Alexandria Macmadu1, Kimberly Paull2, Rouba Youssef2, Sivakumar Batthala2, Kevin H Wilson3, Elizabeth A Samuels4, Jesse L Yedinak5, Brandon D L Marshall6. 1. Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA; The Center for Prisoner Health and Human Rights, The Miriam Hospital, 8 Third Street, Providence, RI, USA. 2. Executive Office of Health and Human Services, State of Rhode Island, Cranston, RI, USA. 3. The Policy Lab, Brown University, Providence, RI, USA. 4. Department of Emergency Medicine, Alpert Medical School of Brown University, Providence, RI, USA. 5. Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA. 6. Department of Epidemiology, Brown University School of Public Health, 121 South Main Street, Providence, RI, USA. Electronic address: brandon_marshall@brown.edu.
Abstract
BACKGROUND: Medicaid recipients have a high burden of opioid overdose and opioid use disorder (OUD). Opioid agonist therapies are an effective treatment for OUD, but there is a wide and persisting gap between those who are indicated and those who receive treatment. The objective of this study was to identify the predictors of enrollment in opioid agonist therapy within 6 months of an opioid overdose or OUD diagnosis in a cohort of Medicaid recipients. METHODS: Using multiple linked, state-level databases, we conducted a retrospective cohort study of 17,449 Medicaid recipients in Rhode Island who had an opioid overdose or an OUD diagnosis between July 2013 and June 2018. RESULTS: The majority (58 %) of Medicaid recipients did not enroll in opioid agonist therapy within 6 months. In adjusted models, having one or more prior overdose (adjusted risk ratio [ARR] = 0.33, 95 % CI: 0.28, 0.38), alcohol use disorder (ARR = 0.56, 95 % CI: 0.52, 0.60), or back problems (ARR = 0.58, 95 % CI: 0.55, 0.61) were strong predictors of non-enrollment. Conversely, emergency department (ARR = 1.31, 95 % CI: 1.28-1.34) and primary care provider (ARR = 1.03, 95 % CI: 1.01-1.34) visit frequency above the 75th percentile were associated with timely enrollment in opioid agonist therapy. CONCLUSIONS: Our findings underscore the need to enhance pathways to treatment for OUD through varied nodes of engagement with healthcare systems. Interventions to improve screening for OUD and referrals to opioid agonist therapies should include high-impact settings, such as treatment programs for alcohol and substance use disorders, pain clinics, and outpatient behavioral care settings.
BACKGROUND: Medicaid recipients have a high burden of opioid overdose and opioid use disorder (OUD). Opioid agonist therapies are an effective treatment for OUD, but there is a wide and persisting gap between those who are indicated and those who receive treatment. The objective of this study was to identify the predictors of enrollment in opioid agonist therapy within 6 months of an opioid overdose or OUD diagnosis in a cohort of Medicaid recipients. METHODS: Using multiple linked, state-level databases, we conducted a retrospective cohort study of 17,449 Medicaid recipients in Rhode Island who had an opioid overdose or an OUD diagnosis between July 2013 and June 2018. RESULTS: The majority (58 %) of Medicaid recipients did not enroll in opioid agonist therapy within 6 months. In adjusted models, having one or more prior overdose (adjusted risk ratio [ARR] = 0.33, 95 % CI: 0.28, 0.38), alcohol use disorder (ARR = 0.56, 95 % CI: 0.52, 0.60), or back problems (ARR = 0.58, 95 % CI: 0.55, 0.61) were strong predictors of non-enrollment. Conversely, emergency department (ARR = 1.31, 95 % CI: 1.28-1.34) and primary care provider (ARR = 1.03, 95 % CI: 1.01-1.34) visit frequency above the 75th percentile were associated with timely enrollment in opioid agonist therapy. CONCLUSIONS: Our findings underscore the need to enhance pathways to treatment for OUD through varied nodes of engagement with healthcare systems. Interventions to improve screening for OUD and referrals to opioid agonist therapies should include high-impact settings, such as treatment programs for alcohol and substance use disorders, pain clinics, and outpatient behavioral care settings.
Authors: Arthur Robin Williams; Edward V Nunes; Adam Bisaga; Frances R Levin; Mark Olfson Journal: Am J Drug Alcohol Abuse Date: 2019-01-24 Impact factor: 3.829
Authors: Camille A Dunkley; Joseph E Carpenter; Brian P Murray; Emma Sizemore; Matthew Wheatley; Brent W Morgan; Tim P Moran; Alaina Steck Journal: J Emerg Med Date: 2019-05-03 Impact factor: 1.484
Authors: Katherine M Waye; Jonathan Goyer; Debra Dettor; Linda Mahoney; Elizabeth A Samuels; Jesse L Yedinak; Brandon D L Marshall Journal: Addict Behav Date: 2018-09-25 Impact factor: 3.913
Authors: Bobbi Jo H Yarborough; Scott P Stumbo; Dennis McCarty; Jennifer Mertens; Constance Weisner; Carla A Green Journal: Drug Alcohol Depend Date: 2016-01-06 Impact factor: 4.492
Authors: Nicole Kravitz-Wirtz; Corey S Davis; William R Ponicki; Ariadne Rivera-Aguirre; Brandon D L Marshall; Silvia S Martins; Magdalena Cerdá Journal: JAMA Netw Open Date: 2020-01-03
Authors: Stephen Crystal; Molly Nowels; Hillary Samples; Mark Olfson; Arthur Robin Williams; Peter Treitler Journal: Drug Alcohol Depend Date: 2022-01-10 Impact factor: 4.492
Authors: Alexandria Macmadu; Sivakumar Batthala; Annice M Correia Gabel; Marti Rosenberg; Rik Ganguly; Jesse L Yedinak; Benjamin D Hallowell; Rachel P Scagos; Elizabeth A Samuels; Magdalena Cerdá; Kimberly Paull; Brandon D L Marshall Journal: JAMA Netw Open Date: 2021-09-01
Authors: August F Holtyn; Forrest Toegel; Matthew D Novak; Jeannie-Marie Leoutsakos; Michael Fingerhood; Kenneth Silverman Journal: Drug Alcohol Depend Date: 2021-05-27 Impact factor: 4.852
Authors: Marguerite E Burns; Steven Cook; Lars M Brown; Laura Dague; Steve Tyska; Karla Hernandez Romero; Cici McNamara; Ryan P Westergaard Journal: JAMA Netw Open Date: 2022-01-04