The government of India has broadly pursued four strategies to improve access to healthcare services for the its entire population: first, by strengthening the government healthcare system through financing and organisational reform; second, by expanding mandated health insurance coverage for formal sector employees; third, through publicly funded health insurance for the bottom 40% of the population; and fourth, by expanding coverage through voluntary health insurance, primarily for the affluent segment of the population (Mahal, Tiwari, Reddy, & Kane, 2024). However, a significant proportion of the population (mainly in the third and fourth quintiles) lacks health insurance because they neither have jobs in the formal sector nor qualify for the targeted tax-funded public health insurance schemes. Furthermore, the premiums for private voluntary health insurance are high and may not be affordable for many in the third and fourth quintiles (Paul & Sarkar, 2023).
Since UHC requires that everyone, everywhere should have access to quality and affordable healthcare – which ultimately ensures healthy lives (WHO, 2010) – it is crucial for the government to ensure access to essential healthcare services for those without formal health insurance.
Since UHC requires that everyone, everywhere should have access to quality and affordable healthcare – which ultimately ensures healthy lives (WHO, 2010) – it is crucial for the government to ensure access to essential healthcare services for those without formal health insurance.
Mahal et al. (2024) estimated that 125 million households are covered under Pradhan Mantri Jan Arogya Yojana (PMJAY), 45 million households are covered by states (extending to Above Poverty Line [APL] families), 34 million households are covered under social insurance schemes (Central Government Health Scheme [CGHS], Employees’ State Insurance Scheme [ESIS], Ex-Servicemen Contributory Health Scheme [ECHS])1 and 57 million households are covered under private insurance (both individual and group). Considering a total of 325 million households in India, around 68–80 million households will remain uncovered, given that there will be some level of overlap between the insurance schemes (Mahal, Tiwari, Reddy, & Kane, 2024).
The Periodic Labour Force Survey (2022–2023) data indicates that 57.3% of the total workforce aged 15 and above were self-employed, primarily in the informal sector. As noted, informal sector workers are not covered by any existing health insurance schemes. Furthermore, a significant proportion of individuals in the formal sector may not have health insurance (Mahal, Tiwari, Reddy, & Kane, 2024). It has been suggested that this uncovered population (or a portion thereof) has the ATP for healthcare, and thus a contributory health insurance scheme2 may be appropriate for this segment (Kumar & Sarwal, 2021). However, it remains unclear how much they can afford to pay. Additionally, even if they can afford to pay, are they willing to pay the necessary amount?
Ability to pay (ATP) in healthcare has largely been understood as the relationship between available resources at the household or individual level and the cost of treatment. The WHO assesses affordability by considering the number of days a lowest-paid unskilled government worker must work to cover the cost of treatment (Beal & Foli, 2020). According to Russell (1996), a common method for determining affordability is the ratio approach, where healthcare expenditure is analysed as a percentage of household income or expenditure. Successive HCESs indicate that 4%–6% of total household expenditure is the average expenditure ratio on healthcare, thus considered the affordable ratio. Using the ratio method, a 45-degree line (equality line) plots, for instance, a health expenditure ratio of 6%. Any point above the equality line is deemed affordable, as it is less than 6%. A simple visual representation of the ratio method is explained below:
Figure 1 illustrates that households whose medical3 expenditure (as a percentage of household expenditure) is either on or above the equality line are spending less than or proportionate to their overall household expenditure or available resources. Those above the equality line can afford the medical expenditure, whereas those below cannot. However, this method does not account for whether those in the affordable region of the graph are incurring opportunity costs by reducing their expenditure on essentials such as food, shelter, and education below their minimum needs.
Figure 1: Ratio Approach to Ability to Pay (ATP) 
Source: Adapted from Russell (1996).
The core question in the debate on the ATP has been whether the cost of healthcare for a household should be the sole criterion for ATP or whether other factors influencing households’ healthcare decisions should also be considered. Geographic availability can impact ATP for healthcare services (Levesque, Harris, & Russell, 2013), as do indirect costs such as transportation (Doran & Hornibrook, 2014) and financial stress (Yakob & Ncama, 2016). Several studies highlight competing costs, such as those related to food, clothing, education, and electricity bills (Cunningham, 2011; Perumal‐Pillay & Suleman, 2017). Bead and Foli (2020) note that affordability in healthcare is subjective, transactional, and circumstantial.
As discussed above, the ratio approach does not consider factors such as disposable income and costs associated with merit goods. Disposable income is the income that households have available to spend or save after deducting taxes and other mandatory expenses, such as pension and provident fund contributions (Hosier, 2004).
