title: Prescription drug monitoring and dispensing of prescription opioids.
abstract: OBJECTIVE
  In the United States, per-capita opioid dispensing has increased concurrently with analgesic-related mortality and morbidity since the 1990s. To deter diversion and abuse of controlled substances, most states have implemented electronic prescription drug monitoring programs (PDMPs). We evaluated the impact of state PDMPs on opioid dispensing.
  
  
  METHODS
  We acquired data on opioids dispensed in a given quarter of the year for each state and the District of Columbia from 1999 to 2008 from the Automation of Reports and Consolidated Orders System and converted them to morphine milligram equivalents (MMEs). We used multivariable linear regression modeling with generalized estimating equations to assess the effect of state PDMPs on per-capita dispensing of MMEs.
  
  
  RESULTS
  The annual MMEs dispensed per capita increased progressively until 2007 before stabilizing. Adjusting for temporal trends and demographic characteristics, implementation of state PDMPs was associated with a 3% decrease in MMEs dispensed per capita (p=0.68). The impact of PDMPs on MMEs dispensed per capita varied markedly by state, from a 66% decrease in Colorado to a 61% increase in Connecticut.
  
  
  CONCLUSIONS
  Implementation of state PDMPs up to 2008 did not show a significant impact on per-capita opioids dispensed. To control the diversion and abuse of prescription drugs, state PDMPs may need to improve their usability, implement requirements for committee oversight of the PDMP, and increase data sharing with neighboring states.
authors.affiliation: Columbia University, Departments of Anesthesiology and Epidemiology, Center for Injury Epidemiology and Prevention, New York, NY.
authors.forename: Joanne E
authors.initials: JE
authors.lastname: Brady
authors.affiliation: Columbia University, Departments of Anesthesiology and Epidemiology, New York, NY.
authors.forename: Hannah
authors.initials: H
authors.lastname: Wunsch
authors.affiliation: Columbia University, Departments of Anesthesiology and Epidemiology, Center for Injury Epidemiology and Prevention, New York, NY.
authors.forename: Charles
authors.initials: C
authors.lastname: DiMaggio
authors.affiliation: Columbia University, Department of Anesthesiology, New York, NY.
authors.forename: Barbara H
authors.initials: BH
authors.lastname: Lang
authors.affiliation: Columbia University, Department of Emergency Medicine, New York, NY.
authors.forename: James
authors.initials: J
authors.lastname: Giglio
authors.affiliation: Columbia University, Departments of Anesthesiology and Epidemiology, Center for Injury Epidemiology and Prevention, New York, NY.
authors.forename: Guohua
authors.initials: G
authors.lastname: Li
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000701:Analgesics, Opioid / Q000009:adverse effects / Q000627:therapeutic use*; D016208:Databases, Factual; D016903:Drug Monitoring / Q000379:methods / Q000706:statistics & numerical data; D062787:Drug Overdose / Q000453:epidemiology / Q000401:mortality; D004335:Drug and Narcotic Control / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D064226:Prescription Drug Diversion / Q000706:statistics & numerical data*; D063487:Prescription Drug Misuse / Q000401:mortality / Q000706:statistics & numerical data*; D055553:Prescription Drugs / Q000009:adverse effects / Q000627:therapeutic use; D017678:Sex Distribution; D019966:Substance-Related Disorders / Q000453:epidemiology / Q000209:etiology* / Q000401:mortality; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000701:Analgesics, Opioid; D055553:Prescription Drugs