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What is a QALY?

This video explains how to calculate QALYs.
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When we are making decisions about how to allocate health care resources across many different interventions, and for many different patient groups, it is extremely difficult to compare benefits if we’re using lots of different PROMs, all for different clinical areas. To compare evaluations, we need a single measure of benefit. One solution to this is the Quality Adjusted Life Year, or QALY. A QALY combines length of life and quality of life into a single index measure. When we are looking at evaluating the benefits of treatments, some treatments may have an impact on length of life, some on quality of life, and some on both together. The QALY takes both of these into account.
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QALYs give us a common unit of benefit, which we can use in an economic evaluation to compare interventions both within and between clinical areas. To calculate QALYs, we multiply the length of life by the quality of life. Length of life is typically measured in years. And quality of life is measured on a scale of 0 to 1, where 1 is equivalent to perfect health and zero is equivalent to dead. For example, six years lived in perfect health, valued as 1, would give 6 x 1, which equals 6 QALYs. 10 years, lived at a quality of life valued as 0.5 would give 10 x 0.5, which equals 5 QALYs.
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To compare treatments, we can calculate the number of QALYs for each and work out the difference between them to see if there is a QALY gain. Let’s look at a few examples. Firstly, we’ll look at an example where just length of life is affected. Imagine we are comparing a new treatment for heart failure with an existing treatment. The new treatment would extend a person’s life by one year, from four years to five years. But there is no change in quality of life, which remains constant at 0.5. To find out the QALYs gained by using the new treatment, we need to work out the difference between the QALYs for each alternative.
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With the existing treatment, a patient can expect to live for four years, at a quality of life valued as 0.5. 4 x 0.5 equals 2, therefore the existing treatment has a total of 2 QALYs. With the new treatment, a patient can expect to live for five years with the same quality of life. 5 x 0.5 equals 2.5. Therefore the new treatment has a total of 2.5 QALYs. The QALY gain is the difference between the two. So 2.5 minus 2 equals 0.5. Therefore, the QALY gain is 0.5 QALYs. Next, let’s look at an example where only the quality of life is affected. Imagine we are comparing a new treatment for bowel cancer with an existing treatment.
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Using the new treatment would not extend a person’s life, but would increase the quality of their life from 0.6 to 0.7. With the existing treatment, a patient can expect to live for 4 years, with a quality of life valued as 0.6. 4 x 0.6 equals 2.4. Therefore, the existing treatment has a total of 2.4 QALYs. With the new treatment, the patient will live for the same amount of time, but with a quality of life valued at 0.7. 4 x 0.7 equals 2.8. Therefore, the new treatment has a total of 2.8 QALYs. 2.8 minus 2.4 equals 0.4. Therefore, the QALY gain is 0.4 QALYs. Finally, let’s consider an example which impacts on both quality and length of life.
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Imagine we are comparing a new treatment for kidney failure with an existing treatment.
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The new treatment would extend a person’s life by 4 years, from 2 years to 6 years, and increase quality of life from 0.75 to 0.8. With the existing treatment, a patient can expect to live for 2 years, at a quality of life valued as 0.75. 2 times 0.75 equals 1.5. Therefore, the existing treatment has a total of 1.5 QALYs. With the new treatment, the patient can expect to live for 6 years, at a quality of life valued at 0.8. 6 times 0.8 equals 4.8. Therefore, the new treatment has a total of 4.8 QALYs. 4.8 minus 1.5 equals 3.3. Therefore, the QALY gain is 3.3 QALYs.
In the previous step, we saw that the use of different PROMs for different interventions and for different patient groups means that we do not have a single measure of benefit, which makes comparing healthcare interventions nearly impossible.
In this video, Katherine demonstrates how to calculate Quality Adjusted Life Years or QALYs; a unit of benefit that can be used to assess the extent of the benefits gained from a variety of healthcare interventions.
To calculate QALYs, we multiply the length of life expected to be gained by the new treatment or invention by the quality of life a patient can expect to have.
  • The length of life can be measured in trials, but will often require extrapolation beyond this period using assumptions and other data sources. For example, if we know that a drug reduces cholesterol and we know that cholesterol is linked to heart disease and therefore to mortality, we can use this information to estimate length of life. Alternatively, we can use large epidemiology studies that help estimate life expectancy based on conditions, age and gender.
  • Quality of life is measured on a 0 – 1 scale and this score represents the value of different levels of health. We’ll be exploring what these numbers mean and where they come from later on in the week.
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