9.3 The evidence provided in this chapter shows strong positive effects of PM-JAY on
healthcare outcomes despite the short time since introduction of the programme. First, PM-
JAY is being used significantly for high frequency and low cost care consisting with the general
utilisation of healthcare services. Using the distribution of claims, we find that the distribution
is a long-tailed one that peaks in the range of INR 10,000-15,000. The highest number of pre-
authorization claims received were for procedures that cost in this range. The distribution is
heavily right-tailed indicating significantly fewer claims for more expensive procedures.
these effects stemmed directly from enhanced care enabled by insurance coverage, others
represent spillover effects due to the same. Overall, the comparison reflects significant
improvements in several health outcomes in states that implemented PM-JAY versus those
that did not. As the difference-in-difference analysis controls for confounding factors, the
Survey infers that PM-JAY has a positive impact on health outcomes.
288 Economic Survey 2020-21 V olume 1
9.4 Second, general medicine has been the overwhelmingly major clinical specialty used
since 2018 with its share continuously growing. It is followed by general surgery, obstetrics
and gynaecology. These three categories combine to account for more than half of the claims
received on average. Dialysis – high frequency, low cost procedure that is life-saving for patients
with renal difficulties – accounts for a large chunk (30 per cent) of the general medicine category
claims under PM-JAY .
9.5 Third, the claims for dialysis did not diminish due to Co VID-19 or because of the lockdown
in March-April 2020 even while we can observe a steep fall in claims under the overall general
medicine category during the lockdown. This highlights the users’ reliance on PM-JAY for the
life-saving dialysis procedure. Thus, the critical, life-saving health procedures such as dialysis
seem to have not been severely affected during the Co VID-19 pandemic.
9.6 Fourth, general care-seeking as seen in the PM-JAY claims exhibited a V-shaped recovery
after falling during the lockdown and has reached the pre-Co VID-19 levels in December 2020.
9.7 The final, but the most crucial, analysis in the chapter attempts to estimate the impact of
PM-JAY on health outcomes by undertaking a difference-in-difference analysis. We compare
the health indicators measured by National Family Health Survey 4 (NFHS 2015-16) and the
National Family Health Survey 5 (NFHS 2019-20) to undertake this analysis. As PM-JAY was
implemented in 2018, these two surveys provide before-after data to assess the impact of PM-
JAY with the NFHS-4 serving as the baseline to compare the changes using NFHS-5. To mitigate
the impact of various confounding factors, including but not limited to secular improvements in
health indicators across the country, we undertake this analysis by calculating a difference-in-
difference.
9.8 This analysis is undertaken in two parts. In the first part, we use West Bengal as the state
that did not implement PM-JAY and compare the before-after difference in health outcomes to
its neighbouring states that have implemented PM-JAY – Bihar, Sikkim and Assam. Apart from
all these states being contiguous to each other and therefore being similar on socio-economic
dimensions, we show that the baseline characteristics of these two groups of states were similar.
In the second part, we repeat the same analysis for all states that did not implement PM-JAY
vis-à-vis all states that implemented PM-JAY. o f course, the heterogeneity across the entire
group of states in the country is large. The second analysis is less of a like-for-like comparison
than the first one. Combining the findings from both these comparisons ensures that the findings
are robust not only to a more localised, and therefore, more careful comparison but also to a
comparison that spans all the major states in the country. The findings from this analysis are
summarised as follows:
1. The proportion of households that had health insurance increased in Bihar, Assam and
Sikkim from 2015-16 to 2019-20 by 89 per cent while it decreased by 12 per cent over the
same period in West Bengal. When comparing across all the states over this time period, we
find that the proportion of households with health insurance increased by 54 per cent for the
states that implemented PM-JAY while falling by 10 per cent in the states that did not adopt
PM-JAY . Thus, PM-JAY enhanced health insurance coverage.
2. From 2015-16 to 2019-20, infant mortality rates declined by 20 per cent for West Bengal and
by 28 per cent for the three neighbouring states. Similarly, while Bengal saw a fall of 20 per
cent in its Under-5 mortality rate, the neighbours witnessed a 27 per cent reduction. Thus,
289 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
the neighbouring states witnessed 7-8 per cent greater reduction in these health outcomes.
3. Modern methods of contraception, female sterilization and pill usage went up by 36 per
cent, 22 per cent and 28 per cent respectively in the three neighbouring states while the
respective changes for West Bengal were negligible. While West Bengal did not witness any
significant decline in unmet need for spacing between consecutive kids, the neighbouring
three states recorded a 37 per cent fall.
