title: Declines in Opioid Prescribing After a Private Insurer Policy Change - Massachusetts, 2011-2015.
abstract: Overdose deaths involving opioid pain medications are epidemic in the United States, in part because of high opioid prescribing rates and associated abuse of these drugs (1). In 2014, nearly 2 million U.S. residents either abused or were dependent on prescription opioids (2). In Massachusetts, unintentional opioid-related overdose deaths, including deaths involving heroin, increased 45% from 2012 to 2013.* In 2014, the rate of these deaths reached 20.0 per 100,000, nearly 2.5 times higher than the U.S. rate overall (3,4). On July 1, 2012, Blue Cross Blue Shield of Massachusetts (BCBSMA), the largest insurer in the state with approximately 2.8 million members,†implemented a comprehensive opioid utilization program after learning that many of its members were receiving new prescriptions with a >30-day supply of opioids. The 2016 CDC Guideline for Prescribing Opioids for Chronic Pain recommends avoiding opioids as a first-line therapy for chronic pain and limiting quantities when initiating opioids for acute pain (5). CDC analyzed BCBSMA prescription claims data for the period 2011-2015 to assess the effect of the new utilization program on opioid prescribing rates. During the first 3 years after policy implementation, the average monthly prescribing rate for opioids decreased almost 15%, from 34 per 1,000 members to 29. The percentage of BCBSMA members per month with current opioid prescriptions also declined. The temporal association between implementation of the program and statistically significant declines in both prescribing rates and proportion of members using opioids suggests that the BCBSMA initiative played a role in reducing the use of prescription opioids among its members. Public and private insurers in the United States could benefit from developing their own best practices for prescription opioid utilization that ensure accessible pain care, while reducing the risk for dependence and abuse associated with these drugs.
authors.forename: Macarena C
authors.initials: MC
authors.lastname: García
authors.forename: Anton B
authors.initials: AB
authors.lastname: Dodek
authors.forename: Tom
authors.initials: T
authors.lastname: Kowalski
authors.forename: John
authors.initials: J
authors.lastname: Fallon
authors.forename: Scott H
authors.initials: SH
authors.lastname: Lee
authors.forename: Michael F
authors.initials: MF
authors.lastname: Iademarco
authors.forename: John
authors.initials: J
authors.lastname: Auerbach
authors.forename: Michele K
authors.initials: MK
authors.lastname: Bohm
mesh_terms: D000701:Analgesics, Opioid / Q000627:therapeutic use*; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D006801:Humans; D007348:Insurance, Health / Q000458:organization & administration*; D008404:Massachusetts; D016134:Organizational Policy; D017149:Private Sector / Q000458:organization & administration*; D015397:Program Evaluation
chemical_list: D000701:Analgesics, Opioid