Black Health Matters Too: The Role of Race in Life-and-Death Medical Decision-making

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Image courtesy of visuals.nci.nih.gov

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:

Cardiology

“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.”

Obstetrics

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.

Thus,

“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.

Annie

20 thoughts on “Black Health Matters Too: The Role of Race in Life-and-Death Medical Decision-making

    1. Thanks, Neil. I spent a lot of years as a medical writer/editor and spent a year on a federal study that required me to learn a bit about genetics, which I find fascinating. But mostly, I love researching things that pique my curiosity—especially when there are societal implications.

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  1. This was quite interesting. I have become convinced that “looking under the hood” of all kinds of statistical, scientific, economic or other kinds of conclusions leads to finding all kinds of things that don’t belong there (or that are missing). It is interesting how much bad science has been used in the topic of race, and how hard it has been to get rid of. Of course we have no way of knowing whether these issues are appearances of the ghosts of Sanger-style eugenics or just garden variety sloppy science.

    I do question the formulation of the three factors proposed by the NEJM authors. While the first two represent hard science (legitimate need for adjustment and sound causation) isn’t the third (weighing equities) the victory of subjective judgment over science?

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    1. Possibly—if it isn’t quantifiable. But based on all the studies being done and the rigor the authors are demanding, I feel confident that equity to access can at least be objectively verified. We’ll then be in a better position to see impact on outcomes.

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    1. Difficult, yes. But so clearly essential that I think the forces are in place. But not only must the algorithms be adjusted, but the possibly harder part of changing long-held beliefs must be undertaken.

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  2. “Looking under the hood” is a great image for this. Who knew? And so concerning how many assumptions get baked into our thinking. So concerning. Thanks for this piece! As always, I learn so much from you.

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  3. Thanks so much, Denise. This was a tough piece for me to write because science and scientists are under attack, but I think it’s a really important story that must be fully confronted and corrected.

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  4. The issue we have in the US, I think is this. There is a real entanglement of race and social class. For example, about 25% of black Americans live in “poverty”, as opposed to about 10% of white Americans.An astounding almost 50% of black children live in poverty compared to about 15% of white children. So, the issue which is entangled is this. Are the numbers for black folks a function of “race” or a function of “poverty”? I tend to think the numbers are a function of poverty.

    One obvious problem with overall statistical data is the old one of “garbage in- garbage out”. So, the issue of properly identifying categories of people or health care outcomes and then using that data to draw conclusions is always flawed, to some extent. For example. How do you categorize a person who has a black mother and white father? How do you categorize a household that is just on the brink of poverty?

    This essay pointed out that the data used by doctors to assign possible treatment outcomes may be based on factors that are not genetic, but functions of social class. A legitimate point, I think. While they are a few “race specific” diseases (sickle cell comes to mind) for the most part human beings are genetically “identical” in the larger sense of the word. So,why focus on racial categories?

    Of course, to admit that the primary problem is one of social class and not race, per se, is to admit to the utter failure of the capitalist economy. Any system that keeps significant numbers of people in society mired in poverty is obviously an economic system that does not work for many people. I do think that one of the reasons for focusing on racial, rather than social categories in the delivery of health care is due to our refusal to accept this failure. People have been conditioned to see the capitalist economy as the “best” way to organize the distribution of goods and services. There is a preconceived bias to search for other explanations rather than honestly analyze the system in which we function.

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    1. I’m always pleased to read your thoughtful and meaty comments, Joseph. I do note the huge impact of poverty on health issues—and that we must address issues such as food deprivation and environmental injustice. But we are talking about algorithms that guide decision-making—and the NEJM authors cite the often erroneous and sometimes absent data behind these huge decisions. So it’s not that they’re using the impact of poverty—it’s that they’re using wrong stuff such as the argument that Black people automatically have greater muscle mass, which lowers the likelihood of timely care. As for the big maternal death discrepancies, they affect Black women who are neither poor nor less educated.
      I didn’t refer to a recent NYT OpEd by a Black psychiatrist describing the degree of racism in med schools. Attitudes that draw incorrect algorithms or express these views must be changed, as well as circumstances that perpetuate poverty and lack of access to care.

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  5. We really like the points you’ve made here and we would like to feature you in our upcoming issue of “This Just In… Today’s Era.” Please let us know if we have your permission to quote you.

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    1. I visited your blog and found that you’re all about vampires. So please explain to me how you would be featuring me and this very serious, important issue about Black health disparities. What, precisely, is “This Just In…Today’s Era”?

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      1. Yes we are all about vampires. However, our features are about everyday so that we have a chance to showcase the amazing talent of other authors and present non-vampire issues as food for thought to our readers. So this feature, “Today’s Era” is about the political climate we are in this year and the many vantage points about what is going on in the world, have been going on, and how they pertain to everyday life. Your piece was about how African Americans are not receiving quality medical care because medical decisions are being based on assumptions due to race. So, we would put your information (name, title, site) on a feature card with a quote from your article and that feature card will be showcased in a video presentation like the other features posted. One of our staffers would later write an article about how race & gender has been used to drive many types of decisions about how people are treated (showing why your article was selected because it was spot on). We hope this helps. Even if you decline we hope you read the article about the disparities in society to see what you think, as your talent and comments are both welcome and valued.

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