In their seven-part STAT series, “Embedded Bias,” reporters Katie Palmer and Usha Lee McFarling unmasked a hidden architecture of racism in modern medicine: race-based clinical algorithms. These are tools clinicians use every day — calculators often embedded in electronic health records — to assess disease risk and guide treatment. And in case after case, the reporters found that these algorithms quietly disadvantage patients of color, particularly Black patients, frequently with fatal consequences.
The project began with a deceptively simple question: If race is a social construct, not a biological reality, why is it used so widely in medicine? From there, Palmer and McFarling spent over a year uncovering how these algorithms came to be, why they remain in use, and how deeply flawed the rationale for race adjustment often is — resting in many cases on outdated or erroneous slavery-era science. They discovered, startlingly, that these algorithms are not vestiges of the segregationist past but unintended consequences of the federal push in the 1990s to collect racial data in medical research.
As well-intentioned as that goal was, the downstream effect has been devastating. One example: kidney function calculators that “correct” results for Black patients in a way that artificially improves their kidney health score — thus disqualifying tens of thousands of people from transplant lists. Another: blood test thresholds derived from white populations, which led to many Black patients being mistakenly told they had leukemia.
The series paired sweeping investigative reporting with deeply human storytelling. Palmer and McFarling interviewed more than 100 clinicians, researchers, and patients. They reported on institutional resistance, including a secret meeting of nearly 100 Boston doctors wrestling with the political and scientific implications of changing the kidney algorithm. They uncovered internal battles that pitted ambitious young physicians and medical students against senior gatekeepers, revealing how hierarchy and academic politics often stand in the way of meaningful change.
Working with STAT Data Editor J. Emory Parker and academic collaborators, they compiled the most complete public list to date of 48 race-based clinical algorithms still in use. They turned it into a searchable database that can be used by patients, policymakers, and medical professionals to identify and challenge biased practices in their own institutions.
This is journalism that marries scientific rigor with moral clarity. “Embedded Bias” has become a touchstone in the national conversation around equity in health care — not only exposing harms but pointing the way forward, by providing a roadmap to confront one of health care’s most persistent blind spots: the hidden coding of race into the machinery of diagnosis and treatment.
