title: Healthcare costs and nonadherence among chronic opioid users.
abstract: OBJECTIVE
  To assess the health economic burden of chronic opioid users and to determine whether opioid regimen nonadherence contributes to increased healthcare costs.
  
  
  METHODS
  Retrospective claims-based analysis of patients with long-term prescription opioid use (>120 days of supply over 6 months).
  
  
  METHODS
  Twelve-month healthcare utilization and costs were compared for chronic opioid users (n = 49,425) and, among chronic opioid users with urine drug-monitoring results (n = 2100), between adherent patients versus patients with evidence of nonadherence to their opioid regimen. Likely nonadherence was based on urine test results indicating absence of the prescribed drug, higher or lower than expected drug levels based on a proprietary algorithm, or presence of unprescribed or illegal drugs. The influence of nonadherence on total healthcare costs was assessed using multivariate models.
  
  
  RESULTS
  Prevalence of chronic opioid use was 1.3%. Chronic opioid users had significantly greater healthcare utilization and costs than matched nonusers ($23,049 vs $4975; P <.001). Adherent patients (n = 442) had lower total healthcare costs than likely nonadherent patients (n = 1658; $23,160 vs $26,433; P = .036). After adjustment for demographics, likely nonadherence was significantly associated with elevated total healthcare costs (cost ratio [CR] 1.136; 95% confidence interval [CI] 1.00, 1.29; P = .048). When adjusting for other types of nonadherence, the presence of higher than expected levels of the prescribed opioid was associated with significantly elevated costs (CR 1.121; 95% CI 1.01, 1.25; P = .039).
  
  
  CONCLUSIONS
  Chronic opioid users represent a substantial cost burden relative to similar patients without evidence of chronic pain. Among likely nonadherent chronic opioid users, those with evidence of opioid overuse had significantly elevated healthcare costs.
authors.affiliation: Ameritox, Ltd, Baltimore, MD 21202, USA. harry.leider@ameritox.com
authors.forename: Harry L
authors.initials: HL
authors.lastname: Leider
authors.forename: Jatinder
authors.initials: J
authors.lastname: Dhaliwal
authors.forename: Elizabeth J
authors.initials: EJ
authors.lastname: Davis
authors.forename: Mahesh
authors.initials: M
authors.lastname: Kulakodlu
authors.forename: Ami R
authors.initials: AR
authors.lastname: Buikema
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D000701:Analgesics, Opioid / Q000652:urine*; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006296:Health Services / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007345:Insurance Claim Review; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009293:Opioid-Related Disorders / Q000188:drug therapy / Q000191:economics*; D015995:Prevalence; D012189:Retrospective Studies; D012307:Risk Factors; D013997:Time Factors; D014481:United States; D055815:Young Adult; D016903:Drug Monitoring
chemical_list: D000701:Analgesics, Opioid