The Pradhan Mantri Jan Arogya Yojana was launched in 2018 with the aim of covering hospitalisation expenses of the vulnerable 40% of the population, to protect them against financial risk arising out of catastrophic health expenses. It is touted as a game changer in the Indian health sector. Indrani Gupta and Abhijit Roy argue that if costs supersede the allocated funds for the programme, it may substitute other critical investments in the health sector and introduce distortions in the health services market.
Out-of-pocket expenditures as a percentage of total health expenditure in India is about 61%. A majority of individuals access private facilities for both out-patient and in-patient services, with substantial out-of-pocket expenses, which – in the absence of an adequate health cover – can lead to significant economic burden. In this context, the Pradhan Mantri Jan Arogya Yojana1 (PM-JAY) under Ayushman Bharat Yojana2 is potentially an important game changer in the health sector of the country. If it really succeeds to cover hospitalisation expenses of the vulnerable 40% of the population at moderate costs, it will certainly be addressing the concerns with the high poverty-inducing out-of-pocket expenses that Indian households incur for hospital care3. If, however, costs of the programme increase beyond allocations to it, and pose a challenge to the distribution of the rather meagre government resources for the health sector across other health sector priorities, it will still be a game changer – but in the opposite direction. It may end up substituting other critical investments in the health sector and introducing distortions in the health services market.
Setting aside debates on whether or not this was the best use of scarce health resources in the country, one really hopes that the former scenario comes true – of the scheme running at modest costs and covering all intended beneficiary population with quality hospital services, going forward. However, we are apprehensive and think that the probability of this happening is low, unless sufficient funds are allocated for the scheme.
A calculation of total possible costs associated with PM-JAY
Below, we explain why we are concerned, and restrict ourselves to the financial implications of the PM-JAY. Our discussion is based on our recent background report submitted to the 15th Finance Commission on costs and finances of PM-JAY (Gupta et al. 2019).
The first point to note is that there are three variables that will govern the total costs of the programme: (i) extent of coverage (C), (ii) rate of hospitalisation (H), and (iii) expenditure per hospitalisation (E). The estimated total costs of PM-JAY will have to be around the number obtained by C*H*E.
The National Sample Survey (NSS), 71st round on ‘Health in India’, is the only available dataset which allows us to use nationally representative values for H and E above. It indicates that in 2014, the average rate of hospitalisation was 3.8% if one excludes childbirths (it was around 5% with child births), and average total medical expenditure per hospitalisation case was Rs. 18,628 (Rs. 15,000 with child births). As expected, there were significant state-level variations, with southern states like Kerala and Tamil Nadu showing much higher hospitalisation rates.
The government’s aim is to cover about 107.4 million deprived, poor families or about 0.5 billion beneficiaries. A simple arithmetic calculation of C*H*E taking NSS hospitalisation and expenditure values for cases without child births, and using 0.5 billion as target population yields a total cost of around Rs. 350 billion for the year 2014, with all beneficiaries being covered.
However, PM-JAY has been implemented in 2018-19. If we make the unrealistic assumption that between 2014 and 2019, hospitalisation rates did not change, we still need to correct the average expenditure accounting for inflation. Also, any new scheme comes with administrative and managerial costs – both the insurance and trust models4 would have their own administrative loads – and PM-JAY is also heavily dependent on technology for efficient implementation. Evidence indicates that a 15% top-up per beneficiary is the minimum that can be assumed. Using consumer price index (CPI) and the 15% top-up gives a hospitalisation expenditure of Rs. 26,135 per hospitalisation, with a resultant total costs of around Rs. 500 billion in 2019, if all the beneficiaries are covered. If we omit the administrative costs, it is still about Rs. 430 billion. In other words, in 2019, the costs of PM-JAY could range between Rs. 350 billion to Rs. 500 billion.
As a percentage of GDP (gross domestic product), this is only between 0.17-0.23% of projected GDP in 20195. The budgeted expenditure of the Ministry of Health and Family Welfare (MoHFW) is Rs. 626.6billion in 2019-20 or slightly less than 0.3% of GDP. Clearly, the estimated costs of PM-JAY are likely to absorb almost the entire budget of the MoHFW. Out of this year’s MoHFW allocation, PM-JAY has been given an enhanced allocation of Rs. 64 billion, which is less than 20% of the estimated costs of PM-JAY presented above.
