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What Is A Quality Adjusted Life Year (QALY)?

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The term “quality-adjusted life year” or “QALY” is a measure of health outcomes pertaining to disease burden and is used to assess the value of medical interventions. As health can be defined as the length of life and the quality of life, the QALY combines the two factors into a single figure.

In other words, quality-adjusted life year measures how many additional months or years of life of a reasonable quality a patient or person may gain due to treatment. 

The QALY metric is essential in health economics, medical costs calculations, program evaluations, and insurance coverage determinations..

How Is Quality-Adjusted Life Year (QALY) Calculated?

In order to calculate the QALY and conduct an adequate cost-effectiveness analysis for treatments and clinical trials, two inputs must be considered: the utility value and amount of time people live in various health states. The quantifiable nature of QALY helps to understand the quantity and quality of a patient’s life, and its calculation is based on one year of their health status.

Thus, the QALY results range from 0 to 1, where 0 means death and 1 means perfect health in this period. In some circumstances, the calculation may also reflect health states that would be “worse than dead,” with a value of less than 1.

The methods that measure people’s willingness to trade time in different states of health make up the utility values used in this calculation. The following are factors  proposed in the Journal of Health Economics and are based on the answers of patients:

  1. Time-trade-off (TTO): respondents choose between remaining in ill health for a specific period of time or choosing perfect health with a shorter life expectancy.
  2. Standard gamble (SG): respondents choose between remaining in ill health for a specific period of time or medical intervention that could restore them to perfect health or kill them.
  3. Visual analog scale (VAS): respondents rate a state of ill health on a scale from 0 to 100, where 0 represents being dead, and 100 represents perfect health. The answers can have a solid subjective factor.

The weighting of a particular health state can also be determined using standard descriptive systems, such as the EuroQol Group’s EQ-5D questionnaire.

Examples of QALY’s Calculation

For example, if a patient lived in a situation with a utility of 0.5 or 0.5 QALYs, that person is only experiencing 50% of the possible value of that year. The patient living in less than perfect health for a period of time of one year is valued as much as the value of living half a year in perfect health.

In the next approach, let us think about an intervention that results in a patient living for four extra years rather than dying within one year. In this case, their quality of life would have dropped from 1 to 0.6. The following formula would be generated:

  • 4 years of extra life with a quality of life of 0.6 = 2.4
  • Reduced quality of life in less than 1 year (1 – 0.6)= 0.4
  • QALY value after the intervention = 2.0

This calculation serves as an indication of the benefits of medical procedures regarding the quality of life and survival of the patient. Therefore, it weighs the total life-years lost due to a disease or condition and those gained by a treatment on yearly basis.

Another example would be a patient that has enjoyed 2 years of perfect health, equaling a value of 2 QALYs. If this patient has 2 years of a health status valued at 0.5 and followed by another two years of perfect health, the calculation equals 3 QALYs.

Uses of QALY in Health Economics

The application and uses of QALY are mainly related to health economic evaluations as a measure of treatment outcomes. For example, most recently, the QALY measure has proven fundamental to the calculation and assessment of the cost-effectiveness of the COVID-19 vaccines in the United States. Moreover, the Pfizer-BioNTech COVID-19 vaccine is estimated to have increased the number of QALYs by over a million in the US, mostly by avoiding deaths.

The data shown on medical cost evaluations are often combined with QALYs to estimate the cost-per-QALY associated with a health care procedure. Hence, this information can be used to produce a cost-effectiveness study for any treatment and/or model, and properly allocate healthcare resources. With more evidence, policymakers can review a treatment’s health benefits and health-related quality of life for individuals with a specified health condition.. Cost-benefit research can then be developed with greater emphasis placed on different life-extending  procedures and reducing the burden of disease with a better cost-utility analysis.

In recent years, the use of QALYs has become increasingly utilized in different European countries. For instance, The National Institute for Health and Care Excellence (NICE) has used it to evaluate the utility of health technologies in the United Kingdom. In the Netherlands, the use of QALY is present on highways, local roads, and railway crossings’ security measures.

What Is the Difference Between QALY and DALY?

While Quality-Adjusted Life Year (QALY) was invented in the 1970s and has been a tool to measure life expectancy combined with the quality of life-years remaining, Disability-Adjusted Life Year (DALY) is a tool that emerged in the early 1990s and quantifies the burden of disease.

DALY sums the years of life lost due to premature mortality and the patient’s years in disability or disease. Unlike QALY, DALY uses a severity scale where 0 means perfect health and 1 means death. Both cannot be used interchangeably and produce different results depending on age at disease onset and disease duration.

In Conclusion

Although there is criticism about Quality-Adjusted Life Year regarding its theoretical assumptions—utility independence, risk neutrality, and constant proportional tradeoff behavior—and the difficulty to define perfect health, it is an increasingly used measure in health economics. 

It is easy to calculate and it works as a measure of the value of health outcomes. In the future, the data used to calculate it might be extended to include factors such as well-being to value outcomes, and explore further improvements or replacements.