In 2007, the Maternal Fetal Medicine Units Network (MFMU) created an algorithm to determine whether someone could have a successful vaginal birth after a previous cesarean section (VBAC). The algorithm incorporated race and ethnicity as a variable, along with factors like age, body mass index, and the reason for the previous cesarean. Based on evidence showing that patients with scores below 60% had worse outcomes with a vaginal birth, the VBAC calculator was widely adopted in the US.

More than a decade later, people started to raise concerns about how the use of race and ethnicity in the algorithm furthers structural inequities. Scholars criticized algorithms that used race broadly for perpetuating the false idea that race is biological and obscuring structural root causes of health disparities.

New research led by Nicholas Rubashkin, MD, used interviews with clinicians and patients, along with recorded prenatal visits, to analyze how the use of the VBAC calculator helped “automate” racism by coding race into institutional practices and care interactions.

The researchers identified 4 processes that facilitated automation of inequities:

• Adhering to strict cutoffs. Clinicians reported varying rationales for using cutoff scores to determine who would be offered a vaginal birth. Some clinicians struggled with these policies and argued that cutoff scores shouldn’t override a patient’s preference. Others believe the cutoffs keep patients safe.
• Routine adoption of calculators. Even in institutions that didn’t require the use of a calculator, it was adopted into routine counseling in many sites and became a standard for educating ob-gyn trainees. One Latinx maternal-fetal medicine specialist told researchers, “I feel like I was indoctrinated to the calculator.”
• Obscuring use of the calculator. Despite believing they were guided by objective evidence, clinicians often subjectively interpreted calculator scores as more or less favorable for the patient. Some shared their interpretations with patients without explicitly referencing the calculator, making it harder to identify the potential bias and for patients to push back.
• Reflexively categorizing race and ethnicity. The calculator required clinicians to categorize patients into mutually exclusive racial and ethnic categories of Black, Hispanic, and white. Clinicians sometimes encountered challenges when entering Asian American, Indigenous, multiracial, multi-ethnic, or Afro-Latinx patients. In these situations, some clinicians would decline to use the calculator, while others would apply a “one drop” rule. As one Latina patient who often passed as white told researchers, “I’m like, if this calculator is based on science, then it shouldn’t be like that flexible.”

This study shows how the calculator disadvantages Black and Latinx patients even when racial bias is a known concern. By naturalizing false biological notions of racial and ethnic differences contributing to “failure” rates, the VBAC calculator contributed to obstetric racism in the US.

Algorithms have the potential to inscribe historical racism into new information architectures, institutional practices, and human interactions. When clinicians used cutoff scores, they facilitated the calculator’s inequitable assessment. When they did not transparently show the calculator in their counseling, Black and Latinx patients had to do extra work to expose the inequitable assessment. The calculator was powerful because it appeared to be scientifically designed to ensure a safe birth, but it promoted the false idea that it’s possible to biologically divide people into mutually exclusive races.

In 2021, amidst growing calls for the abolition of race-based medicine, the MFMU developed a new calculator that excludes race and ethnicity. While removing race and ethnicity helped mitigate the most negative consequences, racism might continue to operate implicitly. Racism may explain in part why Black and Latinx people undergo more unnecessary c-sections. Because the new VBAC calculator treats every prior c-section as if it were clinically necessary, people are pushed into a VBAC calculator. If a more fair and just calculator exists, it would have to pay attention to the explicit and implicit ways that racism structures the risk for primary and repeat c-sections. Otherwise, the VBAC prediction model could perpetuate historical structural racism.