Diffusion Mechanisms of Opioid Prescription Limit Policies in State Governments

• In Event: Coalitional Politics in Policy Reform Processes

Abstract

Drug overdose is the primary cause of injury deaths in the United States. The widespread availability of prescription opioids and illicit drugs is mainly responsible for the opioid epidemic. Opioids are prescription drugs prescribed for acute pain, such as post-surgery pain, and chronic pain, such as back pain. The Centers for Disease Control and Prevention (CDC) reports that acute pain patients who are having first-time opioid medication are susceptible to getting addicted to it, and chronic pain patients tend to abuse opioids the most. Thus, to curb the supply of prescription opioids, the state governments across the nation have adopted and implemented Opioid Prescription Limit (OPL) policies. Notable differences have been observed in the order of adoption of the OPL policies across states. Massachusetts was the first state to adopt the OPL policy in March 2016, while six other states also enacted the OPL policy that same year. In the subsequent year, fifteen more states adopted the OPL policy. As of March 2025, forty states, comprising all regions of the United States, have adopted the OPL policies. On the other hand, significant similarities have been observed in states that adopt OPL policies with similar provisions, such as the initial maximum days of opioid supply, daily dosage limits, target patients, restrictions based on insurance type and age, and policymaking authorities. Similarities also exist in neighboring or regional states adopting similar provisions in subsequent years. These similarities and dissimilarities in the adoption of OPL policies suggest the occurrence of policy diffusion among the state governments. This study aims to analyze OPL policy diffusion mechanisms across state governments, using the theory of diffusion of innovation, which encompasses diffusion mechanisms such as imitation, competition, learning, and coercion. First, this study will conduct a conceptual content analysis based on publicly available data to identify the similarities and differences in the OPL policies adopted by state governments. Second, it will perform a cluster analysis based on the organized data from the conceptual content analysis to identify diffusion mechanisms. Third, the study will conduct a Dyadic Event History Analysis (DEHA) based on the publicly available data to find whether the factors such as proximity of the political jurisdictions, perceived effectiveness of the policy, the sheer will of the political entities, benefits outweighing the cost of execution of the policy, the severity of the problem, the influence of the media and interest group, and demographical characteristics of the jurisdictions are associated with the diffusion mechanisms of OPL policies.

 

Author

• Md Ashiqur Rab, Clemson University
  Presenting Author