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Using poison center exposure calls to predict prescription opioid abuse and misuse-related emergency department visits

Authors

  • Jonathan M. Davis,

    Corresponding author
    1. Rocky Mountain Poison and Drug Center, Denver Health and Hospital Authority, Denver, CO, USA
    • Correspondence to: J. M. Davis, Rocky Mountain Poison and Drug Center, Denver Health and Hospital Authority, 777 Bannock St., MC 0180, Denver, CO 80204, USA. E-mail: jonathan.davis@ucdenver.edu

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  • Stevan G. Severtson,

    1. Rocky Mountain Poison and Drug Center, Denver Health and Hospital Authority, Denver, CO, USA
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  • Becki Bucher-Bartelson,

    1. Rocky Mountain Poison and Drug Center, Denver Health and Hospital Authority, Denver, CO, USA
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  • Richard C. Dart

    1. Rocky Mountain Poison and Drug Center, Denver Health and Hospital Authority, Denver, CO, USA
    2. Department of Emergency Medicine, University of Colorado Denver, CO, USA
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ABSTRACT

Background

Prescription drug abuse is a critical problem in the USA and has been linked to more deaths than automobile accidents. Despite this growing epidemic, the USA lacks a timely early warning system. Poison centers (PCs) have the potential to act as sentinel reporting entities for prescription drug abuse and misuse due to near-real-time data reporting and abundant coverage in the USA.

Methods

Data from the Researched Abuse, Diversion and Addiction-Related Surveillance (RADARS®) System PC program were compared with data from the Drug Abuse Warning Network (DAWN) from 2004 through 2010. Population rates of PC call mentions regarding abuse and misuse of prescription opioids were compared with population rates of emergency department visit mentions of the same using linear regression. Products included in the analysis were the following: buprenorphine, fentanyl, hydrocodone, hydromorphone, methadone, morphine, and oxycodone.

Results

The strength of association between RADARS System PC data and DAWN emergency department visits regarding all opioids in aggregate was strong (R2 = 0.81, p < 0.001). The correlations between the two programs at the drug class level also were strong for buprenorphine, hydrocodone, hydromorphone, methadone, and oxycodone (all R2 > 0.70, all p < 0.01), significant for fentanyl (p = 0.05), and moderate for morphine (p = 0.09).

Conclusions

Data on prescription opioid drug abuse from the RADARS System PC program correlates well with emergency room data from DAWN. Due to timeliness of data, geographic coverage and strong associations with other warning systems, PC data can be used for sentinel reporting on prescription drug abuse and misuse in the USA. Copyright © 2013 John Wiley & Sons, Ltd.

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