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Journal Article

Citation

Wakeland W, Nielsen A, Geissert P. Am. J. Drug Alcohol Abuse 2015; 41(6): 508-518.

Affiliation

Systems Science Program, Portland State University , Portland, Oregon , USA.

Copyright

(Copyright © 2015, Informa - Taylor and Francis Group)

DOI

10.3109/00952990.2015.1043435

PMID

25982491

Abstract

BACKGROUND: 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: To 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. To 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: The 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.


Language: en

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