Teresa D. Schmidt

Modeling the Impact of Simulated Educational Interventions on the Use and Abuse of Pharmaceutical Opioids in the United States A Report on Initial Efforts

Three educational interventions were simulated in a system dynamics model of the medical use, trafficking, and nonmedical use of pharmaceutical opioids. The study relied on secondary data obtained in the literature for the period of 1995 to 2008 as well as expert panel recommendations regarding model parameters and structure. The behavior of the resulting systems-level model was tested for fit against reference behavior data. After the base model was tested, logic to represent three educational interventions was added and the impact of each intervention on simulated overdose deaths was evaluated over a 7-year evaluation period, 2008 to 2015. Principal findings were that a prescriber education intervention not only reduced total overdose deaths in the model but also reduced the total number of persons who receive opioid analgesic therapy, medical user education not only reduced overdose deaths among medical users but also resulted in increased deaths from nonmedical use, and a “popularity” intervention sharply reduced overdose deaths among nonmedical users while having no effect on medical use. System dynamics modeling shows promise for evaluating potential interventions to ameliorate the adverse outcomes associated with the complex system surrounding the use of opioid analgesics to treat pain.

Key Data Gaps Regarding the Public Health Issues Associated with Opioid Analgesics.

Most pharmaceutical opioids are used to treat pain, and they have been demonstrated to be effective medications for many. Their abuse and misuse pose significant public health concerns in the USA. Research has provided much insight into the prevalence, scope, and drivers of opioid abuse, but a holistic understanding is limited by a lack of available data regarding key aspects of this public health problem. Twelve data gaps were revealed during the creation of a systems-level computer model of medical use, diversion, nonmedical use, and the adverse outcomes associated with opioid analgesics in the USA. Data specific to these gaps would enhance the validity and real-world applications of systems-level models of this public health problem and would increase understanding of the complex system in which use and abuse occur. This paper provides an overview of these gaps, argues for the importance of closing them, and provides specific recommendations for future data collection efforts.