Population-based estimates of the prevalence of children with congenital heart disease and associated comorbidities

Abstract

AbstractBackgroundCongenital heart defects (CHD) are the most common birth defects and are estimated to affect almost 1% of births annually in the US. CHDs are the leading cause of infant mortality associated with birth defects and can result in chronic disability, morbidity and increased healthcare costs. Most CHD prevalence estimates rely on data from population-based birth defects surveillance systems and these estimates are inconsistent due to varied definitions. It is therefore important to derive high-quality, population-based estimates of the prevalence of CHD to help care for this vulnerable population.MethodsWe performed a descriptive, retrospective 8-year analysis using all payer claims data (APCD) from Colorado (CO) from 2012 - 2019. Children with CHD were identified by applying ICD-9 and ICD-10 diagnoses codes from the American Heart Association-American College of Cardiology (AHA-ACC) harmonized cardiac codes. We included children with CHD <18 years of age who resided in CO, had a documented zip code, and had at least one healthcare claim. CHD type was categorized as simple, moderately complex and complex disease. Association with comorbid conditions and genetic diagnoses were analyzed using chi-square test. We used direct standardization to calculate adjusted prevalence rates, controlling for age, sex, primary insurance provider and urban-rural residence.ResultsWe identified 1,566,328 children receiving care in CO from 2012 – 2019. Of those, 30,512 children had at least one CHD diagnosis, comprising 1.9% (95% CI: 1.93 – 1.97) of the pediatric population. Over half of the children with CHD also had at least one complex chronic condition and 11% had a genetic diagnosis.ConclusionThe current study is the first population-level analysis of pediatric CHD in the US. Our study found a higher CHD prevalence than in previously reported studies and a high comorbidity burden. These findings can inform initiatives to improve screening, treatment and planning of care for this complex population.