The NYC Department of Health implemented a patient navigation program, Check Hep C, to address patient and provider barriers to HCV care and potentially lifesaving treatment. Services were delivered at two clinical care sites and two sites that linked patients to off-site care. Working with a multidisciplinary care team, patient navigators provided risk assessment, health education, treatment readiness and medication adherence counseling, and medication coordination. Between March 2014 and January 2015, 388 participants enrolled in Check Hep C, 129 (33%) initiated treatment, and 119 (91% of initiators) had sustained virologic response (SVR). Participants receiving on-site clinical care had higher odds of initiating treatment than those linked to off-site care. Check Hep C successfully supported high-need participants through HCV care and treatment, and SVR rates demonstrate the real-world ability of achieving high cure rates using patient navigation care models.

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Cardiovascular disease (CVD), the leading cause of death in the United States, is impacted by neighborhood-level factors including social deprivation. To measure the association between social deprivation and CVD mortality in Harris County, Texas, global (Ordinary Least Squares (OLS) and local (Geographically Weighted Regression (GWR)) models were built. The models explored the spatial variation in the relationship at a census-tract level while controlling for age, income by race, and education. A significant and spatially varying association (p < .01) was found between social deprivation and CVD mortality, when controlling for all other factors in the model. The GWR model provided a better model fit over the analogous OLS model (R2 = .65 vs. .57), reinforcing the importance of geography and neighborhood of residence in the relationship between social deprivation and CVD mortality. Findings from the GWR model can be used to identify neighborhoods at greatest risk for poor health outcomes and to inform the placement of community-based interventions.

The community-based model successfully identified persons with HCV infection and linked a large proportion to care. The small number of patients initiating hepatitis C treatment in the program identified the need for patient navigation in high-risk populations. Results can be used to inform screening and linkage-to-care strategies and to support the execution of hepatitis C screening recommendations.

Deaths attributable to hepatitis C (HCV) infection are increasing in the USA even as highly effective treatments become available. Neighborhood-level inequalities create barriers to care and treatment for many vulnerable populations. We seek to characterize citywide trends in HCV mortality rates over time and identify and describe neighborhoods in New York City (NYC) with disproportionately high rates and associated factors. We used a multiple cause of death (MCOD) definition for HCV mortality. Cases identified between January 1, 2006, and December 31, 2014, were geocoded to NYC census tracts (CT). We calculated age-adjusted HCV mortality rates and identified spatial clustering using a local Moran's I test. Temporal trends were analyzed using joinpoint regression. A multistep global and local Poisson modeling approach was used to test for neighborhood associations with sociodemographic indicators. During the study period, 3697 HCV-related deaths occurred in NYC, with an average annual percent increase of 2.6% (p = 0.02). The HCV mortality rates ranged from 0 to 373.6 per 100,000 by CT, and cluster analysis identified significant clustering of HCV mortality (I = 0.23). Regression identified positive associations between HCV mortality and the proportion of non-Hispanic black or Hispanic residents, neighborhood poverty, education, and non-English-speaking households. Local regression estimates identified spatially varying patterns in these associations. The rates of HCV mortality in NYC are increasing and vary by neighborhood. HCV mortality is associated with many indicators of geographic inequality. Results identified neighborhoods in greatest need for place-based interventions to address social determinants that may perpetuate inequalities in HCV mortality.