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Publicly Financed Health Insurance Schemes

Soumitra Ghosh (soumitraiips@gmail.com) teaches at Tata Institute of Social Sciences, Mumbai and is a consultant at National Institute of Public Finance and Policy, New Delhi.

The announcement of the National Health Protection Scheme provides us with an opportunity to see how its predecessor Rashtriya Swasthya Bima Yojana and other publicly funded health insurance schemes have fared so far. The experiences of PFHIS indicate that targeted health insurance coupled with a healthcare delivery system dominated by “for profit” private providers failed to address the issues of access and financial risk protection. They possibly displace resources that can be utilised for strengthening a public health system.

The Rashtriya Swasthya Bima Yojana (RSBY) was launched in 2008 and had a target of covering the entire population below poverty line (BPL) by 2012. However, even after nine years of its implementation, only half of the BPL families were covered according to the government’s own data. Further, there is a huge discrepancy between the coverage figures given by the government data and estimates from surveys. For example, as per the 71st round of National Sample Survey Office (NSSO), 11.1% of population was covered by the RSBY and state-sponsored health insurance schemes (SSHIS) in 2014 (excluding Employment State Insurance Scheme (ESIS), Central Government Health Scheme (CGHS) and Ex-Servicemen Contributory Health Scheme (EcHS)) but data from Insurance Regulatory and Development Authority (IRDA) suggests that the population coverage of these schemes was 16.4%.

One of the major sources of this discrepancy in enrolment rate in the RSBY is due to the creation of bogus beneficiaries by the insurance companies to earn premium subsidy from the government. Another source of discrepancy is that while insurance companies have been given the premium subsidy for covering all eligible households in respective states, the insurer did not reach out to all and only a fraction of the eligible population was enrolled and made aware about their entitlements under various SSHIS. For example, total eligible families for the Mahatma Jyotiba Phule Jan Arogya Yojana (MJPJAY) in Maharashtra, as per the public distribution system (PDS) data, were 2,07,94,294 in 2015, of which merely 2.45% families were enrolled under the scheme in 2016.

Does Targeting Work?

The other problem is related to the identification of poor households. Ghosh and Datta Gupta (2017) found that almost half of the households enrolled in the RSBY actually belonged to the non-poor category. Experience with regard to targeting was similar in other insurance schemes. For example, a study based on primary data collected from Mumbai in 2013 shows that almost half of the households enrolled under the MJPJAY were from the non-eligible category (Rent and Ghosh 2015). These findings suggest substantial leakage to the non-poor in publicly funded health insurance schemes (PFHIS). Targeting basically does not seem to work as we also know from other contexts. Further, the design and process of implementation of PFHIS is blind to gender, age, caste, disability status or religion of the target beneficiaries. The failure to recognise the fact that the scheme’s target population belonged to different sociopolitically disadvantaged groups, encapsulating different degrees of social status led to the exclusion of vulnerable groups or individuals (Ghosh and Mladovsky 2014; Shesadri et al 2014).

Access to Healthcare

It is important to underscore the fact that insurance coverage does not automatically translate into utilisation. For utilisation to take place, it is important that enrolled families possess sufficient information about how insurance coverage can be used for accessing health services. Interestingly, in PFHIS, insurance companies have been entrusted with the responsibility of generating awareness among the target population. As expected, this policy of employing insurance companies for educating the BPL families about health insurance has largely been ineffective (Ghosh 2014).

According to the programme data, the hospitalisation rate was found to be as low as 1% amongst the RSBY-insured individuals, compared to a national average of 2.6% for the general population as of 2014. Further, there is substantial variation across states, ranging from 0.1% in Rajasthan to 4.8% in Kerala (Figure 1, p 17). The point to be noted is that the RSBY is not an exception in this regard. The utilisation rate of other insurance schemes is also very low. For example, the MJPJAY has been in operation in Maharashtra since 2011 but the utilisation rate (calculated as the proportion of eligible persons with at least one inpatient claim during the year) was just 0.12% in 2013–14 and 0.18% in 2014–15.

Signs of Cream-skimming?

