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Brief Review: Racial and Ethnic Disparities in Cardiovascular Care with a Focus on Congenital Heart Disease and
Joseph Bayne1, Jonah Garry2, Michelle A Albert3
1Division of Cardiology, Department of Medicine, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143-0474, USA. Joseph.bayne@ucsf.edu.
Insights
Racial and ethnic minorities face worse outcomes in adult congenital heart disease. Artificial intelligence may worsen disparities if not developed with diverse data, necessitating inclusive research for equitable care.
Area of Science:
- Healthcare disparities
- Cardiovascular health
- Medical artificial intelligence
Background:
- Racial and ethnic minorities, particularly Black and Hispanic groups, exhibit higher risks and poorer outcomes for congenital heart disease (CHD).
- These populations are significantly underrepresented in major clinical trials, limiting the generalizability of findings.
- Emerging technologies like artificial intelligence (AI) in precision medicine promise personalized treatment but risk perpetuating bias due to data limitations.
Purpose of the Study:
- To review racial and ethnic disparities in healthcare, focusing on adult congenital heart disease (CHD).
- To examine the intersection of AI and precision medicine with health equity.
- To highlight under-addressed areas concerning diverse populations in cardiovascular research.
Main Methods:
- Literature review focusing on recent studies and data concerning racial and ethnic disparities in healthcare.
- Analysis of the role of artificial intelligence (AI) and precision medicine in cardiovascular care.
- Examination of data representation and algorithmic bias in medical research.
Main Results:
- Racial and ethnic minorities experience increased morbidity and mortality from adult congenital heart disease.
- AI applications in precision medicine can amplify existing racial and ethnic biases if algorithms are trained on non-diverse datasets.
- Insufficient data from diverse populations hinders the accurate application of AI for equitable cardiovascular treatment.
Conclusions:
- Urgent need for dedicated resources to engage diverse populations in clinical and population-based studies.
- Efforts must focus on eliminating racial and ethnic healthcare disparities in adult congenital heart disease.
- Equitable development and utilization of artificial intelligence are crucial for improving health outcomes across all populations.
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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