270321 Detecting Possible Opioid Abuse or Dependence via Mathematical Modeling

Tuesday, October 30, 2012

Jean Carter, PhD , Department of Pharmacy Practice, University of Montana, Missoula, MT
Nicholas Heck, MA , Department of Psychology, The University of Montana, Missoula, MT
Nicholas Livingston, BS , Department of Psychology, University of Montana, Missoula, MT
Annesa Flentje, Ph.D. , Department of Psychiatry, The University of California, San Francisco, San Francisco, CA
Jill Van Den Bos, MA , Consultant, Milliman, Inc., Denver, CO
Robert Valuck, PhD, RPh , Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Anschutz Medical Campus, Aurora, CO
Daniel Perlman , Data Analyst, Milliman, Inc., Denver, CO
Jorge Torres , Data Analyst, Milliman, Inc., Denver, CO
Bryan Cochran, PhD , Department of Psychology, University of Montana, Missoula, MT
Background: The misuse of prescription drugs, opioids in particular, is a significant public health problem. In this study we attempt to identify “stealth” opioid misusers, who are individuals that have characteristics of opioid misusers, but have not received an opioid misuse diagnosis, via a combination of mental health and other predictor variables. Methods: The dataset was obtained from the Thompson Reuters MarketScan Commercial Claims and Encounters database, and contains 2,841,793 individuals who received an opioid prescription between 2000 and 2008, of which 2,913 also had an opioid misuse diagnosis within the two-year period following the initial opioid prescription. Twenty-nine logistic regression models were calculated to test seven expanded definitions (and combinations thereof) of diagnosed and undiagnosed opioid misusers. The seven definitions include such indicators as filling opioid prescriptions at multiple pharmacies within 24 hours, significant dose escalation, or other unspecified drug dependence diagnosis.

Results: In the context of key variables that predict opioid misuse (e.g., demographic characteristics, other mental health and substance misuse diagnoses, and healthcare utilization), two of the stealth misuse definitions were approximately 90% concordant in identifying actual misusers. The first definition, which operationalized stealth misuse as being prescribed a long acting opioid and two or more short acting opioids, identified 90,740 individuals as actual or stealth misusers. The second definition included all stealth misuse indicators and identified 92,889 actual or stealth misusers.

Discussion: Expanded definitions of stealth misuse may help identify those at increased risk for opioid misuse. Implications exist for opioid misuse intervention and prevention efforts.

Learning Areas:
Public health or related research
Social and behavioral sciences

Learning Objectives:
Describe the variables that may identify individuals at risk for developing opioid abuse or dependence. Explain how mental health variables may contribute to the identification of those at risk for opioid misuse.

Keywords: Drug Addiction, Mental Disorders

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I was the principal investigator on a grant to identify risk for opioid abuse and dependence, and I teach graduate and undergraduate courses related to mental health, drug abuse and dependence.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.