With a population of 1.4 billion and very limited public funding for healthcare (1.29 percent of GDP), an important priority for India is ensuring equitable and cost-effective healthcare. To meet these priorities, in 2018, the government of India launched the world’s largest publicly funded health insurance scheme (ABPM-JAY), which includes a greater role for India’s large and growing private healthcare sector.
Recently the ABPMJAY, which covers 10 million vulnerable families, reached a milestone of providing 100 million treatments. However, given the size of the scheme, ensuring cost-effectiveness within such a large scheme is highly dependent upon having detailed and robust information on economic costs within the health system. Here we discuss, the role of costing in priority setting, price negotiations and the measures that India is taking in this area, as part of its efforts to ensure equity and cost-effectiveness within its healthcare system.
Poor cost data can lead to the misallocation of resources
Priority setting is the process of making decisions about how best to allocate limited resources to improve population health. Priority setting within healthcare can be facilitated through health technology assessments (HTA) which includes quantifying whether investments in healthcare are both clinically effective and cost-effective and through exploring the key factors within the healthcare system that drive costs.
In India, as in many low- and middle-income countries (LMICs), there have been challenges in systematically incorporating explicit priority setting or HTA into healthcare decision-making in India. A key barrier has been the complex and fragmented healthcare system with several different insurance and “assurance” arrangements, at both the central and state level. Despite these challenges, the government of India has begun to take proactive steps towards institutionalising HTA. It has established its own HTA agency at the national level (HTAIn) in the Ministry of Health and Family Welfare, and HTAIn has been developing HTA standards and initiating the first health technology appraisals.
But, as HTA rolls out in India, the limited availability of cost data has been highlighted as a key concern by both government actors and the press. The availability of cost data is in turn constrained by limited cost data collection activities, the inadequacy of information systems to meet costing needs, and the lack of political interest in costing. A typical problem is when only some of the costs relevant to delivery of a drug or diagnostic tool are assessed (e.g. excluding patient monitoring or patient incurred costs). An intervention can then appear more or less cost-effective than they actually are and fail to acknowledge the cost burden placed on patients.
This is a problem found in many LMICs but with political will, a standardised, central, and freely available source of health service cost data can be developed to address this gap (such as in Thailand or Cambodia). As a result it will lead to a fall in the duplication of efforts and the expense of data collection to improve the quality of HTA.
Good quality cost information can help governments negotiate better prices
The terms “cost” and “price” are often, mistakenly used interchangeably. However, they are extremely different things. Specifically, prices do not necessarily reflect costs. Prices are the negotiated rate for a good e.g. drugs or service such as consultations. Set too high, prices can over-stretch a budget, limiting spending in other areas and setting up barriers to care and, where individuals pay for care, lead to catastrophic health expenditure. At the same time, high reimbursement rates can result in the over-use of certain treatments such as c-sections and have even led to unwanted hysterectomies. Set too low and the prices can contribute to over-use of some therapies such as antibiotics. Good quality cost information and HTA can help regulate prices so that they reflect value for money.
Regulating prices can be easier within health systems that have a central purchaser such as the UK, France, Australia and Thailand where prices are set in accordance with costs. Within these countries, uniform reimbursement rates are set using data on the cost of health service provision collected through the mandated submission of cost data from all providers or, in the case of Thailand, comprehensive cost surveys conducted by the Health Intervention and Technology Assessment Program of the Ministry of Public Health (HITAP).
Such a system which involves a central regulator encourages transparency and can help contain growth in costs through both accountability as well as economies of scale. For example, using reliable cost information in an HTA process allowed the Thai government to negotiate an affordable price for the HPV vaccines, demonstrating how monopsony power (when there is only one buyer in a market) combined with good cost information can contain costs.
