High-Risk Prescribing to Medicaid Enrollees Receiving Opioid Analgesics

Individual- and County-Level Factors

Published in: Substance Use & Misuse [Epub January 2018]. doi: 10.1080/10826084.2017.1416407

Posted on RAND.org on January 16, 2018

by Sara Elizabeth Heins, Mark J. Sorbero, Christopher M. Jones, Andrew W. Dick, Bradley D. Stein

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Background

Prescription opioid overdoses have increased dramatically in recent years, with the highest rates among Medicaid enrollees. High-risk prescribing includes practices associated with overdoses and a range of additional opioid-related problems. Objectives: To identify individual- and county-level factors associated with high-risk prescribing among Medicaid enrollees receiving opioids.

Methods

In a four-states, cross-sectional claims data study, Medicaid enrollees 18–64 years old with a new opioid analgesic treatment episode 2007–2009 were identified. Multivariate regression analyses were conducted to identify factors associated with high-risk prescribing, defined as high-dose opioid prescribing (morphine equivalent daily dose ≥ 100 mg for > 6 days), opioid overlap, opioid-benzodiazepine overlap.

Results

High-risk prescribing occurred in 39.4% of episodes. Older age, rural county of residence, white race, and major depression diagnosis were associated with higher rates of all types of high-risk prescribing. Individuals with prior opioid, alcohol, and hypnotic/sedative use disorder diagnoses had lower odds of high-dose opioid prescribing but higher odds of opioid overlap and opioid-benzodiazepine overlap than individuals without such disorders. High-dose opioid prescribing in Massachusetts was less common than in California, Illinois, and New York, whereas the rate of benzodiazepine overlap in Massachusetts was more common than in other states.

Conclusions/Importance

High-risk prescribing was common and associated with several important demographic, clinical, and community factors. Findings can be used to inform targeted interventions designed to reduce such prescribing, and given state variation observed, further research is needed to better understand the effects of state policies on high-risk prescribing.

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