Abstract

Assessing preferences for treatments among family members of people with drug dependence is a key issue due to the externalities that these pathologies generate. The willingness to pay method allows researchers to obtain a monetary valuation of the intangible effects of these pathologies on family members. Drug use causes multiple consequences that the cost of illness literature usually classifies as direct (e.g. cost of health care), indirect (e.g. lost productivity) or intangibles (mainly loss of quality of life). Although the study of these consequences is usually focused on the drug user, these problems also directly affect their family members and relatives, as well as society as a whole 1. Quantifying the consequences of drug use is therefore of great interest to avoid underestimating their importance 2, 3. Within the economic evaluation of health programs framework, the literature shows different approaches to quantifying the effect of addictions in the family environment 4-6. The choice of measurement tool will depend largely on the variable under study. Focusing on intangible costs, if the objective is to measure the loss of health-related quality of life, the use of instruments proposed in cost–utility analysis studies is widely supported. Scales such as the Euroqual (EQ)-5D 7 or the Short form (SF)-6D 8 allow researchers to measure variations in quality of life and estimate losses in quality-adjusted life years 9, 10. I disagree with Shanahan et al.’s claim that the SF-6D is insensitive to the impact of drug dependence 11. This insensitivity appears to be the result of the test having a ‘floor’ effect that makes it insensitive towards discriminating small health gains in the worst-case scenarios. Part of this ‘floor’ effect seems to be due to the standard gamble technique used to obtain the test's weights. Abellán et al. have demonstrated how the use of double lottery or equivalent lottery techniques allow us to obtain weights that reduce this effect 12. Thus, there are some experiments and preference studies in which SF-6D has been shown to be sensitive to the impact of alcohol dependence 6, 10. However, if the goal is to measure other aspects, besides loss of quality of life, the willingness-to-pay method emerges as a good candidate. This recent methodology was initially proposed to assess the impact of environmental policies, but little by little it was extended to other areas, such as health interventions. This approach allows quantification of the monetary value of an intervention for a specific subject, for their family members or for society. In addition to this, said values can be incorporated later on in cost–benefit analysis studies. There are examples in the literature of researchers applying this approach to questions around illegal drugs 13-15 and alcohol 16, 17. In the paper by Shanahan et al. 11, the willingness to pay approach is adopted within a discrete choice experiment study, to assess preferences for treatment for heroin dependence among the subjects’ family members. The advantage of a discrete choice experiment is that it allows researchers to quantify preferences for several aspects of the problem and, therefore, the quantification of a monetary value for each of them. To do this, the authors identify, based on the literature, the aspects of the problem that are most relevant to the family members and then they estimate the willingness to pay for the hypothetical improvements in the aspects analyzed. The advantage of this strategy is that it not only allows one to obtain the willingness to pay for a specific treatment, but also allows one to estimate and compare the value to family members of different treatment scenarios. This type of study may be relevant both in clinical and economic settings. At the clinical level, it is not only of interest to involve family members in the treatment of the addict, but also to assess the loss of quality of life that they themselves experience. On an economic level, these types of analyses may be relevant both for their application in cost of illness studies—they permit an identification of the intangible costs analyzed in this literature 18—as well as for economic evaluation studies that lead to decisions on prioritization of health resources 19. In addition to this, although it is just a pilot study, Shanahan et al. show an analysis methodology that may be of interest to researchers who want to monetarily quantify different intangible consequences of addictions. None.

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