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A quality-adjusted life year (QALY) is a single number that measures both how long someone lives and how well they live during that time. One QALY equals one year in perfect health. It lets healthcare systems compare treatments with different survival and quality trade-offs on the same scale.
- A QALY multiplies years of life by a quality-of-life weight between 0 (death) and 1 (perfect health), producing a single comparable metric across different treatments.
- QALYs have been the standard tool for cost-effectiveness analysis in healthcare for more than 30 years, used by major health systems to allocate resources.
- The metric treats all years equally regardless of who receives them, which raises equity concerns when a treatment benefits a small group or a rare disease.
- QALYs measure healthy years gained, while DALYs measure healthy years lost, and the two scales run in opposite directions.
- Quality-of-life weights come from surveys and preference studies, not from clinical measurements, which means they capture what people report about their own well-being rather than objective health status.
A quality-adjusted life year (QALY) is a single metric that combines how long someone lives with how well they live. One QALY equals one year lived in perfect health. It lets healthcare systems and researchers compare treatments that work in different ways: one drug might add years but leave someone in pain; another might reduce pain but add fewer years. Without a common scale, choosing between them is impossible. The QALY provides that scale.
This metric has become the academic standard for measuring treatment value. Health systems use it to decide which drugs and procedures to fund. Researchers use it to weigh the benefit of one intervention against another. Understanding how it works, and what it cannot do, is essential for anyone reading health policy, evaluating clinical evidence, or working in healthcare economics.
What a quality-adjusted life year actually is
A QALY is a number that captures two things at once: how many years someone lives, and how good their health is during those years. It is expressed as a decimal. One QALY means one year of perfect health. Half a QALY means either half a year of perfect health, or one full year at half the quality of life. The scale runs from 0, representing death, to 1, representing perfect health.
The power of the QALY is that it lets you compare completely different treatments on a single axis. Suppose one drug adds two years to someone's life but leaves them with moderate pain and limited mobility. Another drug adds one year but restores them to near-normal function. Without a shared measure, you cannot say which is better. With QALYs, you can: if the first treatment delivers 1.4 QALYs and the second delivers 0.95, the numbers tell you something about the trade-off. The choice is still a values question, but the comparison is now possible.
How QALYs are calculated
A QALY is calculated in two steps. First, estimate how many years someone will live with the treatment. Second, assign a quality-of-life weight to those years. Multiply them together and you have your QALY count.
Measuring life expectancy
The years component comes from clinical data: survival curves from trials, epidemiological studies, or disease registries. If a treatment is expected to extend someone's life by five years, that is your starting number. The years are usually measured from the point of treatment onward, not from birth. In cost-effectiveness studies, researchers often project life expectancy to the end of life, not just the duration of the trial. This projection requires assumptions about what happens after the study ends, which introduces uncertainty but is necessary for a fair comparison across treatments with different follow-up periods.
Assigning quality-of-life weights
The quality weight is a decimal between 0 and 1 that represents how good life is in a particular health state. Perfect health is 1. Death is 0. A health state with moderate pain and limited mobility might be weighted at 0.7, meaning a year in that state counts as 0.7 QALYs. A more severe state, such as advanced dementia with total dependence on others, might be 0.4.
These weights do not come from doctors or from clinical measurements. They come from surveys of patients, the public, or both, asking people to rate how much they value different health states. Two widely used instruments are the EQ-5D and the SF-6D, which ask respondents to describe their health across dimensions like mobility, pain, and anxiety, then convert those descriptions into a single utility score.
Suppose a treatment for heart disease keeps someone alive for ten years but leaves them with chest pain on exertion and fatigue that limits daily activity. A quality-of-life survey might assign that state a weight of 0.75. The QALY count would be 10 years times 0.75, or 7.5 QALYs. If another treatment adds only six years but restores full function (weight 1.0), it produces 6 QALYs. The first treatment delivers more total health, even though it adds more years, because the quality difference matters.
Why QALYs guide healthcare decisions
A healthcare system cannot fund every treatment. Money is finite. QALYs provide a way to compare the value of different uses of that money. A common comparison is the incremental cost-effectiveness ratio, or ICER: the cost per QALY gained by choosing one treatment over another.
