Why the study?
Diverse racial and ethnic groups with congenital heart disease have worse outcomes but remain underrepresented in clinical trials, while artificial intelligence in precision medicine risks exacerbating bias due to inadequate diverse data.
This review highlights the critical need for diverse representation in clinical trials and AI algorithm development to prevent exacerbating existing racial and ethnic disparities in congenital heart disease care.
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Disparities in congenital heart disease outcomes warrant attention; leaves open whether diverse AI datasets can mitigate bias without prospective validation.
PURPOSE OF REVIEW: This is a brief review about racial and ethnic disparities in healthcare with focused attention to less frequently covered areas in the literature such as adult congenital heart disease, artificial intelligence, and precision medicine. Although diverse racial and ethnic populations such as Black and Hispanic groups are at an increased risk for CHD and have worse related outcomes, they are woefully underrepresented in large clinical trials. Additionally, although artificial intelligence and its application to precision medicine are touted as a means to individualize cardiovascular treatment and eliminate racial and ethnic bias, serious concerns exist about insufficient and inadequate available information from diverse racial and ethnic groups to facilitate accurate care. This review discusses relevant data to the aforementioned topics and the associated nuances. RECENT FINDINGS: Recent studies have shown that racial and ethnic minorities have increased morbidity and mortality related to congenital heart disease. Artificial intelligence, one of the chief methods used in precision medicine, can exacerbate racial and ethnic bias especially if inappropriate algorithms are utilized from populations that lack racial and ethnic diversity. Dedicated resources are needed to engage diverse populations to facilitate participation in clinical and population-based studies to eliminate racial and ethnic healthcare disparities in adult congenital disease and the utilization of artificial intelligence to improve health outcomes in all populations.
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Bayne et al. (2023) studied this question.
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