Diabetes is a common chronic disease in children and adolescents under age of 18 years. In the recent two decades, both the prevalence and incidence of type 1 diabetes (T1D) and type 2 diabetes (T2D) have been increasing considerably among US children and adolescents. T2D now accounts for ~15% of diabetes cases diagnosed in childhood and adolescence. The SEARCH for Diabetes in Youth study is the only ongoing multisite surveillance study of T1D and T2D in US children and adolescents. The SEARCH study is a population-based registry, which is a more expensive, more labor-intensive, and slower surveillance method compared with a surveillance system using electronic health records (EHRs). EHR algorithms have shown great potential in identifying diabetes cases. This study will analyze both structured EHR data (e.g., diagnosis codes, medications, and laboratory results) and unstructured clinical notes. We will apply expert knowledge, machine learning, and natural language processing to develop the best algorithms for identifying prevalent and incident T1D and T2D cases. The primary objective of this study is to establish an EHR-based surveillance system for monitoring the burden of T1D and T2D in US children and adolescents. We will collaborate with 3 EHR research networks from the National Patient-Centered Clinical Research Network (PCORnet), covering ~3 million racially, ethnically, and socioeconomically diverse children and adolescents from 4 states (IL, LA, NY, and TX) in 3 Census regions. The patient populations in this study are roughly representative of the source populations in the catchment areas.
The specific aims of this study are 1) to estimate the prevalence of T1D and T2D in US children and adolescents by age, sex, race/ethnicity, and geographic region in 2019; 2) to estimate the incidence of T1D and T2D in US children and adolescents by age, sex, race/ethnicity, and geographic region in 2019; 3) to estimate 10-year trends in the prevalence and incidence of T1D and T2D in US children and adolescents by age, sex, race/ethnicity, and geographic region, 2014-2023; and 4) to compare the prevalence and incidence of diabetes by type, as well as temporal trends, in US children and adolescents with those in children and adolescents from other countries and regions. This study is innovative because it will leverage EHRs for surveillance (more efficient and cost-effective than registries and surveys), use advanced statistical approaches (e.g., machine learning and natural language processing), estimate a denominator using patient zip codes, build flexibility into the surveillance methods according to local availability of clinical notes, and use a 2-staged sampling approach to improve chart review efficiency. All 4 states in this study do not have an active diabetes surveillance system for children and adolescents and are not covered by the SEARCH study. This study will advance our understanding of the geographic, age, sex, and racial/ethnic differences in the burden of T1D and T2D in US children and adolescents. The obtained surveillance data will help identify and prioritize subpopulations for prevention of diabetes and related comorbidities to reduce health disparities.
The burden of type 1 and type 2 diabetes has been increasing considerably among US children and adolescents. A population-based registry, which is expensive and labor-intensive, has provided estimates for the prevalence and incidence of type 1 and type 2 diabetes in children and adolescents from limited geographic regions in the US. This study will build an efficient and cost-effective multisite surveillance system using electronic health records covering several other geographic regions, to estimate the prevalence, incidence, and trends of type 1 and type 2 diabetes in US children and adolescents according to age, sex, race/ethnicity, and geographic region.
