Dynamic Model of Nonmedical Opioid Use Trajectories and Potential Policy InterventionsAmerican Journal of Drug and Alcohol Abuse
SponsorSupport was provided by NIH/NIDA grant 5R21DA031361-02.
- Opioid abuse -- Case studies,
- Opioid abuse -- Statistics,
- Opioids -- Therapeutic use,
- Opioids -- Pathophysiology,
- Opioid abuse -- Forecasting,
- Drug abuse -- Government policy,
- System theory
AbstractBackground—Nonmedical use of pharmaceutical opioid analgesics (POA) increased dramatically over the past two decades and remains a major health problem in the United States, contributing to over 16,000 accidental poisoning deaths in 2010. Objectives—Create a systems oriented theory/model to explain the historical behaviors of interest, including the various populations of nonmedical opioid users and accidental overdose mortality within those populations. Use the model to explore policy interventions including tamper resistant drug formulations and strategies for reducing diversion of opioid medicines. Methods—A system dynamics model was constructed to represent the population of people who initiate nonmedical POA usage. The model incorporates use trajectories including development of use disorders, transitions from reliance on informal sharing to paying for drugs, transition from oral administration to tampering to facilitate non-oral routes of administration, and transition to heroin use by some users, as well as movement into and out of the population through quitting and mortality. Empirical support was drawn from national surveys (NSDUH, TEDS, MTF, and ARCOS) and published studies. Results—Model was able to replicate the patterns seen in the historical data for each user population, and the associated overdose deaths. Policy analysis showed that both tamper resistant formulations and interventions to reduce informal sharing could significantly reduce nonmedical user populations and overdose deaths in the long term, but the modeled effect sizes require additional empirical support. Conclusion—Creating a theory/model that can explain system behaviors at a systems level scale is feasible and facilitates thorough evaluation of policy interventions.
Citation InformationWakeland, W., Nielsen, A., & Geissert, P. (2015). Dynamic model of nonmedical opioid use trajectories and potential policy interventions. The American Journal of Drug and Alcohol Abuse, 41(6), 508–18