A comprehensive 12-year review has revealed that health care algorithms can both reduce and exacerbate racial and ethnic disparities in patient outcomes. The study, led by Dr. Shazia Mehmood Siddique, examined literature from 2011 to 2023 to assess the impact of these algorithms on health care equity.
The research, published in the Annals of Internal Medicine, found a complex landscape where some algorithms improved disparities while others worsened them. For instance, a revised kidney allocation system was shown to reduce disparities, while certain severity-of-illness scores used in critical care resource allocation perpetuated them.
The study comes in the wake of heightened awareness of systemic racism in American society, sparked by events in 2020 including the deaths of George Floyd, Breonna Taylor, and Ahmaud Arbery, as well as the disproportionate impact of COVID-19 on communities of color.
Researchers identified seven strategies to guide more equitable algorithm practices, emphasizing the need for thoughtful design and implementation. The study acknowledged limitations, noting that most evidence came from modeling studies, which may not fully represent real-world applications.
An accompanying editorial highlighted the ongoing debate about the use of race in medical algorithms, citing the National Kidney Foundation and American Society of Nephrology’s evidence-based approach to developing a new, equitable kidney function equation.
The research underscores the critical importance of addressing racial and ethnic disparities in healthcare as algorithms continue to influence patient care. It serves as a call to action for stakeholders to carefully consider the potential impacts and unintended consequences of these tools in the pursuit of health equity.
