The intersection of race and health is complicated. But the emerging picture seems to be that health conditions that affect Black people disproportionately—such as kidney disease and maternal deaths—may have their roots not only in poverty or access to health care, but also in preconceived and unproven notions of race that affect medical decision-making. (emphases mine throughout)
In one sense, that’s a painful reminder of the pervasive extent of racism in our institutions. Right now we are watching Black people bearing a disproportionate burden of COVID-19—in part because of their preexisting conditions.
In another sense, it offers hope that by confronting and changing those preconceived notions, we can actually change health outcomes.
Of course we also need to improve our inequitable hodgepodge of a health care system and address issues related to poverty—such as food deprivation and environmental injustices (eg, housing in toxic areas).
But at the same time, we should be educating clinicians to take a new look at their decision-making when treating each specific Black patient–indeed, all minority patients.
As far as geneticists are concerned, to the extent that there are racial groups, there is greater genetic variation within the specific groups than there is between groups. That means that when the specialty societies that design algorithms to guide clinical decision-making have built in beliefs that aren’t scientifically based, they are obliged to go back to the drawing board.
The need to take a fresh look at the implications of these preconceived notions was raised in an important article in The New England Journal of Medicine: “Hidden in Plain Sight—Reconsidering the Use of Race Correction in Clinical Algorithms.” (I cite a couple of other sources in this post as well.)
The authors observe that:
“Despite mounting evidence that race is not a reliable proxy for genetic difference, the belief that it is [a reliable proxy] has become embedded, sometimes insidiously, within medical practice.”
They speak of “diagnostic algorithms and practice guidelines that adjust or “correct” their outputs on the basis of a patient’s race or ethnicity…By embedding race into the basic data and decisions of health care, these algorithms propagate race-based medicine….[and] may direct more attention or resources to white patients than to members of racial and ethnic minorities.”
For example, if you look at the results of your blood work, you may have noticed two separate readings for kidney function. The estimated glomerular filtration rate, or eGFR, has historically been based on four elements: the levels of creatinine (waste the kidneys remove from the blood), age, gender, and race. The higher the score, the better the kidneys are seen to be functioning.
But there’s one assessment for Black people and one assessment for everyone else. The original reasoning was derived from the flawed assumption that Black people have more muscle mass, and thus better kidney function.
So the assessment for Black people automatically adds points for better kidney function—regardless of the particular patient. (Do most clinicians even know the reasons behind the differentiation?)
The result can be disastrous:
“These higher eGFR values may delay referral to specialist care or listing for kidney transplantation.”
In fact, the authors note:
“Black people already have higher rates of end-stage kidney disease and death due to kidney failure than the overall population.”
The good news is that both physicians and medical students at some prominent universities have called for an end to this race-based kidney testing.
Several leading hospitals have already done so. And the National Kidney Foundation and the American Society of Nephrology have said they’ll establish a task force to evaluate this use. (This information is from another source.)
The NEJM article has an insightful table of “Examples of Race Correction in Clinical Medicine” that shows how race has affected a number of decisions routinely made by clinicians who are merely following the guidelines.
By specialty, they cite the tool affected by a racial correction, input variables, use of race, and equity concern. In addition to Nephrology, the specialties include Cardiology, Cardiac Surgery, Obstetrics, Urology, Oncology, Endocrinology, and Pulmonology.
Here are just a few examples:
“The American Heart Association (AHA) Get with the Guidelines—Heart Failure Risk Score predicts the risk of death in patients admitted to the hospital. It assigns three additional points to any patient identified as ‘nonblack,’ thereby categorizing all black patients as being at lower risk. The AHA does not provide a rationale for this adjustment….Since ‘black’ is equated with lower risk, following the guidelines could direct care away from black patients.”
And here’s the real-life implication:
“A 2019 study found that race may influence decisions in heart-failure management, with measurable consequences: black and Latino patients who presented to a Boston emergency department with heart failure were less likely than white patients to be admitted to the cardiology service.”
A similar situation exists with the calculators thoracic surgeons use to estimate complications and risk of death before deciding to operate. Here, too, the algorithm’s developers don’t explain how they arrived at their conclusions, but, say the NEJM authors, “When used preoperatively to assess risk, these calculations could steer minority patients, deemed to be at higher risk, away from surgery.”
We know that Black women are up to three to four times more likely to die in childbirth than white women, according to the CDC. And though among poorer women, lack of access to care and poorer quality of care are significant factors, women who are not poor and are well-educated are also represented in these distressing statistics.
Dr. Ana Langer, Director of the Women and Health Initiative at the Harvard T.H. Chan School of Public Health in Boston has said:
“Black women are undervalued. They are not monitored as carefully as white women are. When they do present with symptoms, they are often dismissed.”
One algorithm the NEJM authors discuss pertains to Vaginal Birth After Cesarean (VBAC)—assessing the risk of labor to a woman who has had a Cesarean section when she’s about to deliver another baby.
At present, the algorithm predicts a lower success rate for women identified as African American or Hispanic to have vaginal births. In the chart, the authors note that “the decrement for [women identified as ] black…or Hispanic…is almost as large as the benefit…from prior vaginal delivery or prior VBAC.”
The result: Nonwhite women in the US–even those who have had previous vaginal deliveries—have higher rates of C-sections than white women, despite the fact that successful vaginal deliveries are safer, lead to faster recoveries, and result in fewer complications during subsequent pregnancies.
“Use of a calculator that lowers the estimate of VBAC success for people of color could exacerbate these disparities” and worsen the already high maternal death rate among Black women.
The NEJM authors say that these types of algorithms exist throughout medicine, and they cite studies to back up these assertions:
“Some algorithm developers offer no explanation of why racial or ethnic differences might exist. Others offer rationales, but when these are traced to their origins, they lead to outdated, suspect racial science or to biased data.”
The racial differences that are apparent, they say, which are erroneously attributed to genetics, are most likely the result of the experience of being Black in America—“toxic stress and its physiological consequences.” Therefore, adjustments based on race make matters worse, “baking inequity into the system.”
The answer isn’t to ignore race, they stress. Doing so would “blind us to the ways in which race and racism structure our society. However, when clinicians insert race into their tools, they risk interpreting racial disparities as immutable facts rather than as injustices that require intervention.”
“Researchers and clinicians must distinguish between the use of race in descriptive statistics, where it plays a vital role in epidemiological analyses, and in prescriptive clinical guidelines, where it can exacerbate inequities.”
The NEJM authors propose three questions that physicians should be asking in the development or application of clinical algorithms:
–Is the need for race correction based on robust evidence and statistical analysis?
–Is there a plausible causal mechanism for the racial difference that justifies the race correction?
–And would implementing this race correction relieve or exacerbate health inequities?
As evidenced by the reexaminations of the eGFR and VBAC ratings, the efforts to correct these inequities have begun. Medicine must seize upon these efforts promptly in all specialties as an opportunity to strengthen the Hippocratic Oath: First, do no harm.