Monetary conversion factors for economic evaluations of substance use disorders.
Academic Article
Overview
abstract
AIMS: Estimating the economic consequences of substance use disorders (SUDs) is important for evaluating existing programs and new interventions. Policy makers in particular must weigh program effectiveness with scalability and sustainability considerations in deciding which programs to fund with limited resources. This study provides a comprehensive list of monetary conversion factors for a broad range of consequences, services, and outcomes, which can be used in economic evaluations of SUD interventions (primarily in the United States), including common co-occurring conditions such as HCV and HIV. METHODS: Economic measures were selected from standardized clinical assessment instruments that are used in randomized clinical trials and other research studies (e.g., quasi-experimental community-based projects) to evaluate the impact of SUD interventions. National datasets were also reviewed for additional SUD-related consequences, services, and outcomes. Monetary conversion factors were identified through a comprehensive literature review of published articles as well as targeted searches of other sources such as government reports. RESULTS: Eight service/consequence/outcome domains were identified containing more than sixty monetizable measures of medical and behavioral health services, laboratory services, SUD treatment, social services, productivity outcomes, disability outcomes, criminal activity and criminal justice services, and infectious diseases consequences. Unit-specific monetary conversion factors are reported, along with upper and lower bound estimates, whenever possible. CONCLUSIONS: Having an updated and standardized source of monetary conversion factors will facilitate and improve future economic evaluations of interventions targeting SUDs and other risky behaviors. This exercise should be repeated periodically as new sources of data become available to maintain the timeliness, comprehensiveness, and quality of these estimates.
