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Ly KN, Barker LK, Kilmer G, Shing JZ, Jiles RB, Teshale E. Disparities in hepatitis C among people aged 12-59 with no history of injection drug use, United States, January 2013-March 2020. Liver Int 2024. [PMID: 39324414 DOI: 10.1111/liv.16108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 08/21/2024] [Accepted: 09/11/2024] [Indexed: 09/27/2024]
Abstract
BACKGROUND AND AIMS In the United States, hepatitis C virus (HCV) infection occurs primarily through injection drug use (IDU), but transmission also occurs through other ways. This study examined HCV prevalence and disparities among US residents aged 12-59 years with no IDU history. METHODS We analysed 2013-March 2020 National Health and Nutrition Examination Survey data to calculate the HCV prevalence among people with no drug use history and only a non-IDU history, collectively referred to as no IDU history. These estimates were compared to those with an IDU history and stratified by sociodemographic and hepatitis A and hepatitis B serologic characteristics. RESULTS The current HCV infection prevalence among people aged 12-59 was .7% overall, and specifically 17.2% among people with an IDU history, .9% among people with a non-IDU history and .2% among people with no drug use history. These rates represented 1.4 million people with current HCV infection, of whom, 730 000 had an IDU history, 262 000 had a non-IDU history and 309 000 had no drug use history. Among people with no drug use history, current HCV infection prevalence was higher for people born during 1954-1965 versus after 1965, had completed high school or less versus at least some college and had past/present hepatitis B versus vaccinated for hepatitis B. CONCLUSION While the HCV infection burden was highest among people with an IDU history, we found a sizeable burden among people without such a history. These findings support policies and practices aimed at addressing disparities among people needing treatment.
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Affiliation(s)
- Kathleen N Ly
- Division of Viral Hepatitis, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Laurie K Barker
- Division of Viral Hepatitis, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Greta Kilmer
- Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jaimie Z Shing
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ruth B Jiles
- Division of Viral Hepatitis, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Eyasu Teshale
- Division of Viral Hepatitis, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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DeCamillis RB, Hekman AL, Priest DH. Screening for hepatitis C as part of an opioid stewardship quality improvement initiative: Identifying infected patients and analyzing linkage to care. Clin Liver Dis (Hoboken) 2024; 23:e0118. [PMID: 38283305 PMCID: PMC10810596 DOI: 10.1097/cld.0000000000000118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/07/2023] [Indexed: 01/30/2024] Open
Abstract
Screening patients with opioid use disorder (OUD) for HCV can potentially decrease morbidity and mortality if HCV-infected individuals are linked to care. We describe a quality improvement initiative focused on patients with OUD, incorporating an electronic health record decision-support tool for HCV screening across multiple health care venues, and examining the linkage to HCV care. Of 5829 patients with OUD, 4631 were tested for HCV (79.4%), (compared to a baseline of 8%) and 1614 (27.7%) tested positive. Two hundred and thirty patients had died at the study onset. Patients tested in the acute care and emergency department settings were more likely to test positive than those in the ambulatory setting (OR = 2.21 and 2.49, p < 0.001). Before patient outreach, 279 (18.2%) HCV-positive patients were linked to care. After patient outreach, 326 (23.0%) total patients were linked to care. Secondary end points included mortality and the number of patients who were HCV-positive who achieved a cure. The mortality rate in patients who were HCV-positive (12.2%) was higher than that in patients who were HCV-negative (7.4%) (OR = 1.72, p < 0.001) or untested patients (6.2%) (OR = 2.10, p<0.001). Of the 326 with successful linkage to care, 113 (34.7%) had a documented cure. An additional 55 (16.9%) patients had a possible cure, defined as direct acting antiviral ordered but no follow-up documented, known treatment in the absence of documented sustained viral response lab draw, or documentation of cure noted in outside medical records but unavailable laboratory results. A strategy utilizing electronic health record decision-support tools for testing patients with OUD for HCV was highly effective; however, linking patients with HCV to care was less successful.
