As India’s population ages, the demand for tertiary healthcare to treat non-communicable diseases (NCDs) such as cancer, diabetes, and cardiovascular ailments is increasing rapidly. Estimates from the World Health Organisation show that deaths in India due to non-communicable diseases increased from 4.2 million in 2000 to 5.8 million in 2016. Over the same period, deaths due to communicable diseases that typically do not require hospitalisation decreased from 4.02 million to 2.55 million. Treatment for NCDs is expensive, often beyond households' capacity to pay, which creates a role for policy interventions to publicly finance or operate tertiary healthcare.
Private vs. public insurance
In many developed countries including the US, private insurance is the primary vehicle through which most residents finance health care while public insurance serves a supplementary role for poorer and elderly individuals. In the UK, healthcare is publicly funded and operated by the government irrespective of patient background.
India in the late 2000s moved towards a model where the state finances healthcare for the below poverty line citizens with minimum co-payment while wealthier citizens pay for tertiary healthcare services out-of-pocket. The primary programme in India, the Rashtriya Swasth Bima Yojana (RSBY, or the national health insurance programme) treated 11.84 million below poverty line patients from 2007 to 2016. Yet, low health expenditure coverage and other barriers such as smart-card enrollment, have limited the adoption and use of insurance. State-sponsored health insurance without registration fees, such as Aarogyasri and NTR Vaidya Seva in the states of Telangana and Andhra Pradesh (AP) respectively, may avoid beneficiary enrollment barriers and increase utilisation of tertiary healthcare significantly. More than 3.1 million patients combined used Aarogyasri and NTR Vaidya Seva between 2007 and 2015 at a cost greater than $1.2 billion.
Taking a cue, the Modi government introduced the Ayushman Bharat-National Health Protection Mission in 2018, a collaboration between the central and state governments designed to pay for tertiary healthcare for nearly 100 million families across the country, while overcoming several enrolments and participation challenges associated with the Rashtriya Swastha Bima Yojana. Despite several desirable features such as pan India portability, public and private hospital empanelment, and deprivation-based entitlement, Ayushman Bharat faces several economic design issues. These include:
- Government expenditures. Writing in Mint newspaper, the CEO of Ayushman Bharat, Dr. Indu Bhushan, recently called the reimbursement rates for treatment the “elephant in the room”. The key issue is that the central and state governments must decide the level of reimbursement. Setting the level too low implies that not enough hospitals will participate, and the programme will have capacity shortfalls and potentially lower quality. Setting the level too high implies that the fiscal burden will be high, which might be unsustainable in the future.
- Hospital participation. Hospitals have to decide whether to participate in the programme, the specialties to offer, and how many beds to make available. They also have to make micro-decisions on personnel and infrastructure that influence the type and quality of care received by patients. For instance, Dafny (2005) showed that price (reimbursement) changes by the Medicare system in the US led to more “upcoding”, or switch patients from lower-paying to higher-paying diagnosis. Of course, based on the management type, different types of hospitals and the people who work there, might care more or less for the service mission compared to profits. But generally, greater quality costs more, and the treatment reimbursement rates will constrain participation and quality even for not-for-profit institutions.
Moreover, too many hospitals participating in the programme will increase competition and squeeze margins, which could lead to compromises on quality or other manipulations by hospitals. Conversely, lower hospital participation might reduce competitive pressures, which could potentially allow hospitals to increase expenditures on patients and increase quality.
More widespread provision of tertiary care will create a publicly financed private option for a large number of patients in many places around the country, constraining the rates charged even by non-participating hospitals. By lowering prices paid by patients across the sector, Ayushman Bharat could improve welfare far beyond direct beneficiaries.
- Patient participation. While the Ayushman Bharat reduces out-of-pocket payment, it is difficult for patients to ascertain the quality of care they receive, both before seeking treatment and once a procedure has been completed. Thus, healthcare remains an exception where patients are unable to impose the typical discipline exercised by “customers” in other markets. The Quality and Outcomes Framework (QOF) introduced in 2004 in the NHS which made payments to GPs directly proportionate to the quality of care received by their patients tried to solve this quality conundrum. QOF resulted in limited improvements in quality and reduced socioeconomic inequalities in delivery of care (Roland 2016). However, measuring quality of healthcare is a challenge in itself and requires patient specific data on healthcare delivery. Apart from quality, several factors such as distance to empaneled health facilities and long-term care costs might impact patient participation.
Several other design issues could emerge including:
- How will it monitor claims, mitigate fraud, and encourage preventive care?
- How will it impact investment in the hospital sector?
- How will it motivate new talent to join the healthcare sector, and what will happen to early career education and specialisation decisions of physicians, nurses, and the wider healthcare workforce?
- What will be the impact on related markets such as health insurance, pharmaceuticals, hospital equipment, and long-term care?
Answering these design questions will help understand both the “impact” of Ayushman Bharat, but also uncover the trade-offs inherent in making policy. In the healthcare sector, ethical, moral, technical, and even political concerns are often at the forefront of decision-making. Even so, the sheer costs associated with Ayushman Bharat are large enough that administrators will face budget constraints relatively soon.
We can learn from experiences with existing programmes in the country (RSBY, Odisha’s Biju Swasthya Kalyan Yojana, Aarogyasri, Employees State Insurance Scheme etc.), as well as from NHPO as the programme is rolled out across the country. A critical ingredient is for the NHPO to share data with researchers in India who can contribute analytical capabilities for the programme. A good template for this is how Medicaid and Medicare share data through the Centres for Medicare and Medicaid Services in the US. Over time, this collaboration with researchers led to landmark studies including those on the effects of Medicaid and Medicare (see Finkelstein’s (2007) study), health insurance expansion (notably the Oregon Health Insurance Experiment), the Massachusetts Healthcare Reform, and the Affordable Care Act (see Frean et al.’s (2017) study). In India, the Aarogyasri programme routinely posts data publicly which facilitated analysis of the drivers of utilisation. We hope that Ayushman Bharat will follow this lead.
Dafny, L (2005), “How do hospitals respond to price changes?”, American Economic Review 95(5):1525-1547.
Debnath, S and T Jain (2018), Social connections and public healthcare utilization.
Debnath, S and T Jain (2016), Public health insurance for tertiary diseases: Lessons from Andhra's Aarogyasri programme, Ideas for India.
Finkelstein, A (2007), “The aggregate effects of health insurance: Evidence from the introduction of Medicare, Quarterly Journal of Economics, 122(1), 1–37.
Rajasekhar, D, E Berg, M Ghatak, R Manjula and S Roy (2011), “Implementing health insurance: The rollout of Rashtriya Swasthya Bima Yojana in Karnataka. Economic and Political Weekly 46(20), 56–63.
Frean, M, J Gruber and B Sommers (2017), “Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act”, Journal of Health Economics, 53, 72-86.
Roland, M (2016), “Quality and outcomes framework: What have we learnt?”, British Medical Journal, 354.
 Only 15% of households have any health insurance coverage, and efforts to increase adoption through private markets have not met widespread success.