title: A comparison of an opioid abuse screening tool and prescription drug monitoring data in the emergency department.
abstract: OBJECTIVE
  This study aimed to: (a) determine the percentage of ED patients receiving prescriptions for opioid pain medications that meet the criteria for "high-risk for abuse potential" on the Screener and Opioid Assessment for Patients with Pain (SOAPP(®)-R), (b) determine the percentage of patients with high-risk behavior on the state prescription drug monitoring program (PDMP) database, (c) compare the SOAPP-R with data from the PDMP, and (d) determine psychometric properties of SOAPP-R for ED patients
  
  
  METHODS
  Convenience sample of ED patients who were being considered for discharge with a prescription for an opioid pain medication. Subjects completed SOAPP-R on an electronic tablet and PDMP data was obtained. Scores on SOAPP-R ≥ 18 were defined as "at-risk", and PDMP data showing both ≥ 4 opioid prescriptions and ≥ 4 providers in 12 months was considered the criterion standard for high-risk behavior.
  
  
  RESULTS
  82 patients (88.2%) provided consent. 32.9% (n=27) were determined to be "at-risk" (score ≥ 18) by SOAPP-R. 15.9% (n=13) subjects met PDMP criteria and 53.9% (n=7) of those had SOAPP-R scores ≥ 18 (sensitivity 54%, specificity 71%, positive predictive value 26%, negative predictive value 89%). The association of an at-risk SOAPP-R score and PDMP high-risk criteria was an adjusted odds ratio of 1.39 (95% confidence interval 0.73-3.68).
  
  
  CONCLUSIONS
  In our population, about one-third of patients being considered for discharge with an opioid prescription scored "at-risk" on SOAPP-R and 15.9% met the PDMP high-risk criteria. The high negative predictive value of SOAPP-R indicates it may be a useful screening tool for the ED patient population.
authors.affiliation: Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA, United States. Electronic address: sweiner@bwh.harvard.edu.
authors.forename: Scott G
authors.initials: SG
authors.lastname: Weiner
authors.affiliation: Tufts University School of Medicine, Boston, MA, United States. Electronic address: laura.horton@tufts.edu.
authors.forename: Laura C
authors.initials: LC
authors.lastname: Horton
authors.affiliation: Boston Medical Center and Boston University Department of Emergency Medicine Providence, RI Inflexxion, Inc., Newton, MA, United States. Electronic address: traci.c.green@gmail.com.
authors.forename: Traci C
authors.initials: TC
authors.lastname: Green
authors.affiliation: Inflexxion, Inc., Newton, MA, United States. Electronic address: sfbutler@inflexxion.com.
authors.forename: Stephen F
authors.initials: SF
authors.lastname: Butler
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000701:Analgesics, Opioid / Q000627:therapeutic use; D016208:Databases, Factual; D004363:Drug Utilization / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009293:Opioid-Related Disorders / Q000175:diagnosis* / Q000523:psychology; D010146:Pain / Q000188:drug therapy; D011594:Psychometrics; D018570:Risk Assessment; D012309:Risk-Taking; D055815:Young Adult
chemical_list: D000701:Analgesics, Opioid
keywords: Emergency department; Opioids; Prescription drug monitoring program; Screening