Overall, public expenditure on health as a percentage of GDP was 1.02% in 2015-16 according to the National Health Profile, 2018. Even if it increases to 2.5% as envisaged in the National Health Policy, 2017, the PM-JAY will eat into much of this as the preceding conservative estimates indicate. Thus, it is not immediately clear how the finances for the scheme will be met. If it does work at the costs stipulated by the government and covers all those it intends to cover, it will be one of the cheapest such schemes the world over. Clearly other countries will want to emulate it.
What then is the missing part of the picture? How can the government be confident of running this scheme at such low costs?
How are the costs envisaged so low?
There are two control knobs with the government: the government can keep the costs of hospitalisation down by lowering the package rates and/or it can restrict the number of beneficiaries accessing hospitalisation. The third parameter, rate of hospitalisation – which was already between 3-5% of the population in 2014 – should be totally demand-driven and dependent on the disease burden and treatment-seeking behaviour of the beneficiaries, and ought not to be a policy knob. However, inaccessibility of suitable healthcare facilities as well as bureaucratic sloth can lower hospitalisation rates artificially. For now, we assume that this is exogenous and discuss the other two parameters – expenditure on hospitalisation and beneficiaries covered.
The package rates have been negotiated to a significant extent and highly modest rates have been set up for different package rates. It remains to be seen if these rates are sufficient for hospitals and insurance companies to carry out the business of giving decent hospital care. In an environment of increasing burden of non-communicable diseases and technology-driven treatment, it is highly improbable that the per hospital cost can go below the 2014 NSS numbers of Rs. 15,000--18,000 at current prices, in a tertiary care market which is mostly private. If, in fact, it does go down below that, all else being equal, it has to imply that quality and appropriate care is not on offer. Hospitals will find a way of cutting down their costs for PM-JAY cases knowing they will only be reimbursed at the package rates.
The second way the costs can be kept down is by reducing the coverage – by omission or commission.
In the calculations below, we have recalculated the total costs by assuming different beneficiary coverage at 10%, 20%, 30%, and so on, of target beneficiaries.
Table 1. Total costs of PM-JAY with variable coverage rates (Rs. billion)
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Beneficiaries covered (%) |
Hospitalisation=3.8%; Cost per hospitalisation = Rs. 18,628 |
Hospitalisation=3.8%; Cost per hospitalisation = Rs. 26,135 |
10 |
35.4 |
49.7 |
20 |
70.8 |
99.3 |
30 |
106.2 |
149 |
40 |
141.6 |
198.6 |
50 |
177 |
248.3 |
60 |
212.4 |
297.9 |
70 |
247.8 |
347.6 |
80 |
283.2 |
397.3 |
90 |
318.5 |
446.9 |
100 |
353.9 |
496.6 |
Source: Authors’ calculation
The last row indicates the scenario with full coverage discussed above. The first row shows 10% coverage, and different coverage rates in increasing order shown in the rows in between. Clearly, higher the coverage, greater the costs. If only 10% get covered, the costs are between Rs. 35 and 50 billion.
In the 2019-20 Budget, allocations to PM-JAY has been increased to Rs. 64 billion. Given that it is a sharing model, and states would put in their share, a total of approximately Rs. 100 billion would be available for the scheme in 2019-20. This means that less than 1/4th of the beneficiaries would be covered with the current allocations, based on Table 1.
The PM-JAY scheme is being run by states either on a trust model or an insurance model. It is learnt that the scheme has received very low premium quotes from some insurers. What could be the reasons for these low quotes and low premiums for government business? Table 2 below helps understand this issue to a certain extent.
The Table shows that while government business contributes 75% of the persons covered, the premium amounts to only 11% of the total. Per person premium is a little over Rs. 100 for government business. This low premium is possible for two reasons. Large schemes like the Rashtriya Swasthya Bima Yojana (RSBY)6have a low cap of Rs. 30,000. Further, government schemes have very low claim ratios on account of administrative failure and a lack of awareness among the intended beneficiaries. Thus, insurance companies can quote low premiums. However, if PM-JAY is a success with increasing demand for hospital care, the insurance pay-outs would increase substantially, putting pressure on the quotes, despite bulk buying.
