Health economics is concerned with issues related to scarcity in the allocation of health care. The basic tasks of any economic evaluation are to identify, measure, value, and compare the costs and benefits of alternatives being considered. Traditional means of measuring benefits in the delivery of health care have concentrated on improvements in health outcomes using clinical outcomes and Quality Adjusted Life Years (QALY). The QALY is a measure of the quantity of life gained weighted by the quality of that life. QALYs are extensively used in economic analyses in health care. They claim to capture the health outcome benefits caused by an intervention . However, benefits of a health care intervention or service can be many-sided, e.g. containing non-health outcomes (e.g. amount of information) and process characteristics (e.g. treatment location, route of drug administration, patient experienced burden of testing). For instance, is ‘reduction of dying from cervical cancer’ the only screening characteristic that is considered by women attending a cervical cancer screening programme? Evidence shows that, within the context of cervical cancer screening, women’s preferences for various programmes are also determined by other characteristics than the reduced chance of dying from cervical cancer. Individuals are willing to trade changes in health outcome (change in chance of dying from cervical cancer) with process characteristics (time between smears, time for results, chance of being recalled, chance of abnormality, cost of each smear). This is just one example that illustrats that utility (benefit, satisfaction) of an intervention is derived from both health outcomes and process- and non-health outcomes. Other studies showed that this result is not specific to cervical cancer screening. This suggests that, assuming the goal of health interventions or services is to maximise utility, the value of process attributes and non-health outcomes should be considered alongside health outcomes. These might be relevant for individuals’ preferences and acceptability for specific health care interventions (i.e. demand-led health care), and for some interventions that do not provide reduction in morbidity or mortality (e.g. cosmetic surgery).

discrete choice experiments, health care, quality of life
E.W. Steyerberg (Ewout)
Erasmus University Rotterdam
Erasmus MC Rotterdam, J.E. Jurriaanse Stichting
Erasmus MC: University Medical Center Rotterdam

de Bekker-Grob, E.W. (2009, November 25). Discrete Choice Experiments in Health Care: theory and applications. Erasmus University Rotterdam. Retrieved from