OBJECTIVE: To measure geographic variation in opioid use in a large, commercially insured, outpatient population in the United States. DATA SOURCES: Outpatient prescription drug claims database of a national pharmaceutical benefit manager for 7,873,337 subjects with at least one prescription drug claim in 2000. STUDY DESIGN: We measured the period prevalence of claims for opioid analgesics and controlled-release oxycodone at the state level. We measured geographic variation using the weighted coefficient of variation and systematic component of variation. In county-level multivariable regression, we explored associations between potential explanatory variables and claims for opioid analgesics and controlled-release oxycodone. PRINCIPAL FINDINGS: A total of 567,778 (64.2 per 1,000 total claims) were for oral opioid analgesics. Claim rates by state ranged from <20 to >100 claims per 1,000 total claims. States with long-standing prescription monitoring programs had among the lowest rates. In the county-level data, presence of a statewide prescription monitoring program and proportions of the population aged 15-24 and 65 years and older were independently and negatively associated with claim rates for all opioid analgesics. Surgeons per 1,000, proportion of the population reporting illicit drug use, and proportion who were female were independently and positively associated with claim rates for all opioid analgesics. Only the proportion of the population aged 25-34 and number of surgeons per 1,000 were independently and positively associated with claim rates for oxycodone. CONCLUSIONS: Claim rates for opioid analgesics vary significantly by state. Presence of a statewide prescription monitoring program is associated with lower claim rates at the county level. Future research should use individual-level data to assess whether these findings reflect a reduction in abuse and diversion or suboptimal treatment of pain.
OBJECTIVE: To measure geographic variation in opioid use in a large, commercially insured, outpatient population in the United States. DATA SOURCES: Outpatient prescription drug claims database of a national pharmaceutical benefit manager for 7,873,337 subjects with at least one prescription drug claim in 2000. STUDY DESIGN: We measured the period prevalence of claims for opioid analgesics and controlled-release oxycodone at the state level. We measured geographic variation using the weighted coefficient of variation and systematic component of variation. In county-level multivariable regression, we explored associations between potential explanatory variables and claims for opioid analgesics and controlled-release oxycodone. PRINCIPAL FINDINGS: A total of 567,778 (64.2 per 1,000 total claims) were for oral opioid analgesics. Claim rates by state ranged from <20 to >100 claims per 1,000 total claims. States with long-standing prescription monitoring programs had among the lowest rates. In the county-level data, presence of a statewide prescription monitoring program and proportions of the population aged 15-24 and 65 years and older were independently and negatively associated with claim rates for all opioid analgesics. Surgeons per 1,000, proportion of the population reporting illicit drug use, and proportion who were female were independently and positively associated with claim rates for all opioid analgesics. Only the proportion of the population aged 25-34 and number of surgeons per 1,000 were independently and positively associated with claim rates for oxycodone. CONCLUSIONS: Claim rates for opioid analgesics vary significantly by state. Presence of a statewide prescription monitoring program is associated with lower claim rates at the county level. Future research should use individual-level data to assess whether these findings reflect a reduction in abuse and diversion or suboptimal treatment of pain.
Authors: Anita K Wagner; Stephen B Soumerai; Fang Zhang; Connie Mah; Linda Simoni-Wastila; Leon Cosler; Thomas Fanning; Peter Gallagher; Dennis Ross-Degnan Journal: Int J Qual Health Care Date: 2003-10 Impact factor: 2.038
Authors: Richard A Epstein; William V Bobo; Peter R Martin; James A Morrow; Wei Wang; Rameela Chandrasekhar; William O Cooper Journal: Ann Epidemiol Date: 2013-08 Impact factor: 3.797
Authors: Joanne E Brady; Hannah Wunsch; Charles DiMaggio; Barbara H Lang; James Giglio; Guohua Li Journal: Public Health Rep Date: 2014 Mar-Apr Impact factor: 2.792
Authors: Denise Boudreau; Michael Von Korff; Carolyn M Rutter; Kathleen Saunders; G Thomas Ray; Mark D Sullivan; Cynthia I Campbell; Joseph O Merrill; Michael J Silverberg; Caleb Banta-Green; Constance Weisner Journal: Pharmacoepidemiol Drug Saf Date: 2009-12 Impact factor: 2.890