Estimating the impact of wide scale uptake of screening and medications for opioid use disorder in US prisons and jails
•Medications for opioid use disorder in prisons/jails reduced overdose post-release.•Our model predicted that treatment alone would have saved 1840 lives.•We predicted that treatment and post-release retention would have saved 4400 lives. Medications for opioid use disorder (OUD) are the most effect...
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| Vydáno v: | Drug and alcohol dependence Ročník 208; s. 107858 |
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| Hlavní autoři: | , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Ireland
Elsevier B.V
01.03.2020
Elsevier Science Ltd |
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| ISSN: | 0376-8716, 1879-0046, 1879-0046 |
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| Abstract | •Medications for opioid use disorder in prisons/jails reduced overdose post-release.•Our model predicted that treatment alone would have saved 1840 lives.•We predicted that treatment and post-release retention would have saved 4400 lives.
Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality.
We used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016.
Our model predicted that 1840 (95% Simulation Interval [SI]: -2757 – 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 – 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 – 1812) and 1609 (95% SI: 972 – 2037) lives saved per 10,000 persons incarcerated, respectively.
Prison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact. |
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| AbstractList | •Medications for opioid use disorder in prisons/jails reduced overdose post-release.•Our model predicted that treatment alone would have saved 1840 lives.•We predicted that treatment and post-release retention would have saved 4400 lives.
Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality.
We used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016.
Our model predicted that 1840 (95% Simulation Interval [SI]: -2757 – 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 – 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 – 1812) and 1609 (95% SI: 972 – 2037) lives saved per 10,000 persons incarcerated, respectively.
Prison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact. Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality.BACKGROUNDMedications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality.We used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016.METHODSWe used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016.Our model predicted that 1840 (95% Simulation Interval [SI]: -2757 - 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 - 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 - 1812) and 1609 (95% SI: 972 - 2037) lives saved per 10,000 persons incarcerated, respectively.RESULTSOur model predicted that 1840 (95% Simulation Interval [SI]: -2757 - 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 - 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 - 1812) and 1609 (95% SI: 972 - 2037) lives saved per 10,000 persons incarcerated, respectively.Prison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact.CONCLUSIONSPrison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact. Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality. We used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016. Our model predicted that 1840 (95% Simulation Interval [SI]: -2757 - 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 - 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 - 1812) and 1609 (95% SI: 972 - 2037) lives saved per 10,000 persons incarcerated, respectively. Prison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact. Background: Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in US prisons and jail settings, and limited data are available to guide policy decisions. The objective of this study was to estimate the impact of screening and treatment with medications for OUD in US prisons and jails on post-release opioid-related mortality. Methods: We used data from the National Center for Vital Statistics, the Bureau of Justice Statistics, and relevant literature to construct Monte Carlo simulations of a counterfactual scenario in which wide scale uptake of screening and treatment with medications for OUD occurred in US prisons and jails in 2016. Results: Our model predicted that 1840 (95% Simulation Interval [SI]: -2757 – 4959) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated. The model also predicted that approximately 4400 (95% SI: 2675 – 5557) lives would have been saved nationally if all persons who were clinically indicated had received medications for OUD while incarcerated and were retained in treatment post-release. These estimates correspond to 668 (95% SI: -1008 – 1812) and 1609 (95% SI: 972 – 2037) lives saved per 10,000 persons incarcerated, respectively. Conclusions: Prison and jail-based programs that comprehensively screen and provide treatment with medications for OUD have the potential to produce substantial reductions in opioid-related overdose deaths in a high-risk population; however, retention on treatment post-release is a key driver of population level impact. |
| ArticleNumber | 107858 |
