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QALYfying life in policy decisions

Health and its benefits are difficult features to measure, which makes the evaluation of health policies a troublesome job. A simple way to quantify the benefits of an intervention is to estimate the increase in the life span, holding additional years of life as a proxy for health increases. However, the benefits cannot be estimated through the increase in the subject’s life expectancy alone – the quality of the life span has to be accounted for.

Quality-Adjusted Life Years (QALYs) come as a way to measure and combine increments in longevity and the utility of the health state with which those additional years will be lived. To simplify the computations, it is assumed that a state of perfect health is regarded as having a utility equal to 1 and the state of death yields a utility level of 0. Therefore, every condition that may impair the health stock will have a utility lower than one[1].

QALYs represent an important tool when performing health policy decisions by the cost-benefit analysis criterion, such as the approval of a new treatment or funding the development of a new drug. As utility is difficult to measure accurately, the QALYs will then measure the benefits of a given policy. In addition, as suggested by the literature, the QALYs provide a very powerful tool in welfare policy evaluation as they present a better proxy for overall wellbeing than the traditional sum of willingness to pay/willingness to accept[2]. Policymakers will then decide based on the alternative with the lowest cost to QALY ratio (or Incremental Cost Effectiveness Ratio), that is less costly option given its benefits.

QALYs have gained considerable importance over the last decade, despite the initial critiques to their usefulness and ethical content[3]. Nevertheless, the ethical arguments may still be plausible to mention, namely regarding the use of the QALYs for prioritizing conditions and groups of patients. If the criterion of QALYs is to be used when selecting which patients are more efficient to treat (i.e. which ones will cost less), or which conditions are expected to deliver more efficient results if treated, this puts equity concerns at stake.

Going beyond the scope of the ethical implications, there may be extra setbacks in this convention. By assigning a lower weight to the years with worse health states, the computation of the QALYs overlooks the absolute increase in life span. But, while it is true that the key point is to measure health benefits, increasing life may in fact increase medical costs in the future. The QALYs account for the quality of the years lived, but do not explicitly state the monetary costs those years will create. This happens because in the survey methods through which the weights of the conditions are estimated[4], people may not fully perceive the cost implications of a given health state and overestimate the level of utility it provides. The computation of a QALY may improve if the costs of the conditions were to be added to the estimation of the utility.

The QALYs are a helpful way of measuring the value of health outcomes, causing nevertheless a significant amount of controversy. Supporters advocate that problems of scarcity of resources call for the efficiency of this method, while others argue over the fact that it does not account for equity issues. But, of course, at the end of the day, it is in the hands of the policy makers and health economists to make the last call and decide the policies to follow.

Carla Ferreira #636


[1]  It is argued that a QALY can be negative, as some states of chronic and prolonged disease are considered to be worse than death, so the weighing factor cannot be restricted to the interval between 0 and 1

[2] Adler, M. “QALYs and Policy Evaluation: A New Perspective” (2005). Faculty Scholarship. Paper 57.

http://scholarship.law.upenn.edu/faculty_scholarship/57

[3] Harris, J. “QALYfying the Value of Life” (1987). Journal of Medical Ethics (13) 117-123

[4] Most popular methods are the Time-tradeoff and the Standard-gamble method.

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Author: studentnovasbe

Master student in Nova Sbe

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