Table 2. Classification of health insurance: 2017-18
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Type of business |
Premium (in Rs. billion) |
No. of persons covered (in million) |
Government business |
39.81 (11%) |
359.3 (75%) |
Group business (excluding government business) |
177.6 (48%) |
89.4 (19%) |
Individual business |
152.9 (41%) |
33.3 (6%) |
Total |
370.3 (100%) |
482 (100%) |
Source: Insurance Regulatory and Development Authority (IRDA) Annual Report, 2017-18.
In reality, smart negotiation involving reasonable package rates for bulk buying can reduce premiums to some extent. It is said that government is able to reduce group insurance premium rates substantially on account of bulk buying. However, it must be noted that buyers of non-government group insurance business also negotiate hard with insurance companies, who in turn negotiate with hospitals. Hence, their premiums are also a good indicator of negotiated market premiums, and one cannot presume that non-government group premiums are unrealistically high. Since PM-JAY has no exclusions regarding age and pre-existing diseases, the scheme is more attractive than most non-government group health schemes, and should in the normal course lead to higher level of claims, which in turn would impact level of the premiums.
If allocations remain totally out of sync with what would be required to run the scheme successfully, the scheme can still run, but with its own internal speed and logic – with low coverage, unwilling or low participation of private hospitals, and low rates of hospitalisation among the beneficiaries indicating a slack in demand generation. And this is setting aside other complexities like supply-side constraints; states’ shares to run the scheme; their ability, skills, and costs to merge their current schemes with PM-JAY; possible increase in out-of-pocket expenditure due to enhanced treatment-seeking behaviour etc. – which will determine the actual total costs of the scheme.
PM-JAY has come in with a lot of promise and has been globally hailed as one of the largest schemes of health coverage. However, one must guard against the financial implications of running such an ambitious scheme successfully, especially when, historically, raising health finances has been a major challenge in the country. A scheme run suboptimally because of lack of finances can introduce further distortions in a rather distorted health sector – a scenario which one must avoid to the extent possible.
Notes:
- Pradhan Mantri Jan Arogya Yojana (PM-JAY) is one of the two components of the Ayushman Bharat Yojana launched in 2018. PM-JAY aims to reduce the financial burden on poor and vulnerable groups arising out of catastrophic hospitalisation episodes.
- Government of India introduced the Ayushman Bharat Yojana (National Health Protection Mission) in 2018. Ayushman Bharat comprises the PM-JAY and the Health and Wellness Centre initiative designed to offer comprehensive primary care to citizens.
- PM-JAY, however, does not cover out-patient services, which is also an important reason for high out-of-pocket expenses.
- States have been given the flexibility to choose the mode of implementation: they can either implement it in insurance mode, or through a trust or in a mixed model.
- The GDP for 2018-19 has been taken from https://www.indiabudget.gov.in/budgetglance.php, and a rate of growth of 12% has been applied to arrive at GDP for 2019-20.
- Rashtriya Swasthya Bima Yojana was launched in 2008 by the Government of India to provide health insurance coverage for Below Poverty Line (BPL) families. The objective was to provide protection to BPL households from financial liabilities arising out of health shocks that involve hospitalisation. It provided total cover of Rs. 30,000 per family (five members) annually for tertiary care expenses.
Further Reading
- Gupta, I, S Chowdhury, Ramandeep and A Roy (2019), ‘Ayushman Bharat: Costs and Finances of the Prime Minister’s Jan Arogya Yojana (PM-JAY)’, Report submitted to the 15th Finance Commission.
- Insurance Regulatory and Development Authority (2018), 'Annual Report, 2017-18'.
- Ministry of Health and Family Welfare (2018), ‘National Health Accounts: Estimates for India’, Government of India, November 2018.
- Ministry of Health and Family Welfare, ‘Household Healthcare Utilization and Expenditure in India: State Fact Sheets’, National Health Systems Resource Centre, Government of India.
- World Health Organization (2010), ‘Administrative costs of health insurance schemes: Exploring the reasons for their variability’, Discussion Paper No. 8, Geneva.
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