Multinational Public Opinion on Race, Ethnicity, and Algorithmic Reform in Medicine

Importance: Several professional medical societies have removed race and ethnicity from widely used clinical algorithms with implications for millions of patients. Yet the opinions of patients and the public regarding the tensions underlying these pivotal changes have not been systematically explored. Objective: To assess global public opinion on the use of race or ethnicity in clinical algorithms, including preferences for different approaches to algorithmic reform and perceptions of alternative predictors. Design: Cross-sectional survey study. Setting: Multinational opt-in online survey conducted via Prolific in January 2026. Participants: A volunteer convenience sample with quota sampling to achieve approximately equal participation by sex at birth and across ten categories of self-identified race and ethnicity. Main Outcomes and Measures: Self-reported comfort with demographic and social predictors in clinical calculators, with net comfort defined as percentage extremely or somewhat comfortable minus percentage extremely or somewhat uncomfortable; preferences for race-specific versus race-free algorithms; perceptions of algorithmic harm or benefit. Results: Of 1,050 responses, 994 (94.7%) met eligibility criteria. Participants resided in 43 countries with a median age of 32.0 years (IQR, 26-41). Net comfort with the use of race or ethnicity in a hypothetical cancer risk calculator was +62.4% (95% CI: +57.8% to +66.9%), compared with +14.5% (95% CI: +9.1% to +19.9%) for postal or ZIP code. Overall, 87.9% (95% CI: 85.9% to 90.0%) were comfortable with race or ethnicity if a clinician explained its use and only 12.8% agreed race and ethnicity should never be used clinically. Across spirometry, kidney function, and cardiovascular risk calculators, 40.0% to 47.6% preferred race-specific versions, whereas 16.7% to 28.2% preferred race-free alternatives. Furthermore, a substantial proportion disagreed that they were well-represented by race and ethnicity categories, ranging from 22.1% for osteoporotic fracture risk equations to 42.9% for cardiovascular risk equations. These findings were consistent across countries, self-identified race and ethnicity, and among participants reporting prior experiences of racism in healthcare. Conclusions and Relevance: In our diverse multinational survey study, respondents were comfortable with the use of race and ethnicity across application areas, but often did not feel represented by existing categories and were less comfortable with the use of alternatives based on postal or ZIP codes.