We frequently hear about new, extremely high-cost medicines that patients or their families try to access but cannot, due to the lack of coverage from public or private insurance. This situation becomes a complex dilemma for decision-makers and a dramatic reality for patients and their environment.

Deciding whether or not to cover a given new health technology (medicines, vaccines, medical devices, etc.) in a context of limited healthcare system resources requires sophisticated capabilities—technical, political, and expectation management alike.

In this context, Health Technology Assessment (HTA) has been, and continues to be, a fundamental process for informed decision-making in healthcare, where the concept of value plays a crucial role. But what does value mean in this setting?

The use of economic evaluations—particularly cost-effectiveness analysis and cost-utility analysis—to assess the incremental benefit of new health technologies has grown significantly over the past three decades. In this framework, the focus has mainly been on determining the so-called quality-adjusted life years (QALYs) provided by a new technology, which has become the preferred metric for assessing health benefit.

However, using QALYs to evaluate the value of a new health technology presents several challenges and limitations.

First, the valuation of quality of life is inherently subjective and may vary significantly across individuals and cultures. Surveys and methods used to capture patient preferences regarding health states may fail to adequately reflect all relevant dimensions of quality of life.

Moreover, some health benefits—such as pain reduction or improvements in daily functioning—can be difficult to quantify in QALY terms. Less tangible outcomes like mental health, psychological well-being, and patient satisfaction may also be inadequately captured.

The use of QALYs may lead to discrimination against people with chronic disabilities or poorer baseline health conditions, since improvements in quality of life for these groups may be smaller compared to healthier individuals. This can result in funding decisions that disadvantage certain patient groups, even when they could benefit substantially from interventions. The Institute for Clinical and Economic Review (ICER) has reported that, to complement the use of QALYs in patients receiving life-extending treatments with chronic disability, the equal value of life-years gained (evLYG) measure could be used. This approach evaluates life extension equally for all individuals, regardless of baseline quality of life, helping decision-makers ensure that assessments do not discriminate against specific patient groups.

Likewise, decisions based on QALYs can raise ethical dilemmas, such as how to weigh life extension versus improvements in quality of life—particularly relevant in diseases such as cancer. Resource allocation based on QALYs may involve difficult ethical judgments about the value of different health states, oversimplifying complex health decisions by reducing multiple benefit dimensions into a single metric.

In addition, QALYs may not adequately capture contextual factors such as the broader social and economic value of health interventions, since societal preferences and priorities are not always well represented.

Estimates of QALYs may also vary significantly depending on the methodologies used and the study population, complicating comparisons across studies and informed decision-making—although efforts have been made to address this issue.

What solutions exist?

To address the limitations of relying exclusively on QALYs in HTA, several alternative approaches and complementary methods have been proposed. These aim to provide a more comprehensive and fair assessment of the benefits and costs of health interventions.

One such approach is Multi-Criteria Decision Analysis (MCDA), which considers additional dimensions beyond QALYs, including clinical, economic, social, and ethical aspects. This facilitates the incorporation of preferences and values from different stakeholders, such as patients, healthcare professionals, and society at large. However, it is important to note that implementing MCDA can be extremely challenging from a methodological perspective. In recent years, efforts to promote its use have been driven by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR).

Another approach involves the use of Patient-Reported Outcome Measures (PROMs), which aim to directly capture patients’ perceptions and experiences regarding their health and quality of life. These include dimensions such as emotional well-being, pain, physical functioning, and treatment satisfaction, offering a more holistic view of the impact of an intervention. PROMs may be particularly useful in specific diseases, such as rare conditions.

There have also been efforts to explicitly incorporate equity and social justice criteria into assessments, ensuring that decisions do not discriminate against vulnerable or disadvantaged groups. This includes considering the distributional impact of interventions to ensure that both healthy populations and those with disabilities or chronic conditions benefit. In this context, Distributional Cost-Effectiveness Analysis (DCEA) has been proposed to assess how health benefits are distributed across population groups, using methods that aim to maximize both population health and equity.

A continuing challenge

As can be seen, capturing the full value of a new health intervention through economic evaluation is far from trivial. The debate has evolved between, on one hand, more standardized and simpler methods (such as QALYs), which may fail to capture the full value of an intervention, and, on the other, efforts to develop more sophisticated approaches, which face practical challenges in implementation.

Continuing this debate is both necessary and critical in order to achieve international consensus that properly balances methodological sophistication with feasibility. This would help ensure that decisions on whether or not to cover a given technology are as objective as possible.

Ultimately, this will support more efficient use of scarce healthcare resources, increase the social legitimacy of decision-making processes, and—most importantly—generate greater benefits for patients.