In 2026, the Supreme Court examined a Public Interest Litigation (PIL) seeking mandatory Nucleic Acid Testing (NAT) in all blood banks. The controversy centered on whether the increased cost of NAT, compared to existing screening methods like ELISA, was justified by the incremental health benefit. The court had to weigh the potential for reducing transfusion-transmitted infections against the financial burden on blood banks and patients.

Without cost-effectiveness analysis, resource allocation in healthcare would likely be less efficient. This could lead to longer wait times for essential treatments, reduced access to innovative therapies, and a slower decline in disease burden. Ordinary citizens might not receive the maximum possible health benefit from the available healthcare budget.

The strongest argument is that cost-effectiveness analysis can lead to discriminatory healthcare decisions, undervaluing the lives of individuals with disabilities or chronic illnesses. My response would be that cost-effectiveness analysis should be used as one input among many, not the sole determinant. Ethical considerations, equity, and human rights must also be given significant weight in healthcare resource allocation decisions.

India should strengthen cost-effectiveness analysis by standardizing methodologies, increasing transparency in data collection and analysis, and establishing a clear willingness-to-pay threshold based on India's economic context. Furthermore, it's crucial to invest in capacity building among healthcare professionals and policymakers to ensure proper understanding and application of cost-effectiveness principles.

India's use of cost-effectiveness analysis is less formalized and standardized compared to countries like the UK or Australia, which have dedicated agencies like NICE (National Institute for Health and Care Excellence). This lack of formal structure can lead to inconsistencies in application and a lack of transparency. However, India's approach may be more flexible and adaptable to its diverse healthcare needs and resource constraints.

The most common trap is presenting a scenario where students instinctively choose the intervention with the lowest *overall* cost, without considering the health outcome. Examiners will often provide data requiring calculation of the cost-effectiveness ratio (cost per QALY or DALY) to identify the *most efficient* intervention, even if it's not the cheapest overall.

Students confuse them because both are used to measure health outcomes. However, QALYs measure the *benefit* of an intervention (years of life gained, adjusted for quality), while DALYs measure the *burden* of disease (years of life lost due to premature mortality and years lived with disability). QALYs are used to assess the value of interventions, while DALYs are used to identify health priorities and track disease burden.

Incremental cost is the *additional* cost of a new intervention compared to the existing standard of care, while the willingness-to-pay threshold is the *maximum* amount society is willing to pay for one additional unit of health outcome (like a QALY).

The most important change is the emphasis on standardized methodologies and transparent reporting. This means UPSC questions are more likely to focus on the *process* of conducting a cost-effectiveness analysis, including data sources, assumptions, and sensitivity analysis, rather than just the results.

In 2026, the Supreme Court examined a Public Interest Litigation (PIL) seeking mandatory Nucleic Acid Testing (NAT) in all blood banks. The controversy centered on whether the increased cost of NAT, compared to existing screening methods like ELISA, was justified by the incremental health benefit. The court had to weigh the potential for reducing transfusion-transmitted infections against the financial burden on blood banks and patients.

Without cost-effectiveness analysis, resource allocation in healthcare would likely be less efficient. This could lead to longer wait times for essential treatments, reduced access to innovative therapies, and a slower decline in disease burden. Ordinary citizens might not receive the maximum possible health benefit from the available healthcare budget.

The strongest argument is that cost-effectiveness analysis can lead to discriminatory healthcare decisions, undervaluing the lives of individuals with disabilities or chronic illnesses. My response would be that cost-effectiveness analysis should be used as one input among many, not the sole determinant. Ethical considerations, equity, and human rights must also be given significant weight in healthcare resource allocation decisions.

India should strengthen cost-effectiveness analysis by standardizing methodologies, increasing transparency in data collection and analysis, and establishing a clear willingness-to-pay threshold based on India's economic context. Furthermore, it's crucial to invest in capacity building among healthcare professionals and policymakers to ensure proper understanding and application of cost-effectiveness principles.

India's use of cost-effectiveness analysis is less formalized and standardized compared to countries like the UK or Australia, which have dedicated agencies like NICE (National Institute for Health and Care Excellence). This lack of formal structure can lead to inconsistencies in application and a lack of transparency. However, India's approach may be more flexible and adaptable to its diverse healthcare needs and resource constraints.

The most common trap is presenting a scenario where students instinctively choose the intervention with the lowest *overall* cost, without considering the health outcome. Examiners will often provide data requiring calculation of the cost-effectiveness ratio (cost per QALY or DALY) to identify the *most efficient* intervention, even if it's not the cheapest overall.

Students confuse them because both are used to measure health outcomes. However, QALYs measure the *benefit* of an intervention (years of life gained, adjusted for quality), while DALYs measure the *burden* of disease (years of life lost due to premature mortality and years lived with disability). QALYs are used to assess the value of interventions, while DALYs are used to identify health priorities and track disease burden.

Incremental cost is the *additional* cost of a new intervention compared to the existing standard of care, while the willingness-to-pay threshold is the *maximum* amount society is willing to pay for one additional unit of health outcome (like a QALY).

The most important change is the emphasis on standardized methodologies and transparent reporting. This means UPSC questions are more likely to focus on the *process* of conducting a cost-effectiveness analysis, including data sources, assumptions, and sensitivity analysis, rather than just the results.