Factors predicting development of opioid use disorders among individuals who receive an initial opioid prescription: Mathematical modeling using a database of commercially-insured individuals

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By Annesa Flentje, Bryan N. Cochran, Jean Cartere, Nicholas C. Heck, Robert Valuck, Daniel Perlman, Jill Van Den Bos, Jorge Torres | 29 July 2014

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.

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).

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

This article was published by ScienceDirect (subscription required).

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