4. Various metrics for mother and child care improved more in the three neighbouring states
than in West Bengal.
5. Each of the effects described above (points 2-4) manifested similarly when we compare all
states that implemented PM-JAY versus the states that did not.
9.9 Overall, the comparison reflects significant improvements in several health outcomes
in states that implemented PM-JAY versus those that did not. As the difference-in-differnce
analysis controls for various compounding factors, the Survey infers that PMJAY impacted
health outcomes positively.
PM-JAY: STATUS AND PROGRESS SO FAR
9.10 As per the latest annual report of PM-JAY released by the National Health Authority
(NHA, 2019), the status of implementation is as follows:
- 32 states and UTs implement the scheme
- 13.48 crore E-cards have been issued
- Treatments worth INR 7,490 crore have been provided (1.55 crores hospital admission)
- 24,215 hospitals empaneled
- 1.5 crore users have registered on the scheme’s website (mera.pmjay.gov.in)
Figure 1: The distribution in utilization of various procedures
Source: NHA data secured from PMJAY
9.11 Figure 1 plots the number of PM-JAY pre-authorizations claims for a procedure against
the average price of the procedure for the time period September 2018 through January 2021
(till January 13, 2021). The distribution is a long-tailed one that peaks in the range of INR
10,000-15,000. The highest number of pre-authorization claims received were for procedures
Page 5
CHAPTER
09
Of all the forms of inequality, injustice in healthcare is the most shocking and
most inhuman.
—Martin Luther King Jr.
This chapter demonstrates strong positive effects on healthcare outcomes of the Pradhan
Mantri Jan Arogya Yojana (PM-JAY) – the ambitious program launched by Government
of India in 2018 to provide healthcare access to the most vulnerable sections. PM-JAY is
being used significantly for high frequency, low cost care such as dialysis and continued
to be utilised without disruption even during the Covid pandemic and the lockdown.
General medicine – the overwhelmingly major clinical specialty accounting for over half
the claims - exhibited a V-shaped recovery after falling during the lockdown and reached
pre-COVID-19 levels in December 2020. The final – but the most crucial – analysis in the
chapter attempts to estimate the impact of PM-JAY on health utcomes by undertaking a
difference-in-difference analysis. As PM-JAY was implemented in 2018, health indicators
measured by National Family Health Surveys 4 (in 2015-16) and 5 (in 2019-20) provide
before-after data to assess this impact. To mitigate the impact of various confounding
factors, we compute a difference-in-difference by comparing states that implemented PM-
JAY versus those that did not. We undertake this analysis in two parts. First, we use
West Bengal as the state that did not implement PM-JAY and compare its neighbouring
states that implemented PM-JAY – Bihar, Sikkim and Assam. Second, we repeat the same
analysis for all states that did not implement PM-JAY vis-à-vis all states that did.
PM-JAY enhanced health insurance coverage. Across all the states, the proportion of
households with health insurance increased by 54 per cent for the states that implemented
PM-JAY while falling by 10 per cent in states that did not. Similarly, the proportion of
households that had health insurance increased in Bihar, Assam and Sikkim from 2015-16
to 2019-20 by 89 per cent while it decreased by 12 per cent over the same period in West
Bengal. From 2015-16 to 2019-20, infant mortality rates declined by 12 per cent for states
that did not adopt PM-JAY and by 20 per cent for the states that adopted it. Similarly,
while states that did not adopt PM-JAY saw a fall of 14 per cent in its Under-5 mortality
rate, the states that adopted it witnessed a 19 per cent reduction. While states that did not
adopt PM-JAY witness 15 per cent decline in unmet need for spacing between consecutive
kids, the states that adopted it recorded a 31 per cent fall. Various metrics for mother and
child care improved more in the states that adopted PM-JAY as compared to those who
did not. Each of these health effects manifested similarly when we compare Bihar, Assam
and Sikkim that implemented PM-JAY versus West Bengal that did not. While some of
JAY Ho: Ayushman Bharat's Jan
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287 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
INTRODUCTION
9.1 As free markets under-provision public goods, a vital role of a government is to provide
public goods to its citizens, especially to the vulnerable sections in a society. While the rich can
seek private alternatives, lobby for better services, or if need be, move to areas where public
goods are better provided for, the poor rarely have such choices (Besley and Ghatak, 2004). Thus,
provision of public goods can particularly affect the quality of living of the vulnerable sections
in a society. Yet, governments may suffer from the “horizon problem” in a democracy, where
the time horizon over which the benefits of public goods reach the electorate may be longer than
the electoral cycles (Keefer 2007 and Keefer and Vlaicu 2007). The myopia resulting from the
horizon problem may again lead to under-provisioning of public goods. Therefore, the provision
of public goods that generate long-term gains to the economy and the society represents a key
aspect of governance in a democratic polity.
