Incorporating Race in Clinical Algorithms—A Response

By
James A. Diao
Emma Pierson
October 1, 2026

Jama Internal Medicine

Background

The incorporation of race in clinical algorithms raises concerns about accuracy, equity, and health disparities. Evaluating both race-aware and race-neutral approaches in algorithm design is important.

Data Highlights

No numerical data provided in the source material.

Key Findings

Patient preferences are a critical factor in the design of clinical algorithms.
Incorporating race into algorithms presents methodological challenges, including misidentification by clinicians.
Race-neutral approaches should be favored when their performance is comparable to race-aware algorithms.
Comparative assessments of race-aware versus race-neutral algorithms are necessary before removing race from clinical considerations.
Race often serves as a proxy for unmeasured factors that algorithms currently cannot incorporate.
Systemic measures are required to address structural disparities beyond algorithmic modifications.

Clinical Implications

Clinicians should consider patient preferences in their decision-making processes. A careful evaluation of the impact of race-aware versus race-neutral algorithms is essential.

Conclusion

The discussion around race in clinical algorithms necessitates a balanced approach that considers methodological rigor and implications for health equity.