![]() ![]() ![]() As a first step to rectifying these issues, we need to collectively recognize their existence as a society and actively work to eliminate them. Systemic biases, including structural racism, sexism, ableism, ageism, and other biases based on sexual orientation, gender identity, and socioeconomic status, contribute substantially to health inequities. Rule 1: Recognize systemic biases and track health disparities. As shown in Fig 1, these rules revolve around 3 principles: (i) improving diversity and equity in science, technology, engineering, and mathematics (STEM) ( Fig 2) (ii) increasing research on underserved areas and populations ( Fig 3) and (iii) considering diverse communities in your research design process ( Fig 4). ![]() In this article, we provide researchers with 10 simple rules in biomedical engineering to improve healthcare equity. As biomedical engineers developing the next generation of healthcare technologies, we are poised to either improve the health disparity landscape or further widen the gap. Other illustrative examples of these harmful oversights are discussed throughout this manuscript. Furthermore, therapeutic dosing has been historically only determined in men whose metabolism is generally faster than that of women, leaving women at a higher risk, and in regard to biomaterial design, researchers have previously not considered differences in skeletal structure between men and women. For example, pulse oximeters, which are used to monitor a patient’s supplemental oxygen needs and guide diagnostic decisions, were found to be 3 times less likely to detect hypoxemia in black patients as compared to white patients. This has resulted in numerous cases of technologies and therapies, be it unknowingly or not, that render the technology either ineffective or hazardous, in particular for women and racially minoritized populations. Given that nondiverse research teams have predominantly led medical device and therapeutic research, it is not surprising that the individual needs of different communities are often not considered in the design and optimization processes. Social determinants and implicit bias are well established as drivers of health disparities however, the impact of biomedical engineers who develop healthcare technologies that further propagate these inequities has only been implicitly stated. Here we focus on healthcare disparities, which refers to differential access, use, and quality of medical care. Health disparities are defined as preventable population-specific differences in the burden of disease, health outcomes, or access to healthcare. The unprecedented nature of the Coronavirus Disease 2019 (COVID-19) pandemic has brought these disparities into the spotlight and reignited the conversation about how to improve health equity in our country. Health disparities have been categorized across race and ethnicity, gender, sexual identity and orientation, disability status or special healthcare needs, and geographic location (rural and urban). Each of these instances illustrates the prevalence of health disparities in diseases, with racial and ethnic minority patients being 1.5 to 2 times more likely than white patients to have major chronic diseases. Women, especially black women, experience higher rates of myocardial infarction or fatal coronary heart disease. For example, babies born to black women in the United States die at more than double the rate of babies born to white women black patients have higher rates of mortality than white patients from many diseases, including inflammatory bowel diseases and cancer American Indians and Alaska Native populations experience increased rates of cardiovascular disease and related risk factors. ” Despite this call to action, there remains a great divide in health outcomes today with statistics that are staggering and unjust. stated, “Of all the forms of inequality, injustice in healthcare is the most shocking and inhumane. In an address at the Convention of the Medical Committee for Human Rights in 1966, Dr. ![]()
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