ABSTRACT
Introduction
This contribution gives an overview on estimating the economic impact of substance use (SU) and substance use disorders (SUDs) from a societal perspective.
Areas covered
In this Expert Review, we first discuss the scope of the economic costs of SU to society and the methods used to estimate them. In general, cost studies should not be limited to SUDs, but should also include costs related to the consequences of any type of SU to achieve a comprehensive picture of the societal burden. Further, estimating potentially avoidable costs will increase the value of cost studies. Importantly, methodologically sound cost studies shed light on the magnitude of societal problems related to SU and can be used as a reference point to evaluate regulatory policies and other preventive measures. The area of estimating potential economic benefits of SU is understudied and lacks a theoretical and methodological framework.
Expert opinion
Overall, economic studies on the impact of SU and SUDs can strongly contribute to better-informed decision-making in the creation of regulatory and control policies. The least developed area of research refers to a consensus methodology that could be used in studies which compare economic costs to potential economic benefits.
Article highlights
Economic impacts of substance use involve both costs and benefits.
Costs can be subdivided into direct and indirect tangible costs, as well as intangible costs. Among tangible costs, the three major sectors impacted are health care, the criminal justice system, and the economy.
Methodological advances in summarizing indicators allow for the costs attributable to substance use to be included in monitoring systems, and to then be used in the evaluation of control policy interventions.
Overall, the costs are substantial, and for the legal drug alcohol these costs far outweigh the income derived from taxation and other duties. However, there is no established methodology to compare the economic costs and benefits of substance use.
The framework of avoidable costs can be used to model policy interventions to predict their outcomes, i.e. to use such models to help in decision-making.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewers Disclosure
Peer reviewers of this manuscript have no relevant financial relationships or otherwise to disclose.