Effectiveness of a Risk Screener in Identifying Hepatitis C Virus in a Primary Care Setting.

Mari-Lynn Drainoni, Elisa A. Koppelman, and Cindy L. Christiansen are with the Department of Health and Policy Management, Boston University School of Public Health, Boston, MA. Alain H. Litwin is with the Division of General Internal Medicine, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY. Bryce D. Smith and Cindy M. Weinbaum are with the Division of Viral Hepatitis, National Center for HIV/Viral Hepatitis/STD/TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA. M. Diane McKee is with the Department of Family Medicine, Albert Einstein College of Medicine and Montefiore Medical Center. Allen L. Gifford is with the VA HIV/Hepatitis Quality Enhancement Research Initiative, Edith Nourse Rogers Memorial Veterans Administration Hospital, Bedford, MA. William N. Southern is with the Division of Hospital Medicine, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center.
American Journal of Public Health (Impact Factor: 4.23). 09/2012; 102(11):e115-e121. DOI: 10.2105/AJPH.2012.300659
Source: PubMed

ABSTRACT Objectives. We evaluated an intervention designed to identify patients at risk for hepatitis C virus (HCV) through a risk screener used by primary care providers. Methods. A clinical reminder sticker prompted physicians at 3 urban clinics to screen patients for 12 risk factors and order HCV testing if any risks were present. Risk factor data were collected from the sticker; demographic and testing data were extracted from electronic medical records. We used the t test, χ(2) test, and rank-sum test to compare patients who had and had not been screened and developed an analytic model to identify the incremental value of each element of the screener. Results. Among screened patients, 27.8% (n = 902) were identified as having at least 1 risk factor. Of screened patients with risk factors, 55.4% (n = 500) were tested for HCV. Our analysis showed that 7 elements (injection drug use, intranasal drug use, elevated alanine aminotransferase, transfusions before 1992, ≥ 20 lifetime sex partners, maternal HCV, existing liver disease) accounted for all HCV infections identified. Conclusions. A brief risk screener with a paper-based clinical reminder was effective in increasing HCV testing in a primary care setting.

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    ABSTRACT: Background Hepatitis C virus (HCV) infection is unidentified in an estimated 40%–85% of infected adults. Surveillance and modeling data have found significant increases in HCV-associated morbidity and mortality. Purpose To compare two HCV antibody (anti-HCV) testing strategies based on (1) elevated alanine aminotransferase levels (ALT) and (2) a birth cohort approach for people born during 1945–1965. Methods Data from 19,055 adults aged 20–70 years who completed the National Health and Nutrition Examination Survey in 1999–2008 were analyzed in 2013. Two independent models were evaluated, based on membership in the 1945–1965 birth cohort or elevated ALT, to compare the number of identified anti-HCV-positive (anti-HCV+) individuals; proportion of total identified cases; and the number of people that would be tested using either strategy. Results The prevalence of anti-HCV among adults aged 20–70 years was estimated at 2.0% (95% CI=1.8%, 2.3%), representing about 3.6 million people. The birth cohort strategy would result in testing about 85.4 million people and identifying nearly 2.8 million anti-HCV+ people with a sensitivity of 76.6%. The ALT strategy would test about 21.5 million adults and identify approximately 1.8 million anti-HCV+ people with a sensitivity of 50.0%. Implementing both strategies concurrently would identify 87.3% of anti-HCV+ adults. Conclusions The birth cohort strategy, which is recommended by both the CDC and the U.S. Preventive Services Task Force, would identify 1 million more anti-HCV+ people than the elevated ALT approach. Concurrent implementation would identify an even larger number of individuals ever infected.
    American Journal of Preventive Medicine 08/2014; 47(3):233-241. DOI:10.1016/j.amepre.2014.05.011 · 4.28 Impact Factor


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May 31, 2014