  There is active debate over whether to consider patient race and ethnicity
when estimating disease risk. By accounting for race and ethnicity, it is
possible to improve the accuracy of risk predictions, but there is concern that
their use may encourage a racialized view of medicine. In diabetes risk models,
despite substantial gains in statistical accuracy from using race and
ethnicity, the gains in clinical utility are surprisingly modest. These modest
clinical gains stem from two empirical patterns: first, the vast majority of
individuals receive the same screening recommendation regardless of whether
race or ethnicity are included in risk models; and second, for those who do
receive different screening recommendations, the difference in utility between
screening and not screening is relatively small. Our results are based on broad
statistical principles, and so are likely to generalize to many other
risk-based clinical decisions.
