A year-long investigation by STAT journalists Katie Palmer and Usha Lee McFarling has shed light on the widespread use of race in clinical algorithms across various medical specialties. Their series, “Embedded Bias,” reveals how these tools, intended to improve patient care, may inadvertently perpetuate health disparities.
The project, which involved over 100 interviews with researchers, clinicians, health system executives, and federal officials, uncovered nearly 50 tools that incorporate race in current clinical care. These algorithms span multiple areas of medicine, from risk calculators for vaginal births after cesarean sections to kidney function estimates.
Palmer’s journey began with a chance discovery of a paper discussing how a risk calculator might place Black women at higher risk of complications from a vaginal birth after a cesarean section. This finding sparked a broader investigation into the use of race in medical decision-making tools.
The reporters faced significant challenges in connecting these abstract algorithms to real-world patient impacts. Many patients are unaware of how race-based calculations influence their care, making it difficult to illustrate the personal consequences of these practices.
One notable exception is the estimated glomerular filtration rate (eGFR) for kidney function, where the racial adjustment is visible on lab reports. This transparency has led to increased awareness and pushback from Black patients who realized they were being treated differently.
The series aims to inspire patients to question how medical decisions are made and to encourage a broader public conversation about the role of race in healthcare algorithms. As the medical community grapples with these issues, the reporting highlights the complex balance between achieving statistical accuracy and ensuring equitable care for all patients.
See “How I Did It: From ‘internet rabbit hole’ to compelling series” (October 3, 2024)
