Sex-specific Risk Factors and Health Disparity Among Hepatitis C Positive Patients Receiving Pharmacotherapy for Opioid Use Disorder

Abstract Background Despite high hepatitis C virus (HCV) prevalence, opioid use disorder (OUD) patients on methadone rarely engage in HCV treatment. We investigated the effectiveness of HCV management via telemedicine in an opioid substitution therapy (OST) program. Methods OUD patients on methadone underwent biweekly telemedicine sessions between a hepatologist and physician assistant during the entire HCV treatment course. All pretreatment labs (HCV RNA, genotype, and noninvasive fibrosis assessments) were obtained onsite and direct-acting antivirals were coadministered with methadone using modified directly observed therapy. We used multiple correspondence analysis, least absolute shrinkage and selection operator, and logistic regression to identify variables associated with pursuit of HCV care. Results Sixty-two HCV RNA–positive patients (24% human immunodeficiency virus [HIV] infected, 61% male, 61% African American, 25.8% Hispanic) were evaluated. All patients were stabilized on methadone and all except 4 were HCV genotype 1 infected. Advanced fibrosis/cirrhosis was present in 34.5% of patients. Of the 45 treated patients, 42 (93.3%) achieved viral eradication. Of 17 evaluated patients who were not treated, 5 were discontinued from the drug treatment program or did not follow up after the evaluation, 2 had HIV adherence issues, and 10 had insurance authorization issues. Marriage and a mental health diagnosis other than depression were the strongest positive predictors of treatment pursuit, whereas being divorced, separated, or widowed was the strongest negative predictor. Conclusions HCV management via telemedicine integrated into an OST program is a feasible model with excellent virologic effectiveness. Psychosocial and demographic variables can assist in identification of subgroups with a propensity or aversion to pursue HCV treatment.

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Development of an Interdisciplinary Telehealth Model of Provider Training and Comprehensive Care for Hepatitis C and Opioid Use Disorder in a High-Burden Region

The Journal of Infectious Diseases ◽

10.1093/infdis/jiaa141 ◽

2020 ◽

Vol 222 (Supplement_5) ◽

pp. S354-S364 ◽

Cited By ~ 1

Author(s):

Jacqueline E Sherbuk ◽

Terry Kemp Knick ◽

Chelsea Canan ◽

Patrice Ross ◽

Bailey Helbert ◽

...

Keyword(s):

Hepatitis C ◽

Sustained Virologic Response ◽

Virologic Response ◽

Opioid Use Disorder ◽

Support Staff ◽

World Population ◽

Opioid Use ◽

Provider Training ◽

Financial Barriers ◽

Efficient Treatment

Abstract Background Hepatitis C virus (HCV) and the opioid epidemic disproportionately affect the Appalachian region. Geographic and financial barriers prevent access to specialty care. Interventions are needed to address the HCV-opioid syndemic in this region. Methods We developed an innovative, collaborative telehealth model in Southwest Virginia featuring bidirectional referrals from and to comprehensive harm reduction (CHR) programs and office-based opioid therapy (OBOT), as well as workforce development through local provider training in HCV management. We aimed to (1) describe the implementation process of provider training and (2) assess the effectiveness of the telehealth model by monitoring patient outcomes in the first year. Results The provider training model moved from a graduated autonomy model with direct specialist supervision to a 1-day workshop with parallel tracks for providers and support staff followed by monthly case conferences. Forty-four providers and support staff attended training. Eight providers have begun treating independently. For the telehealth component, 123 people were referred, with 62% referred from partner OBOT or CHR sites; 103 (84%) attended a visit, 93 (76%) completed the treatment course, and 61 (50%) have achieved sustained virologic response. Rates of sustained virologic response did not differ by receipt of treatment for opioid use disorder. Conclusions Providers demonstrated a preference for an in-person training workshop, though further investigation is needed to determine why only a minority of those trained have begun treating HCV independently. The interdisciplinary nature of this program led to efficient treatment of hepatitis C in a real-world population with a majority of patients referred from OBOTs and CHR programs.

