By Mitchell Linder, MD

Assistant Professor, Department of Obstetrics and Gynecology, University of Rochester School of Medicine and Dentistry, Strong Memorial Hospital, Rochester, NY

Dr. Linder reports no financial relationships relevant to this field of study.

SYNOPSIS: Many clinical calculators use race as a predictive variable to assess risk for outcomes. Although most tools assume a genetic disposition for these outcomes, other factors, such as health disparities and other potential confounders, are more likely to be the underlying reasons for any race-related differences in outcomes.

SOURCE: Vyas DA, Eisenstein LG, Jones DS. Hidden in plain sight – reconsidering the use of race correction in clinical algorithms. N Engl J Med 2020;383:874-882.

This was a theoretical analysis of multiple existing diagnostic algorithms and clinical prediction guidelines and their use of race or ethnicity categories as inputs for calculation. Vyas et al identified 13 prominent tests and calculators in wide use today that each include race/ethnicity in their formulas. Studies they identified include pulmonary function testing, the Fracture Risk Assessment tool (FRAX), the Simplified Calculated Osteoporosis Risk Estimation (SCORE), the Breast Cancer Surveillance Consortium Risk Calculator, the National Cancer Institute Breast Cancer Risk Assessment Tool, the Rectal Cancer Survival Calculator, the pediatric urinary tract infection calculator (UTICalc), the STONE score (used for prediction of possible kidney stones), the Vaginal Birth After Cesarean (VBAC) risk calculator, the Kidney Donor Risk Index, the estimated glomerular filtration rate (eGFR) calculator, The Society of Thoracic Surgeons Short-Term Risk Calculator, and The American Heart Association’s Get with the Guidelines Heart Failure. They noted this list is not all-inclusive but includes readily available examples about how pervasive the use of race/ethnicity is in medical decision-making tools.

The authors examined the tools by specialty to show how each equation uses “race-correction” and how each race adjustment could negatively affect Black patients. In cardiology, the heart failure score predicts lower risks for Black patients (without providing any rationale). Vyas et al noted this could cause clinicians and hospitals to devote fewer resources to these patients, since they are deemed lower risk. For nephrology, the authors specifically noted how calculators overestimate kidney function based on assumptions about race-related differences in creatinine and overestimate the potential for kidney transplant failure involving kidneys from Black donors.

The STONE score also assigns lower scores to Black patients, thereby potentially guiding clinicians away from a possible diagnosis. The VBAC calculator predicts a lower chance of success for African American and Hispanic patients. This lower predicted success rate might discourage these patients from an attempt at a trial of labor and, thus, exacerbate the disproportionately high rate of cesarean delivery that minorities experience already.

Vyas et al urged institutions, medical societies, and individual clinicians to thoroughly review existing tools. To do this properly, clinicians must re-evaluate how they conceptualize race and apply it to the care they provide.


Systemic racism abounds in the medical field, with clinical calculators as just one example where it can be seen. Past research has shown that commonly employed commercial prediction algorithms used to allocate healthcare also include underlying racial bias.1 Unfortunately, we cannot look under the hood to see the inner workings of the tools we often use.

How can clinicians make evidence-based decisions that incorporate guideline-supported rationale? Vyas et al suggested clinicians ask three questions: Is the need for race correction based on robust evidence and statistical analyses (e.g., with consideration of internal and external validity, potential confounders, and bias)? Is there a plausible causal mechanism for the racial difference that justifies the race correction? Would implementing this race correction relieve or exacerbate health inequities?

Asking these questions could help identify inherent bias and systemic racism that could harm patients. It is the responsibility of every practitioner to provide unbiased and appropriate care for patients. Ensuring clinical tools are based on these same principles is a good start. For example, as of June 1, 2020, the University of Washington labs have transitioned from using the eGFR formula to using one that excludes race as a variable.2-4

The inclusion of the VBAC calculator on this list is especially concerning. An analysis of this calculator has shown most of the race-related statistics that underpin the algorithm likely are related to social advantage or disadvantage, as opposed to the result of any specific race.5 Considering these known assumptions built into the VBAC calculator, using the tool becomes more dangerous. It could serve to perpetuate health disparities by needlessly steering patients to repeat cesarean delivery solely because of their race.

With the higher rate of maternal morbidity and mortality that minorities sustain in the United States and the world, it is our duty to look at the tools we use to determine what potential conflicts or biases are included and whether that opinion is valid and applicable to patients.6 Of course, that one step will not reverse entrenched biases everywhere nor eliminate systemic racism in one sweep, but every act to combat inequalities is a worthwhile one to undertake.


  1. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science 2019;366:447-453.
  2. Eneanya ND, Yang W, Reese PP. Reconsidering the consequences of using race to estimate kidney function. JAMA 2019;322:113-114.
  3. Bonham VL, Green ED, Pérez-Stable EJ. Examining how race, ethnicity, and ancestry data are used in biomedical research. JAMA 2018;320:1533-1534.
  4. University of Washington. UW Medicine to exclude race from calculation of eGFR (measure of kidney function). May 29, 2020.
  5. Vyas DA, Jones DS, Meadows AR, et al. Challenging the use of race in the vaginal birth after cesarean section calculator. Womens Health Issues 2019;29:201-204.
  6. Petersen EE, Davis NL, Goodman D, et al. Racial/ethnic disparities in pregnancy-related deaths — United States, 2007-2016. MMWR Morb Mortal Wkly Rep 2019;68:762-765.