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Exploring Gender, Race, and Ethnicity Differences in Assessment of Pediatric Subspecialty Fellows Using the
Melissa L Langhan1, Alan Schwartz2, Angela S Czaja3
1Departments of Pediatrics and Emergency Medicine, Section of Pediatric Emergency Medicine, Yale School of Medicine (ML Langhan), New Haven, Conn.
Objective:
Trainee assessments have demonstrated gender and race or ethnicity biases across specialties. Assessment based on the Entrustable Professional Activity (EPA) framework involves assigning a supervision level for the professional activities included in the EPA. We analyzed Clinical Competency Committee (CCC) assigned EPA supervision levels for differences by gender and race or ethnicity among pediatric subspecialty fellows.
Methods:
This is a secondary analysis of 2 deidentified datasets. CCCs provided supervision levels for each fellow for the Pediatric Subspecialty EPAs from fall 2018 through spring 2022. These data were linked to fellows who participated in a well-being study during residency that included their gender, race, and ethnicity. Based on race or ethnicity, fellows were categorized as underrepresented in medicine, Asian, or White. For each EPA, we fitted an ordinal mixed effects model to supervision ratings, with training year, gender, and race category as covariates, adjusting for clustering of ratings within fellow and institution, and multiple comparisons.
Results:
Demographic data were linked for 561 fellows. Asian fellows were more likely to receive a lower supervision level for the Consultation EPA compared with White fellows (adjusted odds-ratio 0.48, 95% CI:0.31-0.77). No other significant differences were found among the common Subspecialty EPAs.
Conclusions:
EPA-based assessments of pediatric subspecialty fellows demonstrated no differences by gender and a single difference based on race or ethnicity. Given the national trend toward using EPA-based assessments in medical education for health professions, it's reassuring that this first study in pediatric subspecialty fellows demonstrated almost no bias in these assessments.
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