Chrystal O Lau1, Adam B Johnson1,2, Abby R Nolder1,2, Deanne King1, Graham M Strub1,2,3. 1. Department of Otolaryngology-Head and Neck Surgery University of Arkansas for Medical Sciences Little Rock Arkansas USA. 2. Arkansas Children's Hospital Little Rock Arkansas USA. 3. Arkansas Children's Research Institute Little Rock Arkansas USA.
Abstract
Objective: Improve the quality and diversity of candidates invited for the Otolaryngology-Head and Neck Surgery residency match by reducing geographical and inter-rater bias with a novel geographic distribution algorithm. Methods: Interview applicants were divided into geographic regions and assigned to reviewers. Each reviewer selected by force-ranking a pre-determined number of applicants to invite for interviews based on the percentage of applications received for each region. Our novel geographic distribution algorithm was then applied to maintain the geographic representation and underrepresented minority status of invited applicants to match the applicant pool. Results: Analysis of previous interview selection methods demonstrated a statistically significant overrepresentation of local applicants invited for interviews. In 2022, 324 domestic applications were received for the otolaryngology match, which were divided into six geographic regions. There was no significant difference in USMLE scores between regions. The implementation of our distribution algorithm during applicant selection eliminated local overrepresentation in the invited pool of applicants and maintained the representation of underrepresented minority applicants. Following the match, reviewers indicated that implementation of the geographic distribution algorithm was simple and improved the quality and diversity of the group of interviewed applicants. Conclusion: Traditional methods of scoring and inviting otolaryngology residency applicants can be confounded by regional and inter-rater biases. Employing a geographic distribution algorithm improves the quality and diversity of invited applicants, eliminates bias, and maintains the representation of underrepresented minority applicants.
Objective: Improve the quality and diversity of candidates invited for the Otolaryngology-Head and Neck Surgery residency match by reducing geographical and inter-rater bias with a novel geographic distribution algorithm. Methods: Interview applicants were divided into geographic regions and assigned to reviewers. Each reviewer selected by force-ranking a pre-determined number of applicants to invite for interviews based on the percentage of applications received for each region. Our novel geographic distribution algorithm was then applied to maintain the geographic representation and underrepresented minority status of invited applicants to match the applicant pool. Results: Analysis of previous interview selection methods demonstrated a statistically significant overrepresentation of local applicants invited for interviews. In 2022, 324 domestic applications were received for the otolaryngology match, which were divided into six geographic regions. There was no significant difference in USMLE scores between regions. The implementation of our distribution algorithm during applicant selection eliminated local overrepresentation in the invited pool of applicants and maintained the representation of underrepresented minority applicants. Following the match, reviewers indicated that implementation of the geographic distribution algorithm was simple and improved the quality and diversity of the group of interviewed applicants. Conclusion: Traditional methods of scoring and inviting otolaryngology residency applicants can be confounded by regional and inter-rater biases. Employing a geographic distribution algorithm improves the quality and diversity of invited applicants, eliminates bias, and maintains the representation of underrepresented minority applicants.
Authors: Parsa P Salehi; Alyssa Heiser; Pauniz Salehi; R Peter Manes; Benjamin L Judson; Babak Azizzadeh; Yan Ho Lee Journal: Otolaryngol Head Neck Surg Date: 2020-10-20 Impact factor: 3.497
Authors: Christina Dorismond; Zainab Farzal; Rupali N Shah; Charles S Ebert; Robert A Buckmire Journal: Otolaryngol Head Neck Surg Date: 2022-03-01 Impact factor: 3.497
Authors: Grant M Gebhard; Leah J Hauser; Miranda J Dally; David A Weitzenkamp; Cristina Cabrera-Muffly Journal: Laryngoscope Date: 2015-07-30 Impact factor: 3.325