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A Data-driven Approach to Selecting Pulmonary and Critical Care Fellows for Interviews
Jordan A Kempker1, Ashish J Mehta1, J Shirine Allam1
1Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University Department of Medicine, Emory School of Medicine, Atlanta, Georgia.
ATS Scholar
|January 24, 2025
Summary
Developing a data-driven selection process using surveys helps training programs conduct holistic application reviews efficiently. This method supports informed decisions for selecting applicants for interviews within tight timelines.
Area of Science:
- Medical Education
- Health Professions Education
- Clinical