Commercial and public payer opioid analgesic prescribing policies: a case study

Abstract

Abstract Background One strategy to address the high number of U.S. opioid-related deaths is to restrict high-risk or inappropriate opioid analgesic prescribing and dispensing. Federal and state laws and regulations have implemented restrictions but less is known about commercial and public payers’ policies aside from clinician anecdotal reports that these policies are increasing. To assess the number and types of policies with temporal trends, we examined commercial and public (Medicaid) payer policies in one state, Michigan, that has high opioid-related deaths and implemented opioid analgesic prescribing laws. Methods Policies for seven large commercial payers and the public payer for 2012–2018 were reviewed and categorized by actions. Joinpoint regression was used to summarize temporal trends on number of policies for all payers and subgroups. Results Across the 7 years, there were 529 action policies (75.57 (95% confidence intervals (CI) 35.93, 115.22) actions per year) with a range of 36 to 103 actions by payer. Limitations on number of days for initial prescriptions and prior authorizations were the most frequently implemented policy. The temporal trend showed a decline in new policies from 2012 to 2013 but a steady increase from 2014 to 2018 (average annual percent change or AAPC=29.6% (95% confidence intervals 13.2, 48.5%)). The public payer (n=47 policies) showed no increase in number of policies over time (AAPC=2.9% (95% CI -41.6, 61.6%). Conclusions The eight commercial and public payers implemented many new policies to restrict opioid analgesic prescribing with a steady increase in the number of such policies implemented from 2014 to 2018. This case study documented that at least in one state with high opioid-related deaths and multiple commercial payers, new and different policies were increasingly implemented creating barriers to patient care. The impact of these policies is understudied, complicating recommendation of best practices.