Mp66-11 preference signaling in the urology match: impact and usage trends

You have accessJournal of UrologyCME1 Apr 2023MP66-11 PREFERENCE SIGNALING IN THE UROLOGY MATCH: IMPACT AND USAGE TRENDS Ralph Grauer, Daniel Ranti, Kirsten Greene, Michael Gorin, Mani Menon, and Saša Zorc Ralph GrauerRalph Grauer More articles by this author , Daniel RantiDaniel Ranti More articles by this author , Kirsten GreeneKirsten Greene More articles by this author , Michael GorinMichael Gorin More articles by this author , Mani MenonMani Menon More articles by this author , and Saša ZorcSaša Zorc More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003329.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Analyzing behavior from the implementation of signals during the American Urological Association (AUA) urology match will help clarify applicant/program signal usage and trends. METHODS: Using verified data from the match as well as survey data reported by applicants and programs, a logistic regression was performed on applicant factors associated with obtaining a residency interview: age, gender, degree (MD or DO), distribution of signals, US senior status, minority status, Latino status, IMG status, presence of a home urology program, AUA geographic section, and USMLE Step 1 score. We described signal distribution strategies stratified by program competitiveness and program behavior upon receipt of signals with respect to interviewing/ranking applicants. RESULTS: A total of 2,659 signals were sent by 553 candidates submitting rank lists for 364 positions at 142 programs. Programs received a median of 352 applications and were signaled to a median of 16 times each (IQR: 8–26). In a logistic regression predicting interview status, we found that geographic proximity (OR 3.25, 95% CI, 2.05–5.15; p=0.001), and signal status (OR 6.04, 95% CI, 3.50–10.40; p<0.001) were predictive of receiving an interview. Using multiple imputation to broadening the dataset, male gender (OR: 0.64, 95% CI, 0.45–0.92; p=0.039) and IMG status (OR: 0.35, 95% CI, 0.15–0.81; p=0.036) were negatively predictors, while MD degree (OR 2.36, 95% CI, 1.27–4.36; p=0.023), and US senior status (OR 1.91, 95% CI, 1.13–3.23; p=0.039), were positive predictors. CONCLUSIONS: We analyzed trends of the newly added signals. We reportedstrategies for signal dispersal, factors associated with obtaining interviews, and how signals informed program interviewing/ranking decisions. Source of Funding: none © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e936 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ralph Grauer More articles by this author Daniel Ranti More articles by this author Kirsten Greene More articles by this author Michael Gorin More articles by this author Mani Menon More articles by this author Saša Zorc More articles by this author Expand All Advertisement PDF downloadLoading ...