Factors Predicting Development of Opioid use Disorders among Individuals Who Receive an Initial Opioid Prescription: Mathematical Modeling Using a Database of Commercially-insured Individuals

Authors

Bryan N. Cochran, University of Montana - Missoula
Annesa Flentje, University of California - San Francisco
Nicholas C. Heck, Marquette UniversityFollow
Jill van den Bos, Milliman, Inc.
Dan Perlman, Milliman, Inc.
Jorge Torres, Milliman, Inc.
Robert Valuck, University of Colorado at Denver
Jean Carter, University of Montana - Missoula

Document Type

Article

Language

eng

Format of Original

7 p.

Publication Date

5-1-2014

Publisher

Elsevier

Source Publication

Drug and Alcohol Dependence

Source ISSN

0376-8716

Original Item ID

doi: 10.1016/j.drugalcdep.2014.02.701

Abstract

Background

Prescription drug abuse in the United States and elsewhere in the world is increasing at an alarming rate with non-medical opioid use, in particular, increasing to epidemic proportions over the past two decades. It is imperative to identify individuals most likely to develop opioid abuse or dependence to inform large-scale, targeted prevention efforts.

Methods

The present investigation utilized a large commercial insurance claims database to identify demographic, mental health, physical health, and healthcare service utilization variables that differentiate persons who receive an opioid abuse or dependence diagnosis within two years of filling an opioid prescription (OUDs) from those who do not receive such a diagnosis within the same time frame (non-OUDs).

Results

When compared to non-OUDs, OUDs were more likely to: (1) be male (59.9% vs. 44.2% for non-OUDs) and younger (M = 37.9 vs. 47.7); (2) have a prescription history of more opioids (1.7 vs. 1.2), and more days supply of opioids (M = 272.5, vs. M = 33.2; (3) have prescriptions filled at more pharmacies (M = 3.3 per year vs. M = 1.3); (4) have greater rates of psychiatric disorders; (5) utilize more medical and psychiatric services; and (6) be prescribed more concomitant medications. A predictive model incorporating these findings was 79.5% concordant with actual OUDs in the data set.

Conclusions

Understanding correlates of OUD development can help to predict risk and inform prevention efforts.

Comments

Accepted version. Drug and Alcohol Dependence, Vol. 138 (May 1, 2014): 202-208. DOI. © 2014 Elsevier. Used with permission.

Nicholas Heck was affiliated with the University of Montana - Missoula at the time of publication.

Recommended Citation

Cochran, Bryan N.; Flentje, Annesa; Heck, Nicholas C.; van den Bos, Jill; Perlman, Dan; Torres, Jorge; Valuck, Robert; and Carter, Jean, "Factors Predicting Development of Opioid use Disorders among Individuals Who Receive an Initial Opioid Prescription: Mathematical Modeling Using a Database of Commercially-insured Individuals" (2014). Psychology Faculty Research and Publications. 145.
https://epublications.marquette.edu/psych_fac/145