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Florida’s Opioid Crackdown and Mortality From Drug Overdose, Motor Vehicle Crashes, and Suicide: A Bayesian Interrupted Time-Series Analysis
Author(s) -
Kenneth A. Feder,
Ramin Mojtabai,
Elizabeth A. Stuart,
Rashelle J. Musci,
Elizabeth J. Letourneau
Publication year - 2020
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwaa015
Subject(s) - medicine , drug overdose , interrupted time series analysis , opioid overdose , poison control , motor vehicle crash , interrupted time series , emergency medicine , injury prevention , opioid , medical emergency , psychiatry , (+) naloxone , statistics , receptor , mathematics , psychological intervention
In 2011, Florida established a prescription drug monitoring program and adopted new regulations for independent pain-management clinics. We examined the association of those reforms with drug overdose deaths and other injury fatalities. Florida’s postreform monthly mortality rates—for drug-involved deaths, motor vehicle crashes, and suicide by means other than poisoning—were compared with 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% credible interval: −21, −12), motor vehicle crash deaths were down 9% (95% credible interval: −14, −4), and suicide deaths were unchanged compared with what would be expected in the absence of reform. Florida’s opioid prescribing 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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