A Novel Ticket System for Capping Residency Interview Numbers: Reimagining Interviews in the COVID-19 Era

Acad Med. 2021 Jan 1;96(1):50-55. doi: 10.1097/ACM.0000000000003745.

Abstract

The 2019 novel coronavirus (COVID-19) pandemic has led to dramatic changes in the 2020 residency application cycle, including halting away rotations and delaying the application timeline. These stressors are laid on top of a resident selection process already under duress with exploding application and interview numbers-the latter likely to be exacerbated with the widespread shift to virtual interviewing. Leveraging their trainee perspective, the authors propose enforcing a cap on the number of interviews that applicants may attend through a novel interview ticket system (ITS). Specialties electing to participate in the ITS would select an evidence-based, specialty-specific interview cap. Applicants would then receive unique electronic tickets-equal in number to the cap-that would be given to participating programs at the time of an interview, when the tickets would be marked as used. The system would be self-enforcing and would ensure each interview represents genuine interest between applicant and program, while potentially increasing the number of interviews-and thus match rate-for less competitive applicants. Limitations of the ITS and alternative approaches for interview capping, including an honor code system, are also discussed. Finally, in the context of capped interview numbers, the authors emphasize the need for transparent preinterview data from programs to inform applicants and their advisors on which interviews to attend, learning from prior experiences and studies on virtual interviewing, adherence to best practices for interviewing, and careful consideration of how virtual interviews may shift inequities in the resident selection process.

Publication types

  • Review

MeSH terms

  • COVID-19 / epidemiology*
  • Education, Medical, Graduate / methods*
  • Humans
  • Internship and Residency / organization & administration*
  • Pandemics*
  • Personnel Selection*
  • Students, Medical / statistics & numerical data*