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• W3071396780 abstract "The U.S. has seen an unprecedented rise in opioid-related morbidity and mortality, and states have passed numerous laws in response. Researchers have not comprehensively established the effectiveness of pain management clinic regulations to reduce opioid prescribing using national data.We combine a policy dataset from the Prescription Drug Abuse Policy System with the Centers for Disease Control and Prevention county-level opioid prescribing data, as well as with numerous government datasets for county- and state- level covariates. We predict retail opioid prescriptions dispensed per 100 people using county fixed-effects models with a state-level cluster correction. Our key predictors of interest are the presence of any state-level pain management clinic law and eight specific subcomponents of the law.Pain management clinic laws demonstrate consistent, negative effects on prescribing rates. Controlling for county characteristics, state spending, and the broader policy context, states with pain management clinic laws had, on average, 5.78 fewer opioid prescriptions per 100 people than states without such laws (p < .05). Five specific subcomponents demonstrate efficacy in reducing prescribing rates: certification requirements (B = -6.02, p < .05), medical directors (B = -6.14, p < .05), dispenser and dispensing amount restrictions (B = -8.60, p < .01; B = -15.51, p < .001), and explicit penalties for noncompliance (B = -6.02, p < .05). Three subcomponents had no effect: prescription quantity restrictions and requirements to register with or review prescription drug monitoring programs.Implementation of pain management clinic laws reduced county-level opioid prescribing. States should review specific components to determine which forms of law are most efficacious." @default.
• W3071396780 created "2020-08-24" @default.
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• W3071396780 date "2020-11-01" @default.
• W3071396780 modified "2023-10-17" @default.
• W3071396780 title "State pain management clinic policies and county opioid prescribing: A fixed effects analysis" @default.
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• W3071396780 doi "https://doi.org/10.1016/j.drugalcdep.2020.108239" @default.
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