| Author | Martin, Rosemarie A. Green, Traci C. Rich, Josiah D. Clarke, Jennifer G. Macmadu, Alexandria Brinkley-Rubinstein, Lauren Goedel, William C. Adams, Joëlla W. Marshall, Brandon D.L. |
| AuthorAffiliation | 5. Department of Emergency Medicine, Boston University Medical Center, 725 Albany Street, Boston, MA 02118, USA 3. Department of Social Medicine, University of North Carolina at Chapel Hill, 333 South Columbia Street, Chapel Hill, NC 27516, USA 2. The Center for Prisoner Health and Human Rights, The Miriam Hospital, 8 Third Street, Providence, RI, USA 1. Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA 6. Rhode Island Department of Corrections, 40 Howard Avenue, Cranston, RI 02920, USA 4. Center for Health Equity Research, University of North Carolina at Chapel Hill, 335 South Columbia Street, Chapel Hill, NC 27514, USA 7. Department of Behavioral and Social Science, Brown University, 121 South Main Street, Providence, RI 02903, USA |
| AuthorAffiliation_xml | – name: 1. Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – name: 6. Rhode Island Department of Corrections, 40 Howard Avenue, Cranston, RI 02920, USA – name: 2. The Center for Prisoner Health and Human Rights, The Miriam Hospital, 8 Third Street, Providence, RI, USA – name: 5. Department of Emergency Medicine, Boston University Medical Center, 725 Albany Street, Boston, MA 02118, USA – name: 3. Department of Social Medicine, University of North Carolina at Chapel Hill, 333 South Columbia Street, Chapel Hill, NC 27516, USA – name: 4. Center for Health Equity Research, University of North Carolina at Chapel Hill, 335 South Columbia Street, Chapel Hill, NC 27514, USA – name: 7. Department of Behavioral and Social Science, Brown University, 121 South Main Street, Providence, RI 02903, USA |
| Author_xml | – sequence: 1 givenname: Alexandria surname: Macmadu fullname: Macmadu, Alexandria organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – sequence: 2 givenname: William C. surname: Goedel fullname: Goedel, William C. organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – sequence: 3 givenname: Joëlla W. surname: Adams fullname: Adams, Joëlla W. organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – sequence: 4 givenname: Lauren surname: Brinkley-Rubinstein fullname: Brinkley-Rubinstein, Lauren organization: Department of Social Medicine, University of North Carolina at Chapel Hill, 333 South Columbia Street, Chapel Hill, NC, 27516, USA – sequence: 5 givenname: Traci C. surname: Green fullname: Green, Traci C. organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – sequence: 6 givenname: Jennifer G. surname: Clarke fullname: Clarke, Jennifer G. organization: Rhode Island Department of Corrections, 40 Howard Avenue, Cranston, RI, 02920, USA – sequence: 7 givenname: Rosemarie A. surname: Martin fullname: Martin, Rosemarie A. organization: Department of Behavioral and Social Science, Brown University, 121 South Main Street, Providence, RI 02903, USA – sequence: 8 givenname: Josiah D. surname: Rich fullname: Rich, Josiah D. organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA – sequence: 9 givenname: Brandon D.L. surname: Marshall fullname: Marshall, Brandon D.L. email: brandon_marshall@brown.edu organization: Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32050112$$D View this record in MEDLINE/PubMed |
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| Keywords | Prison Jail Overdose Medications for opioid use disorder Opioids |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 CONTRIBUTORS AM, BDLM, JDR, and WCG conceptualized the study and design. AM developed initial drafts of the manuscript. AM and WCG conducted all analyses. JWA contributed significantly to writing the methods section. WCG, JWA, LBR, TCG, JGC, RAM, JDR, and BDLM provided iterative and substantive feedback on the overall approach and all drafts of the manuscript. All authors have approved the final manuscript. |
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| Snippet | •Medications for opioid use disorder in prisons/jails reduced overdose post-release.•Our model predicted that treatment alone would have saved 1840 lives.•We... Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely limited in... Background: Medications for opioid use disorder (OUD) are the most effective treatment for OUD, but uptake of these life-saving medications has been extremely... |
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| SubjectTerms | Adult Analgesics, Opioid - therapeutic use Clinical assessment Computer simulation Correctional Facilities - statistics & numerical data Deaths Drug addiction Drugs Female High risk Humans Imprisonment Jail Jails Life Tables Male Mass Screening - mortality Medical screening Medications for opioid use disorder Middle Aged Monte Carlo Method Monte Carlo simulation Narcotics Opioid-Related Disorders - diagnosis Opioid-Related Disorders - drug therapy Opioid-Related Disorders - mortality Opioids Overdose Prison Prisoners Prisons Procedures and Techniques Utilization - statistics & numerical data Risk Factors Simulation Statistics Substance abuse treatment Substance use disorder Tests Treatment Outcome United States - epidemiology Uptake Vital statistics Young Adult |
| Title | Estimating the impact of wide scale uptake of screening and medications for opioid use disorder in US prisons and jails |
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