Modeling Mitigation Strategies to Reduce Opioid-Related Morbidity and Mortality in U.S.

A decision analytic dynamic Markov model on the US population aged 12 years or older was used to project the number of fatal overdoses caused by any opioid between 2020 – 2029 and project the number of deaths that can be averted by prescribing restrictions, naloxone distribution, and expansion of MAT interventions. Based on data taken from 2010-2018 National Survey on Drug Use and Health, Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey, the US Census, and the National Epidemiologic Survey on Alcohol and Related Conditions- III, the status quo, the model projects 484,429 fatal opioid overdoses to occur between 2020 and 2029, with 155,628 attributed to prescription opioid use (both medical and non-medical use), 199,751 attributed to heroin and previous prescription opioid use, and 129,050 attributed to heroin without previous prescription opioid use. Implementing interventions such as reducing opioid prescribing, enhanced naloxone distribution, and expanding MAT can avert 37% or 179,151 of the projected fatal opioid overdoses, with each of the preceding interventions averting 0.3%, 15.4%, and 25.3% of these projected fatal opioid overdoses, respectively. This model also projected that the combined interventions would decrease the prevalence of people with opioid use disorder by 27.5%, reducing from 2.47 million with opioid use disorder in 2019 to 1.79 million with opioid use disorder in 2029.

Ballreich J, Mansour O, Hu E, et al. Modeling Mitigation Strategies to Reduce Opioid-Related Morbidity and Mortality in the US. JAMA Netw Open. 2020;3(11):e2023677. doi:10.1001/jamanetworkopen.2020.23677

Citation
Ballreich J, Mansour O, Hu E, et al. Modeling Mitigation Strategies to Reduce Opioid-Related Morbidity and Mortality in the US. JAMA Netw Open. 2020;3(11):e2023677. doi:10.1001/jamanetworkopen.2020.23677
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