The murder of George Floyd in 2020 sparked a nationwide movement for racial equity, prompting individuals across various fields to confront the issue of race. In the medical field, James Diao, a former medical student at Harvard Medical School, found himself grappling with the question of why race was a factor in clinical tools used to determine a patient’s risk of disease if race is a social construct.
Diao’s exploration into this question led him to delve into the implications of race in clinical calculators and the impact of its removal. His research on this topic has influenced policy decisions affecting millions of patients and has sparked conversations about the role of race in healthcare.
Working with Arjun Manrai, an assistant professor of biomedical informatics at Harvard Medical School, Diao focused on the calculation of kidney function, known as eGFR, and how hospitals were adjusting their calculators to remove the factor of race. Through extensive Zoom meetings and collaboration with partner Gloria Wu, Diao navigated the complexities of the debate surrounding race in clinical tools.
As debates raged on social media and in academic circles about the harm of both including and excluding race from clinical calculators, Diao remained observant and open to learning. He engaged with literature, discussions with peers, and advocacy groups to deepen his understanding of the issue.
Balancing empirical evidence with moral arguments, Diao worked to present a nuanced perspective on the role of race in clinical decisions. Collaborating with researchers and physicians who had long studied clinical algorithms, Diao navigated the challenges of advocating for change while respecting the complexities of the issue.
In a study published in the Journal of the American Medical Association, Diao quantified the impact on Black patients of removing race from the eGFR calculator. The research highlighted the potential benefits and drawbacks of such a change, sparking further dialogue and debate within the medical community.
As the National Kidney Foundation and American Society of Nephrology convened a task force to reassess the role of race in eGFR, Diao presented his research and testified alongside other medical students advocating for change. His efforts culminated in a perspective published in the New England Journal of Medicine, which proposed a more comprehensive approach to developing a new kidney function equation that goes beyond simply removing race.
Diao’s work exemplifies a thoughtful and balanced approach to addressing the complexities of race in clinical tools. By engaging with diverse perspectives and remaining open to learning, Diao has contributed to discussions that have the potential to improve healthcare outcomes for all patients. Months after the initial recommendation was made to support race-free approaches in healthcare algorithms, James Diao’s work has had a significant impact on the treatment and care of Black patients. Diao, who grew up in Houston and later studied health policy in the UK, has been instrumental in challenging race-based clinical algorithms and advocating for more accurate and equitable approaches.
One of his key projects involved reevaluating the kidney transplant waitlist algorithm, which had previously stratified patients by race. By advocating for a race-free approach, thousands of Black patients have had their wait times adjusted, improving their chances of receiving a much-needed kidney transplant.
Diao’s work didn’t stop there. He also played a crucial role in challenging the American Thoracic Society’s race-based lung function testing algorithm. By highlighting the implications of shifting to a non-race based algorithm, Diao paved the way for the ATS to move away from race-based testing, leading to more accurate diagnoses and treatment options for Black patients.
The impact of Diao’s work extends beyond just medical algorithms. His recent graduation as the 22nd summa cum laude student in Harvard Medical School’s history is a testament to his dedication and expertise. Now diving into residency in Boston, Diao’s focus on cardiology highlights his passion for helping patients with heart-related conditions.
In his pursuit of better patient outcomes, Diao continues to explore the impact of race-free tools in healthcare. His work on the PREVENT calculator, a tool developed by the American Heart Association to predict the likelihood of strokes and heart attacks, showcases his commitment to using data-driven approaches to improve patient care. By incorporating social determinants of health, such as ZIP codes, into the calculations, Diao aims to provide more accurate predictions and address disparities in healthcare outcomes.
As healthcare organizations consider adopting these new tools and guidelines, Diao emphasizes the importance of patient perspectives and feelings about these changes. By listening to diverse voices and actively seeking out different perspectives, Diao hopes to contribute to a more equitable and effective healthcare system for all patients. Patients may have concerns about their race being used to determine their risk of disease, but what about their estimated income factoring in? This is a question that researchers like Diao and his colleagues are exploring in a new study. They are taking the time to listen to patients and understand their perspectives on how personal information should be used in their healthcare.
In the study, participants are being asked about their comfort level with various factors being used in their care. This includes not only race but also estimated income. The goal is to gather insights into how patients feel about the use of this information and how it may impact their healthcare decisions.
For many patients, the idea of their income being factored into their risk of disease may raise concerns about privacy and potential discrimination. Income is a sensitive topic for many people, and they may feel uncomfortable with the idea of it being used in a medical context. This raises important questions about how personal information should be handled in healthcare settings and the potential implications for patient care.
As researchers continue to listen to patients and gather feedback on these issues, it is clear that there is a need for thoughtful consideration of how personal information is used in healthcare. Patients should feel empowered to voice their concerns and preferences about the use of their data, and healthcare providers should be attentive to these concerns in order to provide the best possible care.
Overall, this study highlights the importance of patient-centered care and the need for open communication between patients and healthcare providers. By listening to patients and respecting their preferences, healthcare professionals can ensure that they are providing care that is sensitive to the individual needs and concerns of each patient.
