The aim of this study was to investigate the prevalence of psychotropic medicines in drivers suspected of driving under the influence of medicinal and illicit drugs in The Netherlands and to compare the prevalence of selected impairing medicines with the use of these medicines in the general Dutch population. In total, 3038 blood samples of suspected impaired drivers in The Netherlands have been analyzed for the presence of medicinal and illicit drugs between January 2009 and December 2012. In 94% (2842/3038) of the cases medicinal and/or illicit drugs were detected. Medicinal drugs were found in 33% of the blood samples, with the highest prevalence for anxiolytics. In 86% of the cases illicit drug-positive results were obtained, with the highest prevalence for cannabis. At least in 56% of the blood samples poly-drug use was determined, including medicinal and/or illicit drugs. The highest prevalence of poly-medicine use was found for combinations including anxiolytic and hypnotic drugs. In general, the prevalence of driving impairing medicines in suspected impaired drivers is higher than the use of these medicines in the general Dutch population, due to a positive selection bias in the first population. Differences between both populations may be explained by the used methodological approach (e.g., classification criteria of analytical findings, sample selection bias) and abuse of certain medicinal drugs (e.g., diazepam). Negative effects of medicinal drugs on driving performance determine largely the prevalence in the population of suspected impaired drivers. The degree of impairment depends on different factors, including pharmacokinetic properties of the drug and pharmacodynamic aspects. More research is needed to study the prevalence of all prescribed driving impairing medicines and to investigate if providing additional information to medicinal drug users on driving impairing medicines would lower the prevalence of medicinal drug positive drivers.
Keywords: Blood concentrations; Driving under the influence; Medicinal drugs; Prescription data; Suspected impaired drivers.
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