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The ‘Q’ in the QALY: are we fudging it?

Some recent research from the Centre for Health Economics at Monash University has quantified something that we are all aware of: fudging in the measurement of health-related quality of life. They have found that, on average, randomly changing from one health-related quality of life measure to another changes cost-effectiveness results by 41%. This is clearly huge.

Health-related quality of life?

I am of the opinion that health-related quality of life is not something that, at least in any objective way, actually exists. The extent to which health-related aspects of life affect overall quality of life differs across people, places and time. Discrepancies can become apparent on two levels:

  1. What we perceive as dimensions of health may or may not affect an individual’s subjective level of overall health, and
  2. The relative importance of health in defining overall quality of life, compared with other aspects of life, can vary. This issue has been addressed in relation to adaptation.

These discrepancies translate into an inconsistency in the valuation processes we currently use. The people from whom values are being elicited are seeking to maximise utility (at least, this is what we assume), while the researcher’s chosen maximand is health-related quality of life. This means that any dimension of the chosen measure that can affect non-health-related quality of life will skew the results. As such we end up with a fudge that combines (objective) health characteristics and (subjective) preferences. I believe that, eventually, we will have to settle on a stricter definition of the ‘Q’ in the QALY, and that this will have to be based entirely in either objective heath or (subjective) utility.


An approach to measuring ‘health’ would not be entirely dissimilar to our current approach, but an ‘objective’ health measure would have to be more comprehensive than the EQ-5D, SF-6D, AQoL and other similar measures. Of existing measures, the 15D comes closest. It could include items such as mobility, sensory function, pain, sexual function, fatigue, anxiety, depression and cognition, which the individual may or may not consider dimensions of their health, but which could define health objectively. These would involve a level of subjectivity in that they are being assessed by the individual, but they are less contextual; items such as self-care, emotion, usual activities and relationships, from current measures, are heavily influenced by the context in which they are being completed. The instrument could then be valued using ranking exercises to establish a complete set of health states, ranked from best health to worst health. Dead can be equated to the worst possible health state, as all other outcomes are, in terms of health, an improvement upon death. If all valuations are completed relative to other health states, rather than to ‘death’, much of the distortion of non-health-related considerations will be removed.

I see no reason why the process should involve the elicitation of preferences. A health service does not seek to maximise utility. Evidence-based medicine does not aim to make people happier. Health care – particularly that which is publicly funded – should seek to maximise health, not health-related quality of life. If a person does not wish to improve their own health in a given way, they can choose not to consume that health care (so long as this is not detrimental to the health of others). For example, an individual may choose not to have a cochlear implant if their social network consists largely of deaf people [thanks, Scrubs]. Surely this should be the role of preferences in the allocation of health care.

Quality of life

At the other end of the scale we have a measure of general well-being. In some respects this is the easier approach, though there remains unanswered questions; for example, do we wish to measure present well-being or satisfaction with life? These approaches are simpler insofar as they require only one question such as, ‘how happy are you right now?’ or ‘how satisfied are you with your life overall?’. These questions should be posed to patients. Again, I do not see any benefit of using preferences or capturing decision utility in this case; experienced utility gives a better indication of the impact of health states upon quality of life. This approach could provide us with a measure of utility, so we could implement a cost-utility analysis (which is by no means what we do currently).

The two approaches described here could be used in conjunction. They would provide very different results, as the early findings from Monash demonstrate. A public health service should maintain health as its maximand, but other government departments or private individuals could provide funding for interventions that also benefit people in ways other than their health, or improve the rate at which individuals can derive utility from their health (e.g. education, social housing, social care).

I have little doubt that our current fudging approach – of maximising mainly-but-not-completely-health-related quality of life – is the best thing to do in the meantime, but I suspect it isn’t a long-term solution.

DOI: 10.6084/m9.figshare.1186883

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