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Ahrens K, Sharbaugh M, Jarlenski MP, Tang L, Allen L, Austin AE, Barnes AJ, Burns ME, Clark S, Zivin K, Mack A, Liu G, Mohamoud S, McDuffie MJ, Hammerslag L, Gordon AJ, Donohue JM. Prevalence of Testing for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Among Medicaid Enrollees Treated With Medications for Opioid Use Disorder in 11 States, 2016-2019. Clin Infect Dis 2023; 76:1793-1801. [PMID: 36594172 PMCID: PMC10209438 DOI: 10.1093/cid/ciac981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/21/2022] [Accepted: 12/29/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Limited information exists about testing for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) among Medicaid enrollees after starting medication for opioid use disorder (MOUD), despite guidelines recommending such testing. Our objectives were to estimate testing prevalence and trends for HIV, HBV, and HCV among Medicaid enrollees initiating MOUD and examine enrollee characteristics associated with testing. METHODS We conducted a serial cross-sectional study of 505 440 initiations of MOUD from 2016 to 2019 among 361 537 Medicaid enrollees in 11 states. Measures of MOUD initiation; HIV, HBV, and HCV testing; comorbidities; and demographics were based on enrollment and claims data. Each state used Poisson regression to estimate associations between enrollee characteristics and testing prevalence within 90 days of MOUD initiation. We pooled state-level estimates to generate global estimates using random effects meta-analyses. RESULTS From 2016 to 2019, testing increased from 20% to 25% for HIV, from 22% to 25% for HBV, from 24% to 27% for HCV, and from 15% to 19% for all 3 conditions. Adjusted rates of testing for all 3 conditions were lower among enrollees who were male (vs nonpregnant females), living in a rural area (vs urban area), and initiating methadone or naltrexone (vs buprenorphine). Associations between enrollee characteristics and testing varied across states. CONCLUSIONS Among Medicaid enrollees in 11 US states who initiated medications for opioid use disorder, testing for human immunodeficiency virus, hepatitis B virus, hepatitis C virus, and all 3 conditions increased between 2016 and 2019 but the majority were not tested.
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Affiliation(s)
- Katherine Ahrens
- Public Health Program, Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA
| | - Michael Sharbaugh
- Department of Health Policy and Management, University of Pittsburgh, School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Marian P Jarlenski
- Department of Health Policy and Management, University of Pittsburgh, School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Lu Tang
- Department of Biostatistics, University of Pittsburgh, School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Lindsay Allen
- Health Policy, Management, and Leadership Department, School of Public Health, West Virginia University, Morgantown, West Virginia, USA
| | - Anna E Austin
- Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Andrew J Barnes
- Health Behavior and Policy Department, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Marguerite E Burns
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA
| | - Sarah Clark
- Department of Pediatrics, School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Kara Zivin
- Department of Psychiatry, School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Aimee Mack
- Government Resource Center, Ohio Colleges of Medicine, Ohio State University, Columbus, Ohio, USA
| | - Gilbert Liu
- Government Resource Center, Ohio Colleges of Medicine, Ohio State University, Columbus, Ohio, USA
| | - Shamis Mohamoud
- Hilltop Institute, University of Maryland Baltimore County, Baltimore, Maryland, USA
| | - Mary Joan McDuffie
- Center for Community Research & Service, Biden School of Public Policy and Administration, University of Delaware, Newark, Delaware, USA
| | - Lindsey Hammerslag
- College of Medicine, Institute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, USA
| | - Adam J Gordon
- Program for Addiction Research, Clinical Care, Knowledge and Advocacy, Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Informatics, Decision-Enhancement, and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
| | - Julie M Donohue
- Department of Health Policy and Management, University of Pittsburgh, School of Public Health, Pittsburgh, Pennsylvania, USA
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