Predictors of linkage to care for a nontargeted emergency department hepatitis C screening program

•EDs play a crucial role in Hepatitis C screening and linkage to care.•Predictors of linkage to care failure may be used to enhance linkage efforts.•Predictors of linkage failure were identified for 1674 patients with Hepatitis C.•Young age, white race, homelessness, substance use, & mental illn...

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Published inThe American journal of emergency medicine Vol. 38; no. 7; pp. 1396 - 1401
Main Authors Blackwell, Joshua A., Rodgers, Joel B., Franco, Ricardo A., Cofield, Stacey S., Walter, Lauren A., Galbraith, James W., Hess, Erik P.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.07.2020
Elsevier Limited
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Summary:•EDs play a crucial role in Hepatitis C screening and linkage to care.•Predictors of linkage to care failure may be used to enhance linkage efforts.•Predictors of linkage failure were identified for 1674 patients with Hepatitis C.•Young age, white race, homelessness, substance use, & mental illness increased risk.•Medical comorbidities and HIV co-infection protected against linkage failure. We implemented a nontargeted, opt-out HCV testing and linkage to care (LTC) program in an academic tertiary care emergency department (ED). Despite research showing the critical role of ED-based HCV testing programs, predictors of LTC have not been defined for patients identified through the nontargeted ED testing strategy. In order to optimize health outcomes for patients with HCV, we sought to identify predictors of LTC failure. This was a retrospective cohort study of adult patients who were tested for HCV in the ED between August 2015 and September 2018 and were confirmed to have chronic HCV infection through RNA testing. We used logistic regression to assess the relationship between candidate predictors and the primary outcome, LTC failure, which was defined as a patient not being seen by an HCV treating provider after discharge from the ED. Of 53,297 patients tested, 1,674 (3.1%) had HCV on confirmatory testing, and 355 (21%) linked to care. Predictors of LTC failure included younger age (OR 0.96, 95% CI 0.95–0.97), white race (OR 1.65, 95% CI 1.23–2.22), homelessness (OR 1.91, 95% CI 1.19–3.08), substance use (OR 1.77, 95% CI 1.34–2.34), and comorbid psychiatric illness (OR 2.16, 95% CI 1.59–2.94). Patients with significant medical comorbidities (OR 0.57, 95% CI 0.41–0.78) or HIV co-infection (OR 0.11, 95% CI 0.03–0.46) were less likely to experience LTC failure. One in five HCV-infected patients identified by ED-based nontargeted testing successfully linked to an HCV treating provider. Predictors of LTC failure may guide the development of targeted interventions to improve LTC success.
Bibliography:AJEM Author Contribution Statement
Joshua Blackwell: Conceptualization, Methodology, Formal analysis, Writing – Original Draft, Funding acquisition. Joel Rodgers: Conceptualization, Investigation, Data Curation, Project administration. Ricardo Franco: Conceptualization, Methodology, Writing – Review & Editing. Stacey Cofield: Methodology, Formal analysis, Writing – Review & Editing. James Galbraith: Investigation, Project administration, Writing – Review & Editing. Lauren Walter: Writing – Review & Editing. Erik Hess: Conceptualization, Methodology, Formal analysis, Investigation, Project administration, Visualization, Supervision, Writing – Original Draft, Funding acquisition
SSC assisted with statistical analyses and edited related portions of the manuscript.
JWG assisted with data interpretation and contributed to the writing of the manuscript.
LAW assisted with data interpretation and contributed to the writing of the manuscript.
JAB developed the study’s concept and design, conducted data analyses and interpretation, and wrote the greater portion of the manuscript.
JBR was heavily involved in study design and in the acquisition and organization of data.
RAF assisted with data interpretation and contributed to the writing of the manuscript.
EPH served as the PI for the project, guiding the study design, data analysis and interpretation, and drafting of the manuscript.
Author contributions
ISSN:0735-6757
1532-8171
DOI:10.1016/j.ajem.2019.11.034