What are QALYs or Quality Adjusted Life Years?

QALYs are a generic measure of health that combines mortality and morbidity. It takes years of life and then adjusts these for the quality of life experienced, using utility weights - values on a 0-1 scale, with 1 representing full health and 0 said to represent dead or the worst possible state, equal to death. The way these two aspects are then combined is as follows. If you take 2 years of life lived in full health, with a utility weight of 1 then this represents 2 QALYs e.g 2 x 1 = 2. However, if you take these same two years and these are lived in half health, equivalent to a 0.5 utility weight, this will equate to 1 QALY, 2 x 0.5 = 1. So, life years and quality of life combine into one number that represents the quality of a year's life experienced.

QALYs allow measurement of disease impact in a simple score and provide a broad perspective of impact, rather than focusing on a single trial outcome. 

Common application is in HTA, to estimate the impact of interventions and to compare across options. This includes economic evaluation, as part of cost-utility analysis.

As a common measure, it can be used across a health system to assess the relative benefits of different programmes, useful if there is a central budget to allocate across different priorities or disease areas.

The disadvantages often cited are that QALYs have the potential to discriminate against certain populations, the measure is too broad and can therefore miss important health and disease-specific impacts.

As with anything, they have their benefits and drawbacks and are imperfect but fundamentally they provide the means to estimate and compare. Where they are used to support decision-making, they are generally considered a tool to aid decision-making, alongside other inputs in a wider value framework and set of decision-making criteria.

From an evidence perspective, some thoughts come to mind. Given the two inputs, life years and utility weights, this evidence has to be generated. If via clinical trials, these outcomes will have to be included in the protocol; considerations about which particular outcome is to be included; how practical the inclusion of a particular outcome is versus everything else that is being measured; the performance and validity of certain measures in the target disease area and how generalisable the data from one study will be. If evidence is not generated via clinical trials, then one also has to consider how will this evidence be generated. Attention also turns to how this evidence will be used, e.g. as part of economic evaluation, where in the world it will be used, to name just a few.

1. Brazier J, Ratcliffe J, Salomon J, Tsuchiya A. Measuring and Valuing Health Benefits for Economic Evaluation. Second. Oxford: Oxford University Press; 2017.
2. Drummond, M., Sculpher, M.J., Claxton, K., Stoddart, G., Torrance, G., 2015. Methods for the economic evaluation of health care programmes, Forth. ed. Oxford University Press.
3. Garrison, L.P., Neumann, P.J., Willke, R.J., Basu, A., Danzon, P.M., Doshi, J.A., Drummond, M.F., Lakdawalla, D.N., Pauly, M. v., Phelps, C.E., Ramsey, S.D., Towse, A., Weinstein, M.C., 2018. Value in Health 21, 161–165.
4. Stevens, A., Doyle, N., Littlejohns, P., Docherty, M., 2012. J Med Ethics 38, 258–26
5. Turner, H.C., Archer, R.A., Downey, L.E., Isaranuwatchai, W., Chalkidou, K., Jit, M., Teerawattananon,Y., 2021. Front Public Health 9