Background: Standardized Letter of Recommendation was introduced to capture more meaningful fellowship applicant evaluations. There are concerns that this letter may introduce subjectivity to assessments traditionally measured by objective metrics, such as board scores and publications.
Objective: To evaluate the influence of individual application elements on ranking by referee.
Design: Collected data included applicant demographics and objective assessments of academic performance, including in-service exam percentiles, Step 1 and Step 2 scores, and publication count. Summary statistics and odds ratios from repeated measures logistic regression models using the method of generalized estimating equations are reported.
Settings: Standardized letters submitted to a single institution during the 2019 application cycle were analyzed.
Main outcome measures: To determine if objective applicant parameters are associated with being subjectively ranked #1 by the referee.
Results: Among 302 standardized LOR forms, 51.3% of the applicants were ranked #1 by the referee. Applicants ranked #1 had higher junior and senior in-training exam percentiles (60.3 vs 50.9, p = 0.0002 and 59.5 vs 48.0, p < 0.0001, respectively), Step 1 scores (235 vs 231, p = 0.0287) and average number of publications (5.9 vs 3.5, p = 0.0011). For each unit rise of in-training percentile and publication number, the odd ratio for being ranked #1 improved by 1.03 (p = 0.002) and 1.08 (p = 0.013), respectively. Ranks lower than #1 did not demonstrate the expected decline in objective performance metrics with decreasing rank except Step 1 percentile (p ≤ 0.001). Technical ability was the strongest predictor of a #1 ranking.
Limitations: Analyses limited to elements included in standardized letters.
Conclusions: Standardized letters retain the relationship between objective performance metrics and subjective ratings for applicants ranked #1 by referee. However, this relationship is lost when applicants are ranked lower than first place. Our findings provide valuable insights and inform best practices for employing standardized letters of recommendation in the context of fellowship selection. See Video Abstract.
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