The concept of affordability was redefined by Hancock (1993) in the context of housing prices. He argued that if a household spends a certain percentage of its total budget (or available resources) on housing, it should not reduce expenditure on other merit goods like education and healthcare below the socially desired minimum standards of consumption, usually determined by household survey data.
Hancock’s concept has been extended to understand affordability in health insurance and healthcare (Glied, 2009; Russell, 1996). Unlike the ratio approach, Hancock suggested incorporating other merit goods into the affordability analysis. Given information on how much healthcare and non-healthcare goods are consumed by households, it is possible to determine who cannot afford healthcare expenditure.
A household is said to afford healthcare expenditure if it is left with sufficient resources to meet the minimum expenditure for non-medical goods (food, housing, and education). The trade-off can be represented in a 2×2 matrix, as shown in Figure 2 below.
Figure 2: Categorising Affordability (Based on Hancock, 1993) 
Source: Adapted from Hancock (1993)
It is evident from the figure 2 that there are four possible combinations of the two categories of goods, namely non-healthcare and healthcare, that can be consumed by the household.
The horizontal and vertical red lines in the figure 2 indicate the minimum expected expenditure on these goods by households. Point E on the figure represents the minimum consumption bundle expected to be consumed by households. This implies that if a household’s income is just sufficient to allow spending H’ on medical goods and Y’ on non-medical goods, the household will be able to reach point E. Extending a line from point E towards Y and H, this straight line represents the minimum budget required for all households to achieve point E (the budget constraint line). Therefore, all households on or above the budget constraint line (including the shaded areas in regions C and D) can achieve point E. This means that households in region A can not achieve minimum expenditure for both medical and non-medical goods.
Hancock’s affordability concept has been applied using Household Consumption Expenditure Survey (HCES) data (2022–2023). An average medical expenditure of 6% of total household expenditure is set as the threshold for underconsumption of healthcare, while 52% of total household expenditure is the threshold for underconsumption of non-medical goods.
Applying the four scenarios suggested by Hancock, the HCES data reveal that 30% of households in region A can neither afford minimum healthcare expenditure nor minimum expenditure on other merit goods, while 8% of households in the third and fourth quintiles in region B can afford minimum expenditure for both medical and non-medical goods. The remaining 62% of households face a complex decision because they must choose between two merit goods due to budgetary constraints. Overall, it was found that at least 39% of households (comprising Regions B, C, and D) can afford both goods, and a maximum of 66% of households in the third and fourth quintiles can afford the minimum consumption set.
Table 1: Household Expenditure for Third and Fourth Quintiles
Source: Author’s analysis using HCES data 2022–2023.
Further, the affordability calculation (applying threshold criteria of 6% for medical and 52% of non-medical expenditure as percentage of total household expenditure) suggest that 30% of households in the third and fourth quintiles who spend less than 6% of their total household expenditure on healthcare can contribute a maximum of INR 5,693 per year for both inpatient and outpatient services (Table 1). Eight per cent of households with sufficient resources can contribute a maximum of INR 24,466 per year. For the remaining 62% of households, which can just afford to pay 6% of their household expenditure, the contribution ranges from INR 13,344 to 15,132 per year.
The HCES data for 2022–2023 reveal that less than 10% of the total households in the third and fourth quintiles are able to meet the minimum level of expenditure for both medical and non-medical goods. Most households have to choose one merit good over others.
Way Forward
The HCES data for 2022–2023 reveal that less than 10% of the total households in the third and fourth quintiles are able to meet the minimum level of expenditure for both medical and non-medical goods. Most households have to choose one merit good over others. It is found that about half of the total households cut back on medical expenditure to achieve more than the minimum level of expenditure for other merit goods such as food, housing, and education.
The affordability analysis suggests that to provide comprehensive coverage to all households in the third and fourth quintiles (where 30% of households can pay a maximum of INR 5,693 per year), the government will need to contribute at least 50% of the premium amount.
The affordability analysis suggests that to provide comprehensive coverage to all households in the third and fourth quintiles (where 30% of households can pay a maximum of INR 5,693 per year), the government will need to contribute at least 50% of the premium amount. This is because the minimum health insurance premium for comprehensive coverage is INR 20,466 per year1 for a family of four, and such a contribution would encourage households to participate.
The affordability analysis indicates that households in the third and fourth quintiles can pay an average of INR 5,693 per year for their healthcare needs, covering all outpatient and inpatient services.
This discussion suggests the following key takeaways:
The affordability analysis indicates that households in the third and fourth quintiles can pay an average of INR 5,693 per year for their healthcare needs, covering all outpatient and inpatient services. Since comprehensive coverage of services under health insurance requires a higher premium, there are two possible pathways to ensure healthcare services for middle-income households:
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