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Practical steps to improve chronic hepatitis C treatment in people with opioid use disorder

Hepatic Medicine Evidence and Research ◽

10.2147/hmer.s187133 ◽

2018 ◽

Vol Volume 11 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Carlos Roncero ◽

Pablo Ryan ◽

Richard Littlewood ◽

Juan Macías ◽

Juan Ruiz ◽

...

Keyword(s):

Chronic Hepatitis ◽

Hepatitis C ◽

Chronic Hepatitis C ◽

Opioid Use Disorder ◽

Opioid Use ◽

Hepatitis C Treatment

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Risk Factors for Treatment Drop-Out: Implications for Adverse Outcomes When Treating Opioid Use Disorder

Journal of Social Work Practice in the Addictions ◽

10.1080/1533256x.2020.1838859 ◽

2020 ◽

Vol 20 (4) ◽

pp. 292-301

Author(s):

Patricia Ann Iovine ◽

David Drachman ◽

Harshal Kirane

Keyword(s):

Risk Factors ◽

Opioid Use Disorder ◽

Adverse Outcomes ◽

Drop Out ◽

Opioid Use

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Pluri Psychopathology and Risk of Opioid Use Disorder

Journal of Clinical Review & Case Reports ◽

10.33140/jcrc/03/07/00004 ◽

2018 ◽

Vol 3 (7) ◽

Keyword(s):

Risk Factors ◽

Chronic Pain ◽

Risk Factor ◽

Cancer Pain ◽

Gender Dysphoria ◽

Psychiatric Comorbidity ◽

Opioid Use Disorder ◽

Opioid Use ◽

Transdermal Fentanyl ◽

Case Presentation

Background: Psychiatric comorbidty is an important risk factor when predicting risk of opioid use disorder in chronic non-cancer pain. We present a case with gender dysphoria, in wich psychiatric comorbidity was not taken into account for de prescription of pharmacological treatment for pain. Case presentation: We report the case of a 51-year-old man with gender dysphoria, personality disorder, chronic pain disorder and opioid use disorder. For the last 9 years he has taken continuousy transdermal fentanyl prescribed by chronic non-cancer pain. Despite of presenting a pluripathology that discouraged the use of opioids in this patient, throughout his evolution, he has gone to different non-psychiatrists and has shown himself with a querulous, confictive and demanding attitude, so that he managed to keep on raising his dose of prescribed opioids. Conclusions: This case shows the importance of knowing the risk factors of consumption due to the use of opioids patients with chronic non-cancer pain, the importance of psychiatric comorbidity associated with prognosis and the neeed to know exactly how opioids are managed by some prescribers, as well as to carry out an interdisciplinary therapeutic plan to avoid risks.

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Predictors of Premature Discontinuation of Opioid Use Disorder Treatment in the United States

10.1101/2021.07.26.21261080 ◽

2021 ◽

Author(s):

Celia Stafford ◽

Wesley Marrero ◽

Rebecca B. Naumann ◽

Kristen Hassmiller Lich ◽

Sarah Wakeman ◽

...

Keyword(s):

Risk Factors ◽

Substance Use ◽

The United States ◽

Opioid Use Disorder ◽

Geographic Region ◽

Influential Factors ◽

Opioid Use ◽

Living Situation ◽

Data Set ◽

Targeted Interventions

Over the last few decades, opioid use disorder (OUD) and overdose have dramatically increased. Evidence shows that treatment for OUD, particularly medication for OUD, is highly effective; however, despite decreases in barriers to treatment, retention in OUD treatment remains a challenge. Therefore, understanding key risk factors for OUD treatment discontinuation remains a critical priority. We built a machine learning model using the Treatment Episode Data Set-Discharge (TEDS-D). Included were 2,446,710 treatment episodes for individuals in the U.S. discharged between January 1, 2015 and December 31, 2018 (the most recent available data). Exposures contain 32 potential risk factors, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. Our findings show that the most influential risk factors include characteristics of treatment service setting, geographic region, primary source of payment, referral source, and health insurance status. Importantly, several factors previously reported as influential predictors, such as age, living situation, age of first substance use, race and ethnicity, and sex had far weaker predictive impacts. The influential factors identified in this study should be more closely explored to inform targeted interventions and improve future models of care.

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