Literature DB >> 35108236

An Outcomes-Oriented Approach to Residency Selection: Implementing Novel Processes to Align Residency Programs and Applicants.

Holly A Caretta-Weyer1.   

Abstract

Residency application numbers have skyrocketed in the last decade, and stakeholders have scrambled to identify and deploy methods of reducing the number of applications submitted to each program. These interventions have traditionally focused on the logistics of the application submission and review process, neglecting many of the drivers of overapplication. Implementing application caps, preference signaling as described by Pletcher and colleagues in this issue, or an early Match does not address the fear of not matching that applicants hold, the lack of transparent data available for applicants to assess their alignment with a specific program, or issues of inequity in the residency selection process. Now is the time to reconsider the residency selection process itself. As competency-based medical education emerges as the predominant educational paradigm, residency selection practices must also shift to align with societal, specialty, and program outcomes. The field of industrial and organizational psychology offers a multitude of tools (e.g., job analysis) by which to define the necessary outcomes of residency training. These tools also provide programs with the infrastructure around which to scaffold an outcomes-oriented approach to the residency selection process. Programs then can connect residency selection to training outcomes, longitudinal assessment modalities, and the evolving learning environment. To achieve an outcomes-oriented residency selection process, stakeholders at all levels will need to invest in coproducing novel ways forward. These solutions range from defining program priorities to implementing national policy. Focusing on outcomes will facilitate a more transparent residency selection process while also allowing logistics-level interventions to be successful, as applicants will be empowered to better assess their alignment with each program and apply accordingly.
Copyright © 2022 by the Association of American Medical Colleges.

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Year:  2022        PMID: 35108236     DOI: 10.1097/ACM.0000000000004614

Source DB:  PubMed          Journal:  Acad Med        ISSN: 1040-2446            Impact factor:   6.893


  1 in total

1.  A novel algorithm to reduce bias and improve the quality and diversity of residency interviewees.

Authors:  Chrystal O Lau; Adam B Johnson; Abby R Nolder; Deanne King; Graham M Strub
Journal:  Laryngoscope Investig Otolaryngol       Date:  2022-09-13
  1 in total

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