Liver, Pancreas and Biliary TractPrimary care-based interventions are associated with increases in hepatitis C virus testing for patients at risk☆
Introduction
An estimated 3.2 million persons are chronically infected with the hepatitis C virus (HCV) in the U.S. Although the prevalence of HCV infection is estimated at 1.6% in the U.S. [1], urban clinic populations may have an HCV prevalence as high as 8% [2], [3]. HCV infection causes approximately 40% of chronic liver disease [4] and the majority of cases of hepatocellular carcinoma [5], and we can expect that there will be up to a 4-fold increase in HCV-related deaths over the next 20 years [6], [7], [8]. Effective treatment is available for HCV which can lead to long-term remission of disease and decreased liver-related mortality rates, but approximately 50% of patients are not aware that they are infected [9], [10]. Although the Institute of Medicine (IOM) has recommended increased HCV testing [11], optimal testing strategies have not been described [12]. The aim of this analysis is to evaluate two interventions designed to increase HCV testing for patients at risk for HCV infection and disease.
There are several potential screening strategies which may be used when designing HCV testing programs. The Centers for Disease Control and Prevention and other organizations have recommended HCV testing for persons with an increased risk of infection such as persons who inject drugs [4], [13], [14]. Risk-based approaches to testing may be efficient, because patients with identified risks such as injection drug use have a much higher prevalence of HCV infection (60–90%) [15] than the general population (1.6%) [1]. However, risk-based screening has been limited because primary care providers often do not ask patients about HCV risk factors, testing is rarely initiated based on physician-identified risks, and patients are often reticent to disclose stigmatized risk behaviors [16], [17].
Another approach to HCV screening is to identify a group of patients at higher risk without asking about stigmatized risk behaviors. Americans born between 1945–1964 are more likely to be HCV-infected than those in other age groups [1], and we have established at the three study clinics that HCV infection is nearly 4 times more likely in this high-prevalence birth cohort compared to patients outside of this birth cohort [3]. Approximately 76% of HCV-infected Americans were born between 1945–1964, and Americans born between 1945 and 1964 have a anti-HCV prevalence as high as 4.3% [1]. Therefore, another strategy is to test all patients born between 1945 and 1964.
The Hepatitis C Assessment and Testing Project (HepCAT) was a prospective evaluation funded by CDC via AHRQ ACTION of two serial community-based interventions designed to increase rates of HCV testing of at-risk or high-prevalence patients in urban primary care clinics from rates seen during baseline testing (baseline period). The first intervention (risk-based screener intervention) prompted physicians with a clinical reminder sticker in the progress note to ask whether a patient had specific HCV-related risks and to order HCV tests based on the presence of these risks. The second intervention (birth cohort intervention) prompted physicians with a clinical reminder sticker in the progress note to order HCV tests on all patients born within a high-prevalence birth cohort (1945–1964). We hypothesized that both interventions would be associated with an increase in testing of patients for HCV.
Section snippets
Study design
The study was a serial cross-sectional evaluation of two community-based interventions. We evaluated HCV testing and positivity rates during a baseline and two subsequent intervention periods. We used electronic medical record (EMR) data to examine the associations of interventions with HCV testing rates overall and within at-risk sub-groups.
Study setting
The study was conducted at three community-based primary care (family medicine or internal medicine) clinics affiliated with Montefiore Medical Center, a
Study population
The baseline cohort (n = 6591), the risk screener cohort (n = 8981), and the birth cohort (n = 10,165) included all adult patients (at least 18 years of age) who had not been tested for anti-HCV in the past (since 1997), and who made at least one primary care visit during the baseline, risk screener intervention, or birth cohort intervention periods respectively.
Demographic and clinical information for the overall study population are summarized in Table 1. The mean age was 47.8 years (SD = 17.7). The
Discussion
We demonstrated that implementation of a clinical reminder sticker as the backbone of a multi-component intervention was associated with a significant increase of anti-HCV testing for a population of at-risk and high prevalence patients in three large urban primary care clinics. Both the risk-based screener and birth cohort interventions were associated with significantly increased rates of HCV testing overall, and among those with HCV-related risks. In the clinic with the lowest rate of
Future directions
Future studies could investigate the effect of combining our strategies by adding the birth cohort question to the risk-based screener. Risk-based screening will allow identification of younger patients who are less likely to have comorbidities and contraindications to HCV treatment, and have a better chance of SVR. Conversely, birth cohort screening will allow identification of older patients who are more likely to urgently need antiviral treatment to prevent decompensated cirrhosis,
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The project was funded by the Agency for Health Care Research and Quality (AHRQ) and the Centers for Disease Control and Prevention via the AHRQ ACTION initiative to Boston University, contract HHSA2902006000012 T0#4. The content is solely the responsibility of the authors and does not necessarily represent the official views of AHRQ. The study and investigators were also funded by the Clinical Investigation Core of the Center for AIDS Research at the Albert Einstein College of Medicine and Montefiore Medical Center, funded by the National Institutes of Health NIH P30 AI51519, NIDA K23 DA022454, and the CTSA Grant UL1 RR025750 and KL2 RR025749 and TL1 RR025748 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH).