Surveillance of Congenital Heart Defects Among Children, Adolescents, and Adults

surveillance system, electronic health records, administrative data (e.g., Medicaid/Medicare, hospital discharge), or other sources available to funding recipients. Background: Congenital heart defects (CHD) affect about 1% of all births in the United States, and are a leading cause of birth defect-associated infant mortality, morbidity, and healthcare costs. Improvements in early detection and treatment of CHD and consequently in survival have resulted in many people, including those affected by a severe CHD, living into adolescence and adulthood. An estimated two million persons in the U.S. are living with a CHD, including over one million adults; about 12% of these affected adults have a severe CHD. Most current efforts to conduct population-based surveillance of CHD have focused on monitoring newborns. However, little data exist on the descriptive epidemiology of CHD beyond early childhood in the U.S. Despite the public health burden, the lack of population-based surveillance precludes reliable data on people with CHD, their survival, healthcare utilization, and characteristics associated with long-term outcomes. Through this surveillance activity, these data will be assessed, enabling and informing efforts to improve the health and well-being of people with CHD. Objectives: Component A objectives include: (1) assess survival, comorbidities, healthcare utilization during the period 2021-2023, and characteristics associated with long-term outcomes among people with CHD; (2) assess health equity among people with CHD; (3) examine state and national healthcare policies that have an impact on people with CHD; (4) examine COVID-19 and related data such as health care utilization during the pandemic among people with CHD; and (5) work with local/state partners to use site-specific CHD data. Component B objectives include: (1) develop and refine a machine learning algorithm for the surveillance data collected through Component A; and (2) apply this machine learning algorithm to data collected from all recipients funded through Component A.