A direct comparison of the two measures is presented in Gold et al. Although measured on similar scales, the former represent levels of quality of life enjoyed by individuals in particular health states, while the latter represent levels of loss of functioning caused by diseases.
The former are normally measured on a scale in which 1 represents full health and 0 represents death, therefore higher values correspond to more desirable states and states deemed worse than death can take negative values. The latter are measured on a scale in which 0 represents no disability, therefore lower scores correspond to more desirable states. The two types of weights are also derived in different ways, using different elicitation techniques and different groups of subjects.
In practice, DALY calculations tend to be based on a universal set of standard weights based on expert valuations, while QALY calculations often rely on preference-based health-related quality of life measures directly elicited from general population samples or from groups of patients.
The most common preference elicitation techniques are the standard gamble and the time trade-off, both choice-based Torrance These may be applied directly, or indirectly in the assessment of the value of individual dimensions of multi-attribute systems like the Health Utilities Index Torrance et al. Health profiles with constant quality of life. Note : Health profiles with intervention i solid line , and without intervention broken line. Health profiles with variable quality of life.
The calculation methods illustrated in the previous section will be applied in two examples, one on tuberculosis, a temporary non-fatal disease, and one on bipolar disorder, a chronic disease potentially affecting life expectancy. In both examples, it is initially assumed that the loss of quality of life determined by the respective diseases in QALY calculations is exactly equivalent to the level of disability estimated in DALY calculations i.
This assumption will be later relaxed to illustrate the impact of potential differences between the two. Finally, quality of life is assumed stable throughout the duration of the disease. An individual affected by tuberculosis will experience a temporary, non-fatal disability if the disease is appropriately diagnosed and treated. The level of disability attributed to tuberculosis in the GBD study varies in a relatively narrow range 0. Dion et al. Therefore, it is not possible to calculate conversion factors like those reported in Table 1.
Tsevat et al. Figures 4—6 illustrate how QALYs gained and DALYs saved vary in relation to changes in, respectively, age of disease onset a , duration of disability without treatment L , and disability weight with treatment D i. Benefits of preventing a potentially fatal disease: effect of age of disease onset a. Benefits of preventing a potentially fatal disease: effect of duration of disability without treatment L.
Benefits of preventing a potentially fatal disease: effect of disability weight with treatment D i. This paper provides an illustration of calculation methods for assessing quality-adjusted life expectancy and for measuring the outcomes of health interventions in terms of QALYs.
Two examples in different disease areas have shown that age of disease onset is an important factor determining variations between numbers of QALYs gained and DALYs saved, when interventions are compared using the two metrics. The pattern of variation is mostly dictated by the shape of the age-weighting function. These conclusions are based on the use of the age-weighting function originally proposed in the GBD study Murray and Lopez , still most widely applied in DALY calculations.
Results would have been different if based on a different function, or if QALYs had been age-weighted too, as advocated by some see Sassi et al. The examples have also shown that differences between quality of life and disability weights may cause further divergence between QALYs gained and DALYs saved.
In some cases, estimates of the loss of quality of life used in QALY calculations may be very close, or equal, to disability estimates used in DALY calculations. However, variations can often be expected in either direction. In our examples, we have used quality of life weights derived from the literature to illustrate the possible extent of such variations.
The examples in this paper are based on the assumption that the assessment of the relevant interventions is country-specific. Instead, the original formulation of DALYs for the GBD study was aimed at supporting cost-effectiveness comparisons on a global scale, therefore a standard life expectancy was assumed in order not to disadvantage populations with a shorter actual life expectancy.
The two approaches may lead to different results, an example being an intervention that avoids premature mortality caused by a given disease as in the second example above.
The standard life expectancy assumption leads to a consistently larger estimate of DALYs saved, and the difference is greater where actual life expectancy is shorter. Although QALYs and DALYs stem from the same broad conceptual framework, they are not interchangeable, as they are partly based on different assumptions and different methodologies for instance, methods for eliciting quality of life and disability scores.
Understanding systematic differences between the two measures is important for enabling policy makers to form a sound judgement on the existing evidence about the outcomes of health interventions. The author wishes to thank Mrigesh Bhatia for discussions that led to an earlier version of this paper.
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See also Experimental study. Qualitative research explores people's beliefs, experiences, attitudes, behaviour and interactions. It asks questions about how and why.
For example, why people want to stop smoking, rather than asking how many people have tried to stop. It generates non-numerical data, such as a person's description of their pain rather than a measure of pain. Qualitative research techniques such as focus groups and in depth interviews may be used when developing NICE guidance to find out more about the views and experiences of the target population or practitioners.
Five to 10 quality statements make up a quality standard. The statements describe key markers of high-quality, cost-effective care for a particular clinical condition or pathway. An example of a quality statement for stroke is: 'All patients after stroke are screened within 6 weeks of diagnosis, using a validated tool, to identify mood disturbance and cognitive impairment'. Skip to main content.
Expert insight:. Do you know what a QALY is, and how to calculate it? Therefore, the benefit of the new medicine will be counted as 0. Lieven Annemans. Next Session: November 24, , live online.
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