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The meaning of race in medicine is believed to be dichotomized. On one hand, ethnicity sheds light on different genetic pools within a population. On the other hand, medicine is thought to have a long history of being racist and there has never been sufficient evidence to indicate one’s ethnic background may be a reliable indicator for clinical differences. For example, the US Food and Drug Administration (FDA) approved a race-based medication – BiDil in year 2005. BiDil is a combination of two generic drugs – hydralazine and isosorbide dinitrate marketed to minimize heart failure among individuals who identified themselves as black.
Nevertheless, critics doubted the exclusivity of BiDil by pointing out that “self-proclaimed” racial identity is socially constructed; it may differ from one’s biological race and thus influence individuals’ responses to the drug. Besides, the only clinical trial involving African American patients did not compare the drug’s effects on black patients’ and non-black patients. A separate study involving white, Californian and other heart patients with no specific mention on their race, ethnicity and geographical location found that BiDil works on them too.
What has the new study found?
Even though the impact of race and human genetics on medicine are better understood over the years, all these still did not lead us to a clearer guideline and better practice. Scientists continue to make amendments to their diagnostic algorithms and modify the outputs based on race and ethnicity. Recently, researchers from Massachusetts General Hospital, Harvard Medical School, Harvard University and NYU Langone Medical Center had compiled an incomplete list of race-adjusted algorithms and explore whether they amplify race-based health inequities.
Cardiology was one of the sub-specialties the researchers had looked into. The Guidelines-Heart Failure Risk Score devised by the American Heart Association (AHA) forecasts patients’ mortality as they were admitted into the hospitals. Any patient who self-identified as “non-black” are given three additional points on the risk score and this makes black patients to be at a lower risk. AHA did not explain the rationale adaptation but advised fellow clinicians to use the risk score as they make cardiology referrals or allocating healthcare resources.
Because the risk score inherently regards black patients as having lower risks, naturally they were denied from specialist service. This was reflected in a 2019 study whereby black and Latinx patients with heart failure presented at an emergency department in Boston were less likely that their white counterpart to be admitted to a cardiology service. Furthermore, the Society of Thoracic Surgeons estimates patients’ mortality and risks of complications during surgery. Race and ethnicity were factored into these estimates because of “observed differences”.
Again, exactly what these “observed differences” are remain unknown but the estimate will yield 0.492% for a coronary artery bypass in a low-risk white patient and an 20% increase to 0.586% shall the patient is black or African American. Interestingly, changing to other race and ethnicity does not increase the estimated risk of death. The researchers also did similar analyses in other sub-specialties including Oncology, Obstetrics, Urology, Nephrology, Endocrinology and Pulmonology. All findings were reported on the New England Journal of Medicine (NEJM) last Wednesday (17 June).
How can this be improved?
Altogether, researchers examined 13 algorithms and analyzed the rationale for considering race and ethnicity. They realized when one carefully traces the rationale to the origin, it often reflects a biased data or flawed assumption that race is the main culprit to certain medical outcomes. Developers failed to consider other factors alongside race, such as socioeconomic status, discrimination or accessibility to care, may also have contributed to the outcomes.
David Shumway Jones of Harvard Medical School and the Principal Investigator of the study told Stat, “Modern tools of epidemiology and statistics could sort that out and show that much of what passes for race is actually about class and poverty”. While considering race and ethnicity may exacerbate inequities, it may help to address the problem in certain cases. Hence, developers ought to take additional care in the way they train their algorithms and using them in clinical decision making.
At the beginning of the month, Department of Global Health at University of Washington had declared to exclude race in the calculation of kidney functions. Likewise, hospitals in Boston and San Francisco will also stop adjusting scores in their calculations of kidney functions to make black patients appear better. Jones believe most of these racist algorithms were created unintentionally. “Well-meaning individuals acting without racist intent can still produce work with racist consequences such as redirecting medical resources from one group to another”. He hopes that the paper will encourage the medical community to reflect upon their decisions and practice.