The cascade of care for commercially-insured persons with opioid use disorder and comorbid HIV and HCV infections.

Cascade of care Communicable comorbidities HCV HIV Medications for opioid use disorder (MOUD) Opioid use disorder Treatment initiation Treatment retention

Journal

Drug and alcohol dependence
ISSN: 1879-0046
Titre abrégé: Drug Alcohol Depend
Pays: Ireland
ID NLM: 7513587

Informations de publication

Date de publication:
12 Aug 2024
Historique:
received: 19 04 2024
revised: 17 07 2024
accepted: 06 08 2024
medline: 20 8 2024
pubmed: 20 8 2024
entrez: 19 8 2024
Statut: aheadofprint

Résumé

Opioid use disorder (OUD) significantly impacts individual and public health and exacerbated further by concurrent infectious diseases. A syndemic approach is needed to address the intertwined OUD, HIV, and HCV epidemics, including the expanded use of medications for opioid use disorder (MOUD). To identify MOUD scale-up opportunities, we conducted a retrospective cohort study, representing commercially insured persons, and created the OUD care continuum, including HIV and HCV influences in adults (18-64 years) newly diagnosed with OUD in 2019 using Merative MarketSan data. Among 124,467,633 individuals, the prevalence of OUD was 0.4 % (95 % CI: 0.36 %-0.46 %; N = 497,871), with 327,277 (65.7 %, 95 % CI: 65.60 %-65.87 %) newly diagnosed in 2019. Among these newly diagnosed individuals (54 % men, mean age 44±0.01), 53,568 (27.0 %, 95 % CI: 26.4 %-27.5 %) were prescribed MOUD, with retention rates at 1, 3, and 6 months being 89.0 % (95 % CI: 88.2 %-89.8 %), 66.0 % (95 % CI: 64.8 %-67.2 %), and 50.3 % (95 % CI: 48.3 %-51.6 %), respectively. Buprenorphine was the most prescribed MOUD (79.6 %, 95 % CI: 78.6 %-80.7 %), followed by XR-NTX (14.9 %, 95 % CI:14.0 %-15.8 %) and methadone (5.5 %, 95 % CI: 4.9 %-6.1 %). Six-month retention was highest for methadone (73.4 %, 95 % CI: 73.0 %-73.8 %), however, followed by buprenorphine (55.7 %, 95 % CI: 55.3 %-57.1 %) and substantially lower for XR-NTX (12.6 %, 95 % CI: 10.6 %-14.6 %). Screening for HIV and HCV was low among OUD enrollees (11.1 %, 14.4 %), slightly higher for MOUD initiators (18.0 %, 21.6 %). Being prescribed MOUD was correlated with HCV infection (AOR: 2.54; 95 % CI: 2.41-2.68), HCV/HIV coinfection (AOR: 1.89; 95 % CI: 1.41-2.53), and hospitalization for OUD-related services (AOR: 1.14; 95 % CI: 1.11-1.17), yet hospitalization for OUD-related services was positively correlated with XR-NTX (AOR: 2.72; 95 % CI: 2.56-2.85) prescription and negatively with methadone (AOR: 0.19; 95 % CI: 0.16-0.23) prescription. Having HIV was negatively correlated with being prescribed methadone (AOR: 0.33; 95 % CI: 0.13-0.86). Substantial gaps in the OUD cascade persist, underscoring better implementation opportunities for MOUD prescription in hospital-based settings and expanding access to methadone beyond highly regulated sites given its low coverage yet high treatment retention.

Sections du résumé

BACKGROUND BACKGROUND
Opioid use disorder (OUD) significantly impacts individual and public health and exacerbated further by concurrent infectious diseases. A syndemic approach is needed to address the intertwined OUD, HIV, and HCV epidemics, including the expanded use of medications for opioid use disorder (MOUD).
METHODS METHODS
To identify MOUD scale-up opportunities, we conducted a retrospective cohort study, representing commercially insured persons, and created the OUD care continuum, including HIV and HCV influences in adults (18-64 years) newly diagnosed with OUD in 2019 using Merative MarketSan data.
RESULTS RESULTS
Among 124,467,633 individuals, the prevalence of OUD was 0.4 % (95 % CI: 0.36 %-0.46 %; N = 497,871), with 327,277 (65.7 %, 95 % CI: 65.60 %-65.87 %) newly diagnosed in 2019. Among these newly diagnosed individuals (54 % men, mean age 44±0.01), 53,568 (27.0 %, 95 % CI: 26.4 %-27.5 %) were prescribed MOUD, with retention rates at 1, 3, and 6 months being 89.0 % (95 % CI: 88.2 %-89.8 %), 66.0 % (95 % CI: 64.8 %-67.2 %), and 50.3 % (95 % CI: 48.3 %-51.6 %), respectively. Buprenorphine was the most prescribed MOUD (79.6 %, 95 % CI: 78.6 %-80.7 %), followed by XR-NTX (14.9 %, 95 % CI:14.0 %-15.8 %) and methadone (5.5 %, 95 % CI: 4.9 %-6.1 %). Six-month retention was highest for methadone (73.4 %, 95 % CI: 73.0 %-73.8 %), however, followed by buprenorphine (55.7 %, 95 % CI: 55.3 %-57.1 %) and substantially lower for XR-NTX (12.6 %, 95 % CI: 10.6 %-14.6 %). Screening for HIV and HCV was low among OUD enrollees (11.1 %, 14.4 %), slightly higher for MOUD initiators (18.0 %, 21.6 %). Being prescribed MOUD was correlated with HCV infection (AOR: 2.54; 95 % CI: 2.41-2.68), HCV/HIV coinfection (AOR: 1.89; 95 % CI: 1.41-2.53), and hospitalization for OUD-related services (AOR: 1.14; 95 % CI: 1.11-1.17), yet hospitalization for OUD-related services was positively correlated with XR-NTX (AOR: 2.72; 95 % CI: 2.56-2.85) prescription and negatively with methadone (AOR: 0.19; 95 % CI: 0.16-0.23) prescription. Having HIV was negatively correlated with being prescribed methadone (AOR: 0.33; 95 % CI: 0.13-0.86).
CONCLUSIONS CONCLUSIONS
Substantial gaps in the OUD cascade persist, underscoring better implementation opportunities for MOUD prescription in hospital-based settings and expanding access to methadone beyond highly regulated sites given its low coverage yet high treatment retention.

Identifiants

pubmed: 39159600
pii: S0376-8716(24)01335-8
doi: 10.1016/j.drugalcdep.2024.112410
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

112410

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors report no declarations of interest.

Auteurs

Roman Ivasiy (R)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States. Electronic address: roman.ivasiy@yale.edu.

Lynn M Madden (LM)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States; APT Foundation, New Haven, CT, United States.

Elizabeth DiDomizio (E)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States.

Kimberly A Johnson (KA)

College of Behavioral and Community Science, Department of Mental Health Law and Policy, University of South Florida, Tampa, FL, United States.

Eteri Machavariani (E)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States.

Bachar Ahmad (B)

Yale School of Medicine, New Haven, CT, United States.

David Oliveros (D)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States.

A Ram (A)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States.

Natalie Kil (N)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States.

Frederick L Altice (FL)

Yale School of Medicine, Section of Infectious Diseases, New Haven, CT, United States; APT Foundation, New Haven, CT, United States; Center for Interdisciplinary Research on AIDS, Yale University, New Haven, CT, United States; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States; Yale School of Public Health, Department of Epidemiology of Microbial Diseases, New Haven, CT, United States. Electronic address: Frederick.Altice@yale.edu.

Classifications MeSH