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310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model
BACKGROUND: Direct-acting antivirals (DAAs) have simplified and expanded access to Hepatitis C virus (HCV) treatment. Only 17% of the estimated 2.4 million Americans currently infected with HCV have linked to HCV specialty care. We evaluated linkage to care (LTC) in a non-urban hepatitis C referral...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810553/ http://dx.doi.org/10.1093/ofid/ofz360.383 |
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author | Sherbuk, Jacqueline McManus, Kathleen Knick, Terry Dillingham, Rebecca |
author_facet | Sherbuk, Jacqueline McManus, Kathleen Knick, Terry Dillingham, Rebecca |
author_sort | Sherbuk, Jacqueline |
collection | PubMed |
description | BACKGROUND: Direct-acting antivirals (DAAs) have simplified and expanded access to Hepatitis C virus (HCV) treatment. Only 17% of the estimated 2.4 million Americans currently infected with HCV have linked to HCV specialty care. We evaluated linkage to care (LTC) in a non-urban hepatitis C referral clinic with a nurse navigator model of care and identified disparities in LTC during the DAA era. METHODS: A single-center retrospective cohort analysis was performed among all patients referred to an infectious diseases HCV clinic between 2014 and 2018. The primary outcome was LTC, defined as attendance at a clinic appointment. A multivariable Poisson regression model estimated associations of patient characteristics with LTC. RESULTS: Among 824 referred patients, 624 (76%) successfully linked to care and 369 (45%) achieved sustained virologic response. The mean age was 48.5 years (SD 13.5 years) and 46% (382 of 824) were uninsured. Common reasons for failure of LTC included no-shows (26.5%), could not be contacted (20.5%) and incarceration (10%). On multivariable analysis, LTC rates were higher among women (incidence rate ratio (IRR) 1.11, 95% CI 1.03–1.20, P = 0.01) and those with cirrhosis (IRR 1.20, 95% CI 1.11–1.30, P < 0.001). Lower rates of LTC were seen for young people (< 40 years old) (IRR 0.88, 95% CI 0.79–0.98, P = 0.02) and uninsured people (IRR 0.85, 95% CI 0.77–0.94, P = 0.002). Race, proximity to care, substance use, and HIV status were not associated with differences in LTC rates. CONCLUSION: In an embedded nurse navigator model of care, a high rate of LTC was achieved despite the prevalence of barriers, including a high uninsured rate. LTC was the biggest drop-off in the cascade. Disparities in LTC based on age, sex, and insurance status are present. Substance use was not associated with differences in LTC, supporting current recommendations to provide treatment to all patients with HCV. No-shows were common, potentially due to lack of reliable contact information or lack of transportation. Qualitative work exploring patients’ experiences leading to failure of LTC would be helpful. Future interventions to improve care could include expanded access to insurance, affordable medical tests, and programs bridging care for incarcerated populations. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6810553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68105532019-10-28 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model Sherbuk, Jacqueline McManus, Kathleen Knick, Terry Dillingham, Rebecca Open Forum Infect Dis Abstracts BACKGROUND: Direct-acting antivirals (DAAs) have simplified and expanded access to Hepatitis C virus (HCV) treatment. Only 17% of the estimated 2.4 million Americans currently infected with HCV have linked to HCV specialty care. We evaluated linkage to care (LTC) in a non-urban hepatitis C referral clinic with a nurse navigator model of care and identified disparities in LTC during the DAA era. METHODS: A single-center retrospective cohort analysis was performed among all patients referred to an infectious diseases HCV clinic between 2014 and 2018. The primary outcome was LTC, defined as attendance at a clinic appointment. A multivariable Poisson regression model estimated associations of patient characteristics with LTC. RESULTS: Among 824 referred patients, 624 (76%) successfully linked to care and 369 (45%) achieved sustained virologic response. The mean age was 48.5 years (SD 13.5 years) and 46% (382 of 824) were uninsured. Common reasons for failure of LTC included no-shows (26.5%), could not be contacted (20.5%) and incarceration (10%). On multivariable analysis, LTC rates were higher among women (incidence rate ratio (IRR) 1.11, 95% CI 1.03–1.20, P = 0.01) and those with cirrhosis (IRR 1.20, 95% CI 1.11–1.30, P < 0.001). Lower rates of LTC were seen for young people (< 40 years old) (IRR 0.88, 95% CI 0.79–0.98, P = 0.02) and uninsured people (IRR 0.85, 95% CI 0.77–0.94, P = 0.002). Race, proximity to care, substance use, and HIV status were not associated with differences in LTC rates. CONCLUSION: In an embedded nurse navigator model of care, a high rate of LTC was achieved despite the prevalence of barriers, including a high uninsured rate. LTC was the biggest drop-off in the cascade. Disparities in LTC based on age, sex, and insurance status are present. Substance use was not associated with differences in LTC, supporting current recommendations to provide treatment to all patients with HCV. No-shows were common, potentially due to lack of reliable contact information or lack of transportation. Qualitative work exploring patients’ experiences leading to failure of LTC would be helpful. Future interventions to improve care could include expanded access to insurance, affordable medical tests, and programs bridging care for incarcerated populations. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6810553/ http://dx.doi.org/10.1093/ofid/ofz360.383 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Sherbuk, Jacqueline McManus, Kathleen Knick, Terry Dillingham, Rebecca 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title | 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title_full | 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title_fullStr | 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title_full_unstemmed | 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title_short | 310. Disparities in Hepatitis C Linkage to Care in the DAA Era: Findings from a Referral Clinic with an Embedded Nurse Navigator Model |
title_sort | 310. disparities in hepatitis c linkage to care in the daa era: findings from a referral clinic with an embedded nurse navigator model |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810553/ http://dx.doi.org/10.1093/ofid/ofz360.383 |
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