Suppose treatment A costs £50,000 and delivers 5 QALYs. Treatment B costs £40,000 and delivers 3 QALYs. The ICER for choosing A over B is (£50,000 minus £40,000) divided by (5 minus 3), or £5,000 per QALY. Health systems then ask: is £5,000 per QALY a reasonable price? In the United Kingdom, NICE has traditionally used a threshold of £20,000 to £30,000 per QALY. If the ICER is below that threshold, the treatment is usually approved. If it is above, it is usually rejected.
This framework lets systems make consistent choices. Without it, decisions depend on advocacy, politics, or the charisma of the patient group. With it, a rare disease and a common one are judged by the same metric: how much health does the money buy? That consistency is powerful, though it is also controversial, as we will see.
What QALYs cannot capture
QALYs are useful, but they are not complete. Several important aspects of health and healthcare fall outside the framework, and recognizing those gaps is essential for interpreting QALY-based decisions.
Equity and distribution
A QALY is a QALY, regardless of who receives it. If one treatment produces 10 QALYs for a wealthy patient and another produces 10 QALYs for a poor patient, the QALY metric sees them as equal. Many people do not. They believe that reducing health inequality matters, or that helping the worst-off should count for more, or that some groups have been historically neglected and deserve priority now.
QALYs are silent on these questions. They measure total health gain, not how fairly that gain is distributed. A policy that produces 100 QALYs by helping 100 people gain one year each looks identical to one that produces 100 QALYs by helping one person gain 100 years. The math is the same. The fairness is not. This is not a flaw in the QALY itself, but rather a reminder that QALY efficiency and equity are separate values, and a healthcare system must decide how to balance them.
Rare diseases and small populations
Rare diseases affect few people. A treatment for a rare disease might deliver high QALYs per person but low total QALYs because the population is small. If a QALY-based system allocates resources by total health gain, rare disease treatments will rarely be approved, even if they transform the lives of the people they help.
This creates a tension. A treatment that adds one year of perfect health to 100,000 people produces 100,000 QALYs. A treatment that adds ten years of perfect health to 1,000 people produces 10,000 QALYs. By QALY logic, the first is ten times more valuable. But the second treatment may be the only hope for those 1,000 people. Some health systems address this by weighting rare disease treatments differently or by setting aside funding specifically for them, recognizing that QALY efficiency alone does not capture what matters to patients with no alternatives.
QALYs and related metrics you will encounter
QALYs are one of several metrics used to measure health outcomes and guide resource allocation. Knowing the related concepts will help you interpret evidence and policy documents.
The DALY, or disability-adjusted life year, measures the opposite: healthy years lost rather than gained. A DALY is calculated as the sum of years of life lost due to premature death and years lived with disability. The scales also run in opposite directions. For QALYs, 1 represents perfect health and 0 represents death. For DALYs, 0 represents perfect health and 1 represents death. DALYs are used primarily in public health and epidemiology to measure disease burden, while QALYs are used in healthcare economics to evaluate treatments.
The cost-effectiveness threshold is the price per QALY that a health system is willing to pay. Different countries set different thresholds. The UK threshold of £20,000 to £30,000 per QALY is one example. The United States has no official threshold, though researchers often use $50,000 to $150,000 as a rough benchmark. These thresholds reflect a society's judgment about how much health is worth buying.
The incremental cost-effectiveness ratio, or ICER, compares two treatments head-to-head: the cost difference divided by the QALY difference. An ICER tells you how much extra you pay for each extra QALY when you switch from one treatment to another. It is the number that gets compared to the threshold to decide whether a treatment is approved.
Do this automatically
Calculating QALYs requires clinicians and health economists to extract survival data from multiple sources, assign quality-of-life weights through validated instruments, multiply these components together, and repeat this process across different treatment scenarios to compare cost-effectiveness ratios, a labor-intensive workflow that compounds when healthcare systems must evaluate dozens of interventions simultaneously. Software can automate the data aggregation, weight assignment, arithmetic, and comparative analysis to produce QALY calculations on demand. Healthcare research runs this kind of analysis end to end and cites every figure back to its original source, across as many subjects as you need, with Mimir attaching a citation to every figure. It will not predict a trial's outcome or advise on anyone's treatment. Those decisions stay with clinicians and regulators, and deliberately so. Every plan includes it, including the free one.
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This article is general information about healthcare and life-sciences topics. It is not medical advice, diagnosis, or treatment guidance, and it is not a substitute for a qualified professional. Any treatment decision should be discussed with a clinician.
