TY - JOUR
T1 - Applied machine learning analysis
T2 - Factors correlated with injection drug use and post-prison medication for opioid use disorder treatment engagement
AU - Victor, Grant
AU - Roddy, Ariel
AU - Lenz, Danielle
AU - Willis, Tamarie
AU - Kubiak, Sheryl
N1 - Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.
PY - 2023
Y1 - 2023
N2 - Objectives: This study aimed to classify the factors that were correlated with injection drug use (IDU) and with medications for opioid use disorder (MOUD) treatment engagement among individuals who were recently released from prison. Methods: Data for this study were obtained from a Midwestern reentry program for incarcerated individuals with co-occurring opioid use and a mental health disorder between May 1, 2017, and April 30, 2020. CHAID decision tree modeling was utilized to classify IDU and MOUD treatment engagement. Results: Those most likely to report IDU were individuals with a Hepatitis C diagnosis and a history of overdose, and those least likely to report IDU were not diagnosed with Hepatitis C, identified as a person of color, and never overdosed on opioids. The subgroup of that were most likely to report MOUD treatment engagement were individuals taking psychiatric medication and who had a history of IDU. The subgroup of participants least likely to report MOUD treatment engagement were individuals prescribed psychiatric medication, without had a history of IDU, and were not participating in substance-use treatment. Conclusion: Our findings indicate that, to protect vulnerable populations and to flatten the overdose mortality curve, an increased focus is required within criminal/legal systems to facilitate linkages to care at reentry.
AB - Objectives: This study aimed to classify the factors that were correlated with injection drug use (IDU) and with medications for opioid use disorder (MOUD) treatment engagement among individuals who were recently released from prison. Methods: Data for this study were obtained from a Midwestern reentry program for incarcerated individuals with co-occurring opioid use and a mental health disorder between May 1, 2017, and April 30, 2020. CHAID decision tree modeling was utilized to classify IDU and MOUD treatment engagement. Results: Those most likely to report IDU were individuals with a Hepatitis C diagnosis and a history of overdose, and those least likely to report IDU were not diagnosed with Hepatitis C, identified as a person of color, and never overdosed on opioids. The subgroup of that were most likely to report MOUD treatment engagement were individuals taking psychiatric medication and who had a history of IDU. The subgroup of participants least likely to report MOUD treatment engagement were individuals prescribed psychiatric medication, without had a history of IDU, and were not participating in substance-use treatment. Conclusion: Our findings indicate that, to protect vulnerable populations and to flatten the overdose mortality curve, an increased focus is required within criminal/legal systems to facilitate linkages to care at reentry.
KW - incarceration
KW - medication for opioid use disorder
KW - opioid
KW - reentry
UR - http://www.scopus.com/inward/record.url?scp=85160109213&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85160109213&partnerID=8YFLogxK
U2 - 10.1080/10509674.2023.2213693
DO - 10.1080/10509674.2023.2213693
M3 - Article
AN - SCOPUS:85160109213
SN - 1050-9674
VL - 62
SP - 297
EP - 314
JO - Journal of Offender Rehabilitation
JF - Journal of Offender Rehabilitation
IS - 5
ER -