An aging population is redefining the value of a year of healthy life

As populations age and health care budgets tighten, a new valuation framework shows why the “price” of a healthy life year depends on who earns it and where policy choices may quietly allocate billions.

Study: Deriving the monetary value of quality-adjusted life years through life extension from the value of a statistical life. Image credit: THIHA SATAPITANON / Shutterstock.com

Effective evidence-based resource allocation using quality-adjusted life years (QALYs) is essential, especially as global life expectancy increases. A recent study published in Scientific Reports examines how accounting for age and demographic factors by country in QALY estimates can improve health care policy decisions and resource allocation.

Concerns about increased health care costs due to an aging population

Advances in medical technology and public health have led to a rapidly aging population worldwide, which contributes to increasing healthcare costs and social burdens. By 2040, healthcare spending in Japan is expected to nearly double, raising concerns about the sustainability of healthcare systems.

As similar demographic changes are expected in other developed countries, it is increasingly important to incorporate healthy life expectancy into policy decisions. Achieving sustainable health care will require judicious evidence-based resource allocation.

Tools that guide health care policy

Cost-benefit analysis in health care often uses value of statistical life (VSL) and QALY to guide policy and allocate resources. While VSL represents the monetary value people place on reducing mortality risk, QALY combines quality of life and life expectancy into a single measure.

VSL and QALY enable comparisons between health care policies and support evidence-based decision making. For example, organizations such as the UK’s National Institute for Health and Excellence use the QALY to evaluate medical technologies and guide the efficient use of resources.

Despite its widespread adoption, the use of QALY is associated with notable limitations. By applying the same value to all age groups, despite differences in health status and life expectancy, QALY estimates may lead to biased results. QALY values ​​can also be adopted by other countries without considering local populations and economic factors, which may affect the accuracy of policy evaluations and lead to inefficient allocation of resources.

A new QALY metric for health policy makers

The current study proposes a VSL-based QALY metric that takes health status and age-specific life expectancy into account while focusing on the monetary value of life extension rather than quality of life improvement. The VSL economic model was applied to estimate the life extension value (LEV).

LEV was then combined with quality of life (QoL) measures to calculate the monetary value of a QALY for any given age and scenario. Importantly, the analysis does not directly model policies that improve quality of life. Instead, it estimates life extension under different QoL trajectories. This quality of life framework was used to conduct policy evaluations using the QALY metric.

The researchers reported overall VSL estimates for each scenario, followed by age-specific and mean monetary values ​​of a QALY in millions of Japanese yen (JPY). By comparing QALY values ​​between scenarios, age-dependent differences in the value of a QALY were identified.

The VSL estimates for the SCN1, SCN2, SCN3, and SCN4 scenarios were quantified at 457.6, 468.6, 452.9, and 462.8 million JPY, respectively.

THE The monetary value of a QALY at different ages and scenarios was calculated using VSL. Weighted population means were calculated by multiplying the QALY values ​​of each age group by the population distribution and averaging the results.

In all scenarios, the monetary value per QALY increased with age. When comparing the scenarios, population-weighted mean QALYs were highest in SCN1, followed by SCN4, SCN3 and SCN2.

The standard range of QALY values ​​was compared with the highest and lowest values ​​for each age group. Between ages 20 and 60, SCN3 had the highest QALY monetary values, while SCN2 had the lowest.

Cost reductions were calculated based on the differences between the conventional QALY and the study’s age and scenario QALY estimates. If the QALY was set at five million JPY, a greater proportion of SCN1 led to a negative cost reduction, while a greater proportion of SCN2 was associated with a positive cost reduction.

Conclusions and future perspectives

Longer life spans and an aging population increase healthcare costs and pose challenges to the sustainability of current systems. The proposed VSL-based QALY approach enhances policy relevance by considering demographic factors such as age and quality of life.

Although the conventional and new QALY estimates were broadly aligned, the new method revealed more detailed variations by age and quality of life, which can be used to allocate health resources more efficiently. Taken together, these findings emphasize that policies aimed at extending healthy life expectancy could help control costs, although the analysis does not take into account the costs of preventive, educational, or social interventions needed to achieve such health improvements.

Further research is needed to apply this QALY estimation method to practical policy settings, with particular attention to avoiding double counting of consumption-related utility. Investigating alternative calculation methods, such as non-linear health-utility models, income-health interactions, and different discounting approaches, could also improve accuracy. Validation of the framework using international datasets beyond Japan and refinement of country-specific scenarios, especially those involving improvements in quality of life, will enhance future applications.

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