title: Factors predicting development of opioid use disorders among individuals who receive an initial opioid prescription: mathematical modeling using a database of commercially-insured individuals.
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.
authors.affiliation: Department of Psychology, Skaggs Building Room 143, The University of Montana, Missoula, MT 59812, United States. Electronic address: bryan.cochran@umontana.edu.
authors.forename: Bryan N
authors.initials: BN
authors.lastname: Cochran
authors.affiliation: University of California, San Francisco, San Francisco General Hospital, 1001 Potrero Avenue, Suite 7 M, San Francisco, CA 94110, United States.
authors.forename: Annesa
authors.initials: A
authors.lastname: Flentje
authors.affiliation: Department of Psychology, Skaggs Building Room 143, The University of Montana, Missoula, MT 59812, United States.
authors.forename: Nicholas C
authors.initials: NC
authors.lastname: Heck
authors.affiliation: Milliman, Inc., 1400 Wewatta St, Suite 300, Denver, CO 80202, United States.
authors.forename: Jill
authors.initials: J
authors.lastname: Van Den Bos
authors.affiliation: Milliman, Inc., 1400 Wewatta St, Suite 300, Denver, CO 80202, United States.
authors.forename: Dan
authors.initials: D
authors.lastname: Perlman
authors.affiliation: Milliman, Inc., 1400 Wewatta St, Suite 300, Denver, CO 80202, United States.
authors.forename: Jorge
authors.initials: J
authors.lastname: Torres
authors.affiliation: University of Colorado, Skaggs School of Pharmacy and Pharmaceutical Sciences, Mail Stop C238, 12850 E. Montview Blvd. V20-1201, Aurora, CO 80045, United States.
authors.forename: Robert
authors.initials: R
authors.lastname: Valuck
authors.affiliation: Department of Pharmacy Practice, 32 Campus Drive, The University of Montana, Missoula, MT 59812, United States.
authors.forename: Jean
authors.initials: J
authors.lastname: Carter
mesh_terms: D000328:Adult; D016208:Databases, Factual; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data; D006304:Health Status; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000150:complications / Q000523:psychology; D008875:Middle Aged; D008962:Models, Theoretical; D009293:Opioid-Related Disorders / Q000150:complications / Q000523:psychology*; D055553:Prescription Drugs; D012307:Risk Factors
chemical_list: D055553:Prescription Drugs
keywords: Health claims database; Opioid dependence; Opioid use disorder; Prescription drug misuse