Division of Cardiology, Department of Medicine, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143-0474, USA.
Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
Curr Atheroscler Rep. 2023 May;25(5):189-195. doi: 10.1007/s11883-023-01093-3. Epub 2023 Mar 25.
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 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.
本文简要综述了医疗保健领域的种族和民族差异,并重点关注文献中较少涉及的领域,如成人先天性心脏病、人工智能和精准医学。尽管黑人及西班牙裔等不同种族和民族群体患 CHD 的风险增加,且相关预后更差,但他们在大型临床试验中的代表性严重不足。此外,尽管人工智能及其在精准医学中的应用被吹捧为实现心血管治疗个体化和消除种族和民族偏见的一种手段,但人们严重关切的是,缺乏来自不同种族和民族群体的充足且适当的信息,难以实现准确的治疗。本文讨论了与上述主题相关的、有细微差别的现有数据。
最近的研究表明,少数族裔的先天性心脏病发病率和死亡率更高。人工智能是精准医学中主要使用的方法之一,如果使用来自缺乏种族和民族多样性的人群的不合适算法,它可能会加剧种族和民族偏见。需要专门的资源来让不同人群参与临床和基于人群的研究,以消除成人先天性疾病中的种族和民族医疗保健差异,并利用人工智能改善所有人群的健康结果。