Here is another important revelation in the claims data of the MJPJAY with respect to the utilisation patterns (Table 1). Cancer accounted for 30% of all claims settlement (medical, surgical, and radiation oncology), followed by cardiology and cardiovascular surgery (together accounting for 19.3% of cases) and nephrology (15%). All medical illnesses—general medicine, endocrinology, rheumatology, dermatology, and infectious disease—taken together accounted for only 0.79% of all claims. Clearly, this varies with morbidity patterns in the general population.

Does this pattern indicate any wrongdoing by the providers? Are they cherry-picking?

A closer scrutiny of the claims data actually substantiates this hypothesis. The packages for cardiac, cancers, and dialysis are some of the most expensive procedures covered under the insurance scheme, and understandably, private hospitals choose such high-paying surgeries, leaving the “low profit” patients for the public hospitals. As per the claims data of the MJPJAY, while 70% of the overall utilisation took place in private hospitals, 75% of the cases falling under the above-mentioned specialities were conducted in the private sector. Similar utilisation patterns have also been observed in Aarogyasri Scheme in Andhra Pradesh and Karnataka.

No Financial Protection

There is no evidence that the RSBY has caused reduction in out-of-pocket (OOP) expenditure. Impact evaluation studies showed no significant difference between the RSBY-insured and -uninsured households in terms of OOP payment on outpatient, inpatient or on any type of care (Ghosh and Datta Gupta 2017; Karan et al 2017). Further, researchers found that almost 60% of the RSBY beneficiaries had to make a median OOP payment of ₹4,000 in 2011 for hospitalisation, primarily related to drug purchases (Devadasan et al 2013).

Also, apart from the ineffectiveness of publicly sponsored private health insurance, there are other important aspects of insurance that need to be critically examined. The most important point to note is that because of PFHIS, we are spending a huge portion of financial resources on feeding the health insurance system itself.

For instance, in Maharashtra, the state government paid ₹2,350 crore for MJPJAY as premium subsidy to a private health insurance company from 2012–13 to 2015–16. But the claim disbursement amount was only ₹1,880 crore, which means we purchased ₹1,880 crore worth of insurance services with ₹2,350 crore. So, almost ₹500 crore (20% of the claim revenue) went to the coffers of insurance companies for so-called administrative cost (see Figures 2, 3). These include moving a claim through the system, enrolling beneficiaries, and most importantly, for paying the innumerable and often incomprehensively large salaries of administrators at insurance companies and third-party administrators (TPAs) (private firms that manage most of the administrative tasks of the insurer). The insurance companies employ these TPAs to keep the “claim settlement ratio” low. The lower the claim settlement ratio, the higher is the financial reward for the TPAs. In other words, there is a perverse incentive for TPAs to reject claims and pre-authorisations for cashless procedures.

 

Misplaced Priorities

Since their inception, total expenditures on the state health insurance schemes have increased at a brisk pace. For the first four years of RGJAY/MJPJAY in Maharashtra (2012–16), the premium was pegged at ₹333 per annum per family. Thereafter, it has been on the rise. In 2016–17, the premium was 50% higher than in 2017–18 and then it increased by almost 110% in 2018. The current insurance premium is ₹690 plus taxes for the coverage period January–December 2018.

In Tamil Nadu, the insurance premium for Chief Minister’s Comprehensive Health Insurance Scheme (CMCHS), which was ₹560 in 2012 has been increased to ₹699 per family per annum in 2017–18. In terms of public expenditure on Rajiv Gandhi Jeevandayee Arogya Yojana (RGJAY), it has increased by 153% since 2014 (Table 2). Similarly, Tamil Nadu and Karnataka experienced expenditure increases of almost 100% and 130% respectively. If all government insurance schemes are taken into account, Karnataka spent little more than ₹1,000 crore in 2017–18. Roughly, spending on health insurance schemes ranges from 13% of total government expenditure on health in Telangana to 15% in Karnataka as of 2017–18.

It is no wonder that spending on health insurance programmes has become one of the largest budget items in these states. However, any further changes in the amount spent on insurance schemes will have significant impact on state government’s fiscal balance and the resources available for other programmes. Also, the emphasis on insurance-based coverage for high-end secondary and tertiary care skews public health priorities, and diverts resources away from primary and preventive healthcare. This year’s union budget is a glaring example. While National Health Protection Scheme (NHPS) has been announced with an initial allocation of ₹2,000 crore, there has been a 2.1% reduction in budgetary allocation for the National Health Mission—a flagship programme for strengthening the primary healthcare infrastructure in the country.

