Previous research investigating the cost-effectiveness of a reduction of alcohol consumption only took into account the health effects in heavy drinkers [11
]. However, since alcohol taxes cannot be targeted at this specific group of drinkers (the definition of heavy drinking in that study equals our categories of excessive and dangerous alcohol consumption together), health effects in the entire population, including moderate drinkers, need to be considered. Moderate drinkers even experience some disutility from a tax increase, making this policy a no Pareto improvement, but rather a Kaldor-Hicks improvement, whereby those people worse off theoretically can be compensated for by those persons that are better off with a certain policy option. Another difference with respect to the WHO-CHOICE study is how health effects were modelled. In the WHO approach, alcohol itself was modelled with a direct effect on mortality and quality of life. In our study, we modelled effects on quality of life and mortality through the effects of alcohol on alcohol-related diseases and all-cause mortality. We focused on the dynamic effects of alcohol tax increases on health effects in drinkers themselves and their associated health-care costs.
Although in theory an alcohol tax increase can be implemented by legislation alone, some administrative costs and possible costs of law enforcement to keep smuggling to a minimum have to be made to successfully implement a tax increase. These costs, as well as additional tax revenues, are usually carried by sectors outside the health-care sector. Therefore, for an alcohol tax increase, taking the health-care perspective effectively illustrated the advantages compared with interventions whose costs traditionally fall inside the health sector, such as treatment of alcohol addiction or curative treatments in a hospital setting.
Like all economic evaluation modelling studies, the calculated costs, effects and cost-effectiveness ratios are conditional on various assumptions. Below we will discuss some of the assumptions we made to estimate the cost-effectiveness of increasing alcohol taxes. First, price elasticity is the same for moderate, excessive and dangerous drinkers. If, for instance, dangerous drinkers react less to price changes than moderate drinkers [3
], health effects of tax increases may be smaller than we estimated. However, there are contradictory findings on the exact price elasticity of dangerous drinkers [26
]. Second, all tax increases were translated into price increases. We did not take into account the possibility that producers do not pass on the tax increase to consumers, resulting in a decrease in their profit margin. However, if producers only partially pass on the tax increase to consumers, this will only decrease the amount of health gains but not influence the cost-effectiveness. Third, the effects of a tax increase on alcohol consumption will be sustained in the long run. This assumption is built on studies that argue that, since alcohol consumption is addictive, the long-run price elasticity is significantly higher than the short-run elasticity. Fourth, the price elasticity is the same for high as for small price increases. This is due to the fact that estimates of price elasticity are estimated on time series with mainly small price variations over time. Again, this assumption is probably more important for the estimation of the amount of health gains rather than the cost-effectiveness ratio. Fifth, we used price elasticities based on Clements et al [9
]. We preferred to use specific Dutch data, but the available estimates [28
] were not specific for the different alcohol products (beer, wine, spirits). In an analysis that did not include beverages sold in restaurants, bars and hotels, Leppänen et al [28
] found a high value of total elasticity for alcohol demand in the Netherlands (-1.5). However, in another analysis, they estimated the price elasticity for alcohol in the Netherlands at -0.53, which is close to the weighted average in our analysis that was based on the Clements elasticities (-0.61). Nevertheless, assuming higher values of price elasticity would result in more QALYs gained and increased health-care costs due to increases in life expectancy. For instance, modelling an elasticity of -1.5 for all alcohol types, 13,000 QALYs will be gained at costs of €65,000,000. So, while both QALYs and costs will increase, the ICER would remain almost unchanged.
In the comparative quantification of health risks study, health effects of average alcohol consumption and patterns of drinking were estimated separately [29
]. In this study we have limited ourselves to the effects of a tax increase on average alcohol consumption. This was done because the CDM models average drinking and the demand elasticity estimates for alcohol also refer to average alcohol drinking. Data on the influence of patterns of drinking are less available than data on overall consumption, but evidence is accumulating that patterns of drinking affect the link between alcohol and disease and mortality [29
]. For example, the same overall average volume of alcohol can be consumed in small quantities regularly with meals (for example, two drinks a day with meals) or in large quantities on a few occasions (for example, two bottles of wine on a single occasion every Friday). This also implies that we did not model the effects of a tax increase on alcohol dependence, which is a disorder in itself. The simulation model we employed did not model all diseases considered to be related to be alcohol consumption separately. Some were only modelled indirectly through an elevated mortality risk. This means that we may have underestimated the impact of alcohol consumption on quality of life and health-care costs and have overestimated the cost-effectiveness ratio. Furthermore, the relative risks employed in the CDM are not based on the most recent meta-analyses. However, the study by Holman et al [18
] was the only study that included relative risk estimates for the alcohol categories employed in the CDM for both diseases and mortality, and that provided estimates of all-cause mortality. Such a category of all-cause mortality was not used in other studies on the relative risks of alcohol consumption [23
]. In the simulation model we used these estimates of all-cause mortality to estimate the effects for the causes of death that are not explicitly in our model. Moreover, a recent meta-analysis of relative risks on all-cause mortality yielded similar estimates [19
], and a recent study from the comparative risk assessment collaboration group used comparable estimates of relative risks for specific alcohol-related diseases [30
In this study we have focused solely on health-care costs, ignoring broader costs and consequences of alcohol abuse to society. From a societal perspective, which is often advocated in economic evaluations [31
], other costs and consequences, such as the damage due to violence and accidents induced by binge drinking, need to be considered and may be substantial [32
]. Furthermore, since the price increase is not outweighed by the decrease in consumption, this also implies that tax revenues will increase if taxes are increased. It should be noted that from a societal perspective, tax revenues are transfer payments, which means that they do not increase production but simply that money flows from one place to the other. Therefore, in cost-effectiveness analyses from a societal perspective they should be omitted. However, if alcohol taxes are seen as a health policy instrument, a portion of the additional tax revenues could be added to health care [7
]. Consequently, it can be argued that in this case (part of) the administrative costs and costs of law enforcement associated with tax increases should also be taken into account [13
]. All in all, we expect an alcohol tax increase to be even more cost-effective when a broader societal perspective is taken.