Removing race from kidney function algorithm reveals systemic biases in transplant access for Black patients
Original framing: “Removing race from kidney function algorithm helped more Black patients access transplants” — STAT News
The original framing omits the role of historical and ongoing systemic racism in healthcare, including underfunded Black hospitals, implicit bias among medical professionals, and the exclusion of Black voices in algorithm development. It also lacks a discussion of how Indigenous and other non-Western medical knowledge systems might offer alternative frameworks for assessing health.
High structural omission detected in mainstream coverage.
This narrative was produced by STAT News for a primarily English-speaking, Western audience, likely with the intent of highlighting medical ethics and reform. The framing serves to critique the use of race in clinical algorithms but may obscure the deeper power structures that influence medical research, policy, and access to care for marginalized communities.
Scientific evidence increasingly shows that race is not a biologically meaningful category for health assessment. The eGFR algorithm's reliance on race lacks empirical support and has been shown to produce inaccurate results for Black patients, leading to delayed or denied care.
The removal of race from the eGFR algorithm is a critical step toward addressing systemic inequities in healthcare, but it is only part of a larger transformation needed.