9.2 As healthcare represents a critical public good, successive governments have committed
to achieve universal health coverage (UHC). However, until 2018, UHC remained an elusive
dream. In 2018, Government of India approved the A yushman Bharat Pradhan Mantri Jan Arogya
Yojana (AB-PM-JAY) as a historic step to provide healthcare access to the most vulnerable
sections in the country. Beneficiaries included approximately 50 crore individuals across 10.74
crores poor and vulnerable families, which form the bottom 40 per cent of the Indian population.
The households were included based on the deprivation and occupational criteria from the
Socio-Economic Caste Census 2011 (SECC 2011) for rural and urban areas respectively. The
scheme provides for healthcare of up to INR 5 lakh per family per year on a family floater basis,
which means that it can be used by one or all members of the family. The scheme provides
for secondary and tertiary hospitalization through a network of public and empanelled private
healthcare providers. It also provides for three days of pre-hospitalization and 15 days of post-
hospitalization expenses, places no cap on age and gender, or size of a family and is portable
across the country. It covers 1573 procedures including 23 specialties (see Box 1 for details).
AB-PM-JAY also aims to set up 150,000 health and wellness centres to provide comprehensive
primary health care service to the entire population.
9.3 The evidence provided in this chapter shows strong positive effects of PM-JAY on
healthcare outcomes despite the short time since introduction of the programme. First, PM-
JAY is being used significantly for high frequency and low cost care consisting with the general
utilisation of healthcare services. Using the distribution of claims, we find that the distribution
is a long-tailed one that peaks in the range of INR 10,000-15,000. The highest number of pre-
authorization claims received were for procedures that cost in this range. The distribution is
heavily right-tailed indicating significantly fewer claims for more expensive procedures.
these effects stemmed directly from enhanced care enabled by insurance coverage, others
represent spillover effects due to the same. Overall, the comparison reflects significant
improvements in several health outcomes in states that implemented PM-JAY versus those
that did not. As the difference-in-difference analysis controls for confounding factors, the
Survey infers that PM-JAY has a positive impact on health outcomes.
288 Economic Survey 2020-21 V olume 1
9.4 Second, general medicine has been the overwhelmingly major clinical specialty used
since 2018 with its share continuously growing. It is followed by general surgery, obstetrics
and gynaecology. These three categories combine to account for more than half of the claims
received on average. Dialysis – high frequency, low cost procedure that is life-saving for patients
with renal difficulties – accounts for a large chunk (30 per cent) of the general medicine category
claims under PM-JAY .
9.5 Third, the claims for dialysis did not diminish due to Co VID-19 or because of the lockdown
in March-April 2020 even while we can observe a steep fall in claims under the overall general
medicine category during the lockdown. This highlights the users’ reliance on PM-JAY for the
life-saving dialysis procedure. Thus, the critical, life-saving health procedures such as dialysis
seem to have not been severely affected during the Co VID-19 pandemic.
9.6 Fourth, general care-seeking as seen in the PM-JAY claims exhibited a V-shaped recovery
after falling during the lockdown and has reached the pre-Co VID-19 levels in December 2020.
9.7 The final, but the most crucial, analysis in the chapter attempts to estimate the impact of
PM-JAY on health outcomes by undertaking a difference-in-difference analysis. We compare
the health indicators measured by National Family Health Survey 4 (NFHS 2015-16) and the
National Family Health Survey 5 (NFHS 2019-20) to undertake this analysis. As PM-JAY was
implemented in 2018, these two surveys provide before-after data to assess the impact of PM-
JAY with the NFHS-4 serving as the baseline to compare the changes using NFHS-5. To mitigate
the impact of various confounding factors, including but not limited to secular improvements in
health indicators across the country, we undertake this analysis by calculating a difference-in-
difference.
9.8 This analysis is undertaken in two parts. In the first part, we use West Bengal as the state
that did not implement PM-JAY and compare the before-after difference in health outcomes to
its neighbouring states that have implemented PM-JAY – Bihar, Sikkim and Assam. Apart from
all these states being contiguous to each other and therefore being similar on socio-economic
dimensions, we show that the baseline characteristics of these two groups of states were similar.
