Abstract
BACKGROUND: Research suggests stereotyping by clinicians as one contributor to racial and gender-based health disparities. It is necessary to understand the origins of such biases before interventions can be developed to eliminate them. As a first step toward this understanding, we tested for the presence of bias in senior medical students. OBJECTIVE: The purpose of the study was to determine whether bias based on race, gender, or socioeconomic status influenced clinical decision-making among medical students. DESIGN: We surveyed seniors at 84 medical schools, who were required to choose between two clinically equivalent management options for a set of cardiac patient vignettes. We examined variations in student recommendations based on patient race, gender, and socioeconomic status. PARTICIPANTS: The study included senior medical students. MAIN MEASURES: We investigated the percentage of students selecting cardiac procedural options for vignette patients, analyzed by patient race, gender, and socioeconomic status. KEY RESULTS: Among 4,603 returned surveys, we found no evidence in the overall sample supporting racial or gender bias in student clinical decision-making. Students were slightly more likely to recommend cardiac procedural options for black (43.9 %) vs. white (42 %, p = .03) patients; there was no difference by patient gender. Patient socioeconomic status was the strongest predictor of student recommendations, with patients described as having the highest socioeconomic status most likely to receive procedural care recommendations (50.3 % vs. 43.2 % for those in the lowest socioeconomic status group, p < .001). Analysis by subgroup, however, showed significant regional geographic variation in the influence of patient race and gender on decision-making. Multilevel analysis showed that white female patients were least likely to receive procedural recommendations. CONCLUSIONS: In the sample as a whole, we found no evidence of racial or gender bias in student clinical decision-making. However, we did find evidence of bias with regard to the influence of patient socioeconomic status, geographic variations, and the influence of interactions between patient race and gender on student recommendations.