Predicting Opioid Abuse and Dependence
SOURCE: Ciesielski T, Iyengar R, Bothra A, et al. A tool to assess risk of de novo opioid abuse or dependence. Am J Med 2016;129:699-705.
In an era in which opioid overdose has outstripped auto accidents as a cause of mortality in adults ≤ 45 years of age in many states, it is critical to learn how to better identify patients at risk of opioid addiction, abuse, and dependence. There already are several screening tools for opioid misuse screening available to clinicians such as the Opioid Risk Tool and the Screener and Opioid Assessor for Patients in Pain; however, patients who are willing to be untruthful and hide their risk factors render such tools meaningless.
Ciesielski et al retrospectively studied a large sample from a health insurance database (n = 649,851), from which the authors identified 2,067 cases of opioid abuse or dependence. Predictors for abuse or dependence include younger age, chronic opioid use, psychiatric history, abuse of nonopioid substances, alcohol abuse, smoking, use of high morphine doses, receiving prescriptions from more than one source or pharmacy, male gender, and South or Midwest residence.
Most of the risk factors for abuse/dependence identified through this database have been identified and used by earlier established risk screeners. Because this was a retrospective analysis, whether utilizing a risk stratification tool comprised of all 12 risk factors noted in this population would improve risk prediction remains to be determined.
It is critical to learn how to better identify patients at risk of opioid addiction, abuse, and dependence.
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