# Deriving monetary value of quality-adjusted life years through life extension from the value of a statistical life

## TL;DR

This paper introduces a new way to calculate the value of quality-adjusted life years using life extension data to improve healthcare resource allocation decisions.

## Contribution

A novel framework for estimating QALYs based on the value of a statistical life, incorporating age and regional factors for more accurate cost-benefit analysis.

## Key findings

- Updating QALY estimates with regional characteristics improves cost-benefit analysis accuracy.
- Incorporating age and quality of life changes leads to a more rational QALY estimation.
- The proposed method supports efficient healthcare resource allocation and budgeting decisions.

## Abstract

To address the recent rise in healthcare expenditure due to an aging population, the rational allocation and efficient use of resources, based on scientific evidence, have become indispensable. This study proposes an alternative framework for estimating quality-adjusted life years (QALY) based on the value of statistical life, which can be used for cost-benefit analysis (CBA) of policy interventions and the efficient allocation of healthcare resources. Specifically, we estimate the monetary value of a QALY based solely on life extension. We assess the accuracy of conventional QALY estimates while proposing a new, more rational, and flexible QALY estimation that combines age and scenario factors. Our numerical analysis suggests that updating QALY by considering regional characteristics such as population, age distribution, and changes in quality of life (QoL) can lead to a more accurate CBA. This metric provides information for decision-making in policy budgeting based on scientific evidence and suggests that this approach may contribute to a more efficient allocation of healthcare resources. Furthermore, increasing the proportion of healthy individuals with a gradual decline in QoL may support efforts to reduce healthcare expenditure.