Background:The Community Health Applied Research Network, funded by the Health Resources and Services Administration, is a research network comprising 18 Community Health Centers organized into four Research Nodes (each including an academic partner) and a data coordinating center. The network represents more than 500,000 diverse safety net patients across 11 states.Objective:The primary objective of this paper is to describe the development and implementation process of the CHARN data warehouse.Methods:The methods involved regulatory and governance development and approval, development of content and structure of the warehouse and processes for extracting the data locally, performing validation, and finally submitting data to the data coordinating center.Progress to Date:Version 1 of the warehouse has been developed. Tables have been added, the population and the years of electronic health records (EHR) have been expanded for Version 2.Conclusions:It is feasible to create a national, centralized data warehouse with multiple Community Health Center partners using different EHR systems. It is essential to allow sufficient time: (1) to develop collaborative, trusting relationships among new partners with varied technology, backgrounds, expertise, and interests; (2) to complete institutional, business, and regulatory review processes; (3) to identify and address technical challenges associated with diverse data environments, practices, and resources; and (4) to provide continuing data quality assessments to ensure data accuracy.

ObjectiveColorectal cancer (CRC) screening rates remain lower among some racial/ethnic groups and individuals with low income or educational attainment who are often cared for within community health centers (CHCs). We surveyed clinicians in a network of CHCs to understand their attitudes, practice patterns, and perceived barriers to CRC screening.MethodsA clinician survey was conducted in 2013 within the Community Health Applied Research Network (CHARN).Results180 clinicians completed the survey (47.9% response rate). Participants had an average of 11.5 (SD: 9.8) years in practice, 62% were female, and 57% were physicians. The majority of respondents somewhat agreed (30.2%) or strongly agreed (57.5%) that colonoscopy was the best screening test. However, only 15.8% of respondents strongly agreed and 32.2% somewhat agreed that colonoscopy was readily available for their patients. Fecal immunochemical testing (FIT), a type of fecal occult blood test (FOBT), was viewed less favorably; 24.6% rated FIT as very effective.ConclusionsAlthough there are no data showing that screening colonoscopy is superior to FIT, CHC clinicians believe colonoscopy is the best CRC screening test for their patients, despite the high prevalence of financial barriers to colonoscopy. These attitudes could be due to lack of knowledge about the evidence supporting long-term benefits of fecal occult blood testing (FOBT), lack of awareness about the improved test characteristics of FIT compared to older guaiac-based FOBT, or the absence of systems to ensure adherence to regular FOBT screening. Interventions to improve CRC screening at CHCs must address clinicians' negative attitudes towards FIT.

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Objective: Recent research demonstrates an increased need to understand the contribution of social determinants of health (SDHs) in shaping an individual's health status and outcomes. We studied patients with diabetes in safety-net centers and evaluated associations of their disease complexity, demographic characteristics, comorbidities, insurance status, and primary language with their HbA1c level over time.Methods: Adult patients with diabetes with at least 3 distinct primary care visits between January 1, 2006, and December 31, 2013, were identified in the CHARN data warehouse. These patients were categorized into 4 groups: those without a diagnosis of cardiovascular disease (CVD) or depression; those with CVD but not depression; those with depression but not CVD; and those with CVD and depression. Charlson score; demographic characteristics such as age, sex, and race/ethnicity; and SDHs such as primary language and insurance status were used as predictors. The outcome measure was HbA1c. Hypothesis testing was conducted using 3-level hierarchical linear models.Results: Baseline HbA1c differed significantly across the 4 diabetes groups and by race/ethnicity. The amount of HbA1c change over time differed by insurance status. Patients who were continuously insured tended to have lower baseline HbA1c and a smaller increase. Chinese-speaking patients tended to have lower baseline HbA1c but a larger increase over time compared with English speakers. There were various unexpected associations: compared with the diabetes-only group, mean HbA1c tended to be lower among the other more complex groups at baseline; women tended to have lower measures at baseline; older age and higher Charlson scores were associated with lower HbA1c.Conclusions: There is still unexplained variability relating to both baseline HbA1c values and change over time in the model. SDHs, such as insurance status and primary language, are associated with HbA1c, and results suggest that these relationships vary with disease status among patients with diabetes in safety-net centers. It is important to recognize that there are complex relationships among demographic and SDH measures in complex patients, and there is work to be done in correctly modeling and understanding these relationships. We also recommend prioritizing the collection of SDH and enabling services data for safety-net patients that would be instrumental in conducting a more comprehensive study. 3-7 Interest in studying and describing SDHs has increased over the past few decades, 8 -10 and it is clear that SDHs are associated with suboptimal health status or poor health-related outcomes, 11 such as higher rates of mental disorders and medical conditions. 12 In a meta-analysis conducted by Lorant and colleagues, 13 people with a low socioeconomic status were 1.8 times more likely to report being depressed than were people with higher status. Lett et al 14 also found that low social support was associated with a 1.5-to 2-times increased the risk of developing coronary heart disease or ex...

Colorectal cancer screening varies substantially across CHCs. Electronic health record data can validly measure CRC screening, but repeated assessments of programming accuracy are required. Community health centers may need support to measure quality using EHR data and increase screening.