title: Age and sex trends in long-term opioid use in two large American health systems between 2000 and 2005.
abstract: OBJECTIVE
  To estimate recent age- and sex-specific changes in long-term opioid prescription among patients with chronic pain in two large American Health Systems.
  
  
  METHODS
  Analysis of administrative pharmacy data to calculate changes in prevalence of long-term opioid prescription (90 days or more during a calendar year) from 2000 to 2005, within groups based on sex and age (18-44, 45-64, and 65 years and older). Separate analyses were conducted for patients with and without a diagnosis of a mood disorder or anxiety disorder. Changes in mean dose between 2000 and 2005 were estimated, as were changes in the rate of prescription for different opioid types (short-acting, long-acting, and non-Schedule 2).
  
  
  METHODS
  Enrollees in HealthCore (N = 2,716,163 in 2000) and Arkansas Medicaid (N = 115,914 in 2000).
  
  
  RESULTS
  Within each of the age and sex groups, less than 10% of patients with a chronic pain diagnosis in HealthCore, and less than 33% in Arkansas Medicaid, received long-term opioid prescriptions. All age, sex, and anxiety/depression groups showed similar and statistically significant increases in long-term opioid prescription between 2000 and 2005 (35-50% increase). Per-patient daily doses did not increase.
  
  
  CONCLUSIONS
  No one group showed especially large increases in long-term opioid prescriptions between 2000 and 2005. These results argue against a recent epidemic of opioid prescribing. These trends may result from increased attention to pain in clinical settings, policy or economic changes, or provider and patient openness to opioid therapy. The risks and benefits to patients of these changes are not yet established.
authors.affiliation: University of Washington, Psychiatry and Behavioral Sciences, Seattle, Washington 98195, USA. sthielke@u.washington.edu
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Thielke
authors.forename: Linda
authors.initials: L
authors.lastname: Simoni-Wastila
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Edlund
authors.forename: Andrea
authors.initials: A
authors.lastname: DeVries
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Martin
authors.forename: Jennifer B
authors.initials: JB
authors.lastname: Braden
authors.forename: Ming-Yu
authors.initials: MY
authors.lastname: Fan
authors.forename: Mark D
authors.initials: MD
authors.lastname: Sullivan
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000701:Analgesics, Opioid / Q000008:administration & dosage / Q000191:economics / Q000627:therapeutic use*; D001008:Anxiety Disorders / Q000150:complications / Q000453:epidemiology; D001131:Arkansas; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004363:Drug Utilization / Q000639:trends; D005260:Female; D006801:Humans; D007345:Insurance Claim Review; D007348:Insurance, Health / Q000191:economics / Q000706:statistics & numerical data; D008134:Long-Term Care; D008297:Male; D008484:Medicaid / Q000191:economics / Q000706:statistics & numerical data; D008875:Middle Aged; D019964:Mood Disorders / Q000150:complications / Q000453:epidemiology; D012737:Sex Factors; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000701:Analgesics, Opioid