Regulating prices is trickier in fragmented healthcare systems (e.g. USA or India) which have many different types of providers and purchasers (insurers/government). In India, the fragmented system has resulted in large scale variations in prices for similar services across and between states and providers. The majority of fee rates within India’s many public health insurance schemes have been set using various processes and fee rates with different incentives for different services resulting in a process that is “non-transparent and often arbitrary and irrational.” These prices are likely to be inefficient and highly incentivise certain types of services at the expense of others, such as the use of high technology stent implants that have no evidence based benefit over cheaper models. Gathering information on coronary stent prices revealed price mark ups of between 4-6 times the cost price, leading government price capping and up to 85 percent price reductions. Similarly, a recent Indian initiative to improve TB testing in the private sector has shown how standardisation of prices can be achieved by bringing private laboratories together under a single regulatory body, India has reduced the cost of accredited TB tests to affordable levels. The issue has been highlighted during the COVID-19 pandemic with private hospitals accused of charging exorbitant prices, making the government mandate hospitals to share COVID-19 fee details and some evidence of drops in non COVID related healthcare utilisation due to financial barriers.
As publicly funded health insurance schemes expand to cover a greater portion of the population and consume a greater portion of the healthcare budget, the need for prices to be set at efficient levels is more pressing. The demand for freely available good quality cost information to inform price-setting therefore becomes increasingly important.
India is beginning to build a cost evidence-base
Until now, costing information in India has largely been fragmented, not available across states or levels of the health system and highly disease specific. In fact, the major source of cost data has been individual cost studies which have been mixed in validity and reliability. This has been further compounded by the fact that there is a limited pool of health system experts with costing experience in India.
In recognition of the lack of costing capacity within India, the Department of Health Research (DHR) along with academic experts like PGIMER Department of Community Medicine and School of Public Health have taken a proactive approach to strengthen the costing capacity of the health system. Alongside the establishment of a technical working group on costing, there has been support for the development of training material for economic evaluation more generally and subsequently in specific topics including costing. These take the form of online modules, workshops for policy-makers and practitioners and a forthcoming costing manual which lays out principles and standards for costing health services in India.
To improve the availability of data, a National Health System Cost Database website is being built as a public good, by PGIMER Chandigarh, with the support of the International Decision Support Initiative (iDSI). This database currently includes data on the unit costs of health services from 167 public health facilities (district and below) located in 6 different states across India, collected in collaboration with PGIMER’s partners IIT Madras, PHFI Delhi, TISS Mumbai.
In addition to the development of the database and website, the HTAIn has launched a national cost study-Costing of Health Systems (CHSI)-to collect further cost information from public and private healthcare tertiary and district level providers located across 11 different Indian states. The data will be used for HTA and has been used to estimate the unit costs of the AB-PMJAY health benefit packages (HBP). The National Health System Cost Database website continues to be updated with new data (such as the CHSI results) as these become available, as well as the latest methodological standards and guides.
The database website also hosts a user friendly and unique unit cost predictor (based on a statistical cost function). The predictor allows users to generate state specific average outpatient visit and inpatient admission costs for use in their own analyses. For example, a researcher wanting to do an HTA specific to the state of Andhra Pradesh would be able to extract a mean cost for their locality rather than use a national level average.
These first incremental steps towards generating nationally representative health service cost data for India are already proving their value. Since the launch of these two initiatives, the CHSI study costs results have been used to inform reimbursement rates for AB-PMJAY as well as for as well as for the costing of PMJAY COVID-19 HBPs.
India has initiated a welcome and multi-faceted approach for increasing costing capacity, improving cost data and generating a robust evidence base for HTA. These initiatives are already facilitating priority setting and a more transparent price setting process. But there is still work to be done. The role of costing in decision-making needs to be higher up in the healthcare policy makers’ agenda and become an integral part of the evidence base. Healthcare providers and academic centres can facilitate this by adapting information systems to meet cost data collection needs. More critical, is the need for greater transparency around fees and charges. In the future, Ministry of Health; State Departments of Health; National and State public health insurance agencies can make publication and/or submission of provider healthcare costs or fees a mandatory requirement for all providers and in particular publicly funded healthcare. These incremental but exceedingly important steps will help create more transparent healthcare decision-making in the country.
Thank you to Kalipso Chalkidou for valuable oversight.