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The Influence of State Restrictions on Opioid Prescribing: 2006-2018
Leon E Cosler1, Luis Midence, Jacob J Hayes
1Author Affiliations: Department of Pharmacy Practice, Binghamton University School of Pharmacy and Pharmaceutical Sciences, Johnson City, New York (Dr Cosler, Ms Midence, and Drs Hayes, Gondeck, and Moy); Department of Mathematics and Statistics, Harpur College, Binghamton University, Vestal, New York (Dr Mei-Hsiu); and Albany Medical Health System, Albany, New York (Hogan).
State opioid restrictions significantly decrease opioid prescribing rates over time. While early impacts may not be statistically significant, long-term analysis shows a reduction in opioid prescriptions following policy implementation.
Area of Science:
- Public Health
- Health Policy Evaluation
- Epidemiology
Background:
- Opioid prescribing rates have been a significant public health concern.
- Understanding the impact of policy interventions on prescribing patterns is crucial.
Purpose of the Study:
- To evaluate the longitudinal effect of state-level opioid restrictions on prescribing patterns.
- To analyze prescribing trends at state and regional levels.
Main Methods:
- Utilized Poisson regression analysis on opioid prescribing data from 2006-2018.
- Incorporated state population data and information on opioid prescribing restrictions.
- Modeled estimated opioid counts for subsequent fiscal years.
Main Results:
- Per capita opioid prescribing peaked in 2012, reaching 86.2 per 100 population.
- Statewide opioid prescribing restrictions demonstrated a statistically significant decrease in opioid prescriptions.
- For every 100 prescriptions without restrictions, approximately 98 were expected annually with restrictions.
Conclusions:
- Opioid prescribing restrictions are effective in reducing overall opioid prescribing.
- Statistically significant changes in prescribing rates may take time to become apparent after restriction implementation.
- Findings contrast with some shorter-term studies, highlighting the importance of longitudinal data.
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