A Predictive Model for a Reputation-Based General Surgery Residency Match and a Novel Online Calculator

作者：Killian John T Jr^*; Leeper James D; Xu Qiong; Sauer Paul F Jr; Porterfield John R Jr

来源：Journal of Surgical Education, 2018, 75(4): 846-853.

DOI：10.1016/j.jsurg.2017.09.012

• education
• general surgery
• residency
• NRMP
• match
• calculator

OBJECTIVE: This study aimed to identify medical student characteristics that predict a successful categorical match into a general surgery residency and a match based upon Doximity program rankings.
DESIGN: This was a retrospective study that analyzed academic and personal predictors of a successful general surgery residency match.
SETTING: This study was set at the University of Alabama at Birmingham School of Medicine, a public medical school.
PARTICIPANTS: This study included 173 fourth-year medical students at a public medical school who matched into general surgery residency programs.
METHODS: Our cohort comprised students graduating from our institution between 2004 and 2015 that matched into preliminary or categorical general surgery positions. We collected academic variables and performed univariate analyses and logistic regression to examine the likelihood of specific match outcomes.
RESULTS: Of 173 students, 132 (76%) matched into a categorical position and 41 (24%) matched into a preliminary position. Of all variables, clinical ranking quartile was most effective in predicting a categorical match (R-2 = 0.35). Models for a match based upon Doximity ranking lacked the same predictive power.
CONCLUSIONS: This research identifies students that are at risk for not matching into a categorical position and predicts competitiveness for certain programs. It provides a novel calculator to give applicants easily interpretable match probabilities.

• 出版日期2018-8