In the second part, we repeat the same analysis for all states that did not implement PM-JAY
vis-à-vis all states that implemented PM-JAY. o f course, the heterogeneity across the entire
group of states in the country is large. The second analysis is less of a like-for-like comparison
than the first one. Combining the findings from both these comparisons ensures that the findings
are robust not only to a more localised, and therefore, more careful comparison but also to a
comparison that spans all the major states in the country. The findings from this analysis are
summarised as follows:
1. The proportion of households that had health insurance increased in Bihar, Assam and
Sikkim from 2015-16 to 2019-20 by 89 per cent while it decreased by 12 per cent over the
same period in West Bengal. When comparing across all the states over this time period, we
find that the proportion of households with health insurance increased by 54 per cent for the
states that implemented PM-JAY while falling by 10 per cent in the states that did not adopt
PM-JAY . Thus, PM-JAY enhanced health insurance coverage.
2. From 2015-16 to 2019-20, infant mortality rates declined by 20 per cent for West Bengal and
by 28 per cent for the three neighbouring states. Similarly, while Bengal saw a fall of 20 per
cent in its Under-5 mortality rate, the neighbours witnessed a 27 per cent reduction. Thus,
289 JAY Ho: Ayushman Bharat's Jan Arogya Yojana (JAY) and Health Outcomes
the neighbouring states witnessed 7-8 per cent greater reduction in these health outcomes.
3. Modern methods of contraception, female sterilization and pill usage went up by 36 per
cent, 22 per cent and 28 per cent respectively in the three neighbouring states while the
respective changes for West Bengal were negligible. While West Bengal did not witness any
significant decline in unmet need for spacing between consecutive kids, the neighbouring
three states recorded a 37 per cent fall.
4. Various metrics for mother and child care improved more in the three neighbouring states
than in West Bengal.
5. Each of the effects described above (points 2-4) manifested similarly when we compare all
states that implemented PM-JAY versus the states that did not.
9.9 Overall, the comparison reflects significant improvements in several health outcomes
in states that implemented PM-JAY versus those that did not. As the difference-in-differnce
analysis controls for various compounding factors, the Survey infers that PMJAY impacted
health outcomes positively.
PM-JAY: STATUS AND PROGRESS SO FAR
9.10 As per the latest annual report of PM-JAY released by the National Health Authority
(NHA, 2019), the status of implementation is as follows:
- 32 states and UTs implement the scheme
- 13.48 crore E-cards have been issued
- Treatments worth INR 7,490 crore have been provided (1.55 crores hospital admission)
- 24,215 hospitals empaneled
- 1.5 crore users have registered on the scheme’s website (mera.pmjay.gov.in)
Figure 1: The distribution in utilization of various procedures
Source: NHA data secured from PMJAY
9.11 Figure 1 plots the number of PM-JAY pre-authorizations claims for a procedure against
the average price of the procedure for the time period September 2018 through January 2021
(till January 13, 2021). The distribution is a long-tailed one that peaks in the range of INR
10,000-15,000. The highest number of pre-authorization claims received were for procedures
290 Economic Survey 2020-21 V olume 1
that cost in this range. The distribution is heavily right tailed indicating relatively fewer
claims for more expensive procedures. The high number of claims for low cost procedures
could be indicative of people utilizing PM-JAY as a delivery channel for primary healthcare
services.
9.12 Figure 2 details the share of overall PM-JAY claims by the nature of clinical specialty over
July-September 2018 to o ctober-December 2019.
Figure 2: Share of claims by clinical specialty
Source: NHA data secured from PMJAY
9.13 General medicine has been the overwhelmingly major clinical specialty used since 2018
with its share continuously growing. It is followed by general surgery and obstetrics and
gynaecology. These three categories combined made up close to 56 per cent of claims received
in o ctober-December 2019. An important caveat to note here is that Dialysis itself comprises
a large chunk (30 per cent) of the ‘general medicine’ category claims under PM-JAY . This is
despite the fact that the Pradhan Mantri National dialysis Programme, which was rolled out
in 2016, also provides free dialysis to kidney patients in district hospitals. According to data
from the National Health Ministry, every year, about 2.2 lakh new patients with end stage renal
disease get added in India, resulting in additional demand for 3.4 crore dialysis every year
(Ghosh 2016). These facts corroborate India’s growing burden of non-communicable diseases
in the form of hypertension and kidney disease.
Box 1: Specialties, Packages and Procedures in PM-JAY
Specialty Packages Procedures
Burns Management 6 20
Cardiology 20 26
Cardio-thoracic & Vascular surgery 34 113
Emergency Room Packages 3 4
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