There is also a concern that as the participating states in NHPS would have to foot 40% of the massive insurance bill, they might run into issues of fungibility with finance authorities reducing one source to compensate for increases from another source. This is not an unfounded fear, given the fact that many states do not have the fiscal space to absorb additional spending on health insurance. In all likelihood, primary and preventive care would become the biggest casualty of NHPS. It is worthwhile to point out that post the Fourteenth Finance Commission, contrary to the expectation that states would have larger resources to spend on health and education, many states actually recorded a decline in expenditure on social service sectors (Choudhury et al 2018).

Is PFHIS Cost-effective?

There has not been any study to assess the cost-effectiveness of PFHIS. Nevertheless, we can make a broad comparison between the PFHIS and public healthcare system. Take Rajiv Arogyashri Scheme, for example. Andhra Pradesh was the first state to adopt an insurance-based health system model. According to one study, this scheme for hospital care has used 25% of the state’s health budget for addressing a mere 2% of the disease burden, excluding common illnesses such as tuberculosis and diabetes. Of the payments, 75% went to the private hospitals. On the other hand, public healthcare delivery system received just 30% of the total health spending but provided 45% of hospital care and virtually all preventive care in the country in 2014.

Clearly, the experiences of PFHIS indicate that targeted health insurance coupled with a healthcare delivery system dominated by “for profit” private providers have failed to address the issues of access and financial risk protection. Moreover, it has not only wasted thousands of crores of taxpayers’ money but also possibly displaced the resources that were to be utilised for other important activities. Unfortunately, the present government seems to have decided not to learn from such past policy misadventures. While the focus should have been the building of a public health system to achieve “health for all,” it is rolling out the NHPS, another scheme similar to the RSBY, albeit with some minor cosmetic changes. This is not surprising as the idea of PFHIS resonates very well with Niti Aayog and its health policy practitioners who look to health financing reform of this kind as “nirvana” that will free the government from direct provisioning and reinforce market-oriented reforms in India’s publicly funded healthcare.

References

Choudhury, M et al (2018): “Fourteenth Finance Commission: Impact of Its Recommendations,” Economic & Political Weekly, Vol 53, No 10, pp 74–78.

Devadasan, N et al (2013): “Promoting Universal Financial Protection: Evidence from the Rashtriya Swasthya Bima Yojana in Gujarat, India,” Health Research Policy and Systems, Vol 11, No 1.

Ghosh, S (2014): “Maharashtra Case Study Summary,” Studies in Health Services Organisation and Policy, Vol 32, pp 56–73.

Ghosh, S and N Datta Gupta (2017): “Targeting and Effects of Rashtriya Swasthya Bima Yojana on Access to Care and Financial Protection,” Economic & Political Weekly, Vol 52, No 4, pp 61–70.

Ghosh, S and P Mladovsky (2014): “Social Exclusion and Its Effect on Enrolment in RSBY in Maharashtra,” Studies in Health Services Organisation and Policy, Vol 32, pp 118–31.

Karan, A et al (2017): “Extending Health Insurance to the Poor in India: An Impact Evaluation of Rashtriya Swasthya Bima Yojana on Out of Pocket Spending for Healthcare,” Social Science and Medicine, Vol 181, pp 83–92.

Rent, P and S Ghosh (2015): “Understanding the ‘Cash-Less,’ Nature of Government-sponsored Health Insurance Schemes: Evidence from Rajiv Gandhi Jeevandayee Aarogya Yojana in Mumbai,” SAGE Open, Vol 5, No 4, pp 1–10.

Sakthivel, S (2017): “The Role of Publicly Funded Health Insurance in Universal Health Care,” presentation for the National Conference on Health Insurance and Universal Health Care in India, TISS-CEHAT, 13–14 October.

Shesadri, T et al (2014): “Implementing Programmes as If Social Exclusion Matters: Enrolment in a Social Health Protection Scheme,” Studies in Health Services Organisation and Policy, Vol 32, pp 101–17.

Updated On : 12th Jun, 2018

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