@article{ref1, title="Florida's opioid crackdown and drug, motor vehicle crash, and suicide mortality: a Bayesian interrupted time-series analysis", journal="American journal of epidemiology", year="2020", author="Feder, Kenneth A. and Mojtabai, Ramin and Stuart, Elizabeth A. and Musci, Rashelle and Letourneau, Elizabeth J.", volume="ePub", number="ePub", pages="ePub-ePub", abstract="In 2011, Florida established a Prescription Drug Monitoring Program and adopted new regulations for independent pain-management clinics. This paper examines the association of those reforms with drug overdose deaths and other injury fatalities. Florida's post-reform monthly mortality rates - for drug-involved deaths, motor vehicle crashes, and suicides by means other than poisoning - were compared to a counterfactual estimate of what those rates would have been absent reform. The counterfactual was estimated using a Bayesian structural time-series model based on mortality trends in similar states. By December 2013, drug overdose deaths were down -17% (95% CI, -21% to -12%), motor vehicle crash deaths were down -9% (-14%, to -4%), and suicide deaths were unchanged compared to what would be expected in the absence of reform. Florida's opioid psrescribing reform substantially reduced drug overdose deaths. Reforms may also have reduced motor vehicle crash deaths but were not associated with a change in suicides; more research is needed to understand these patterns. Bayesian structural time-series modeling is a promising new approach to interrupted time-series studies.

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Language: en

", language="en", issn="0002-9262", doi="10.1093/aje/kwaa015", url="http://dx.doi.org/10.1093/aje/kwaa015" }