Improving Diabetes Risk Assessment and Screening in Minority-Predominant Community Health Center Patients

Northwestern University At Chicago, Evanston IL

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Abstract

Project Summary Type 2 diabetes disproportionately affects U.S. racial/ethnic minorities, as evidenced by a higher prevalence of the condition and its complications among Hispanics, blacks, Asian Americans, Pacific Islanders, and Native Americans compared to whites. In October 2015, the U.S. Preventive Services Task Force (USPSTF) released a new recommendation to screen asymptomatic adults who are 40-70 years old and overweight/obese for diabetes and prediabetes (collectively called dysglycemia). These screening criteria are likely to identify proportionately fewer cases of dysglycemia among racial/ethnic minorities, who experience higher risk at younger ages and lower body weights compared to whites. By contrast, the American Diabetes Association (ADA) recommends screening in adults with at least two diabetes risk factors, including non-white race/ethnicity. Screening criteria are based on models that use risk factors to predict the development of dysglycemia. However, existing risk models have limited application in practice because they include data that are not routinely collected, and they do not accurately predict dysglycemia in racial/ethnic minorities. Using data from a national network of community health centers whose patients are predominantly racial/ethnic minorities, this timely research will investigate the assessment of diabetes risk and the effectiveness of alternate screening criteria. The Alliance of Chicago Community Health Services (Alliance) is a national data warehouse for over 200 community health centers, which links sociodemographic, laboratory, and healthcare utilization data from the electronic health records (EHR) of over 800,000 patients. Using longitudinal Alliance data from 2006 to 2015, we will compare the performance of three different approaches for predicting dysglycemia, based on: 1) USPSTF criteria; 2) ADA criteria; and 3) criteria from a novel risk prediction model we will develop using the same EHR data. In a second aim, we will estimate and compare the costs and short- term cost-effectiveness of screening based on the same sets of criteria. This economic analysis is essential to promote the uptake of optimal diabetes screening approaches in practice. Findings from this study can be used to improve diabetes screening recommendations to better identify high-risk individuals, especially racial/ethnic minorities. This study may therefore help reduce racial/ethnic disparities by detecting dysglycemia earlier in these groups, so that prevention and treatment strategies can be initiated. In addition, this study will lead to future research that tests novel interventions for screening, diagnosing, and treating dysglycemia, and examines the long-term cost effectiveness of screening approaches. Our multidisciplinary team has extensive expertise in the content areas and methods needed to successfully conduct the proposed secondary data analysis, and then investigate the application of study findings in practice. This study is timely in its examination of new diabetes screening criteria; novel in its inclusion of a large, minority-predominant patient sample; and significant in its potential to maximize both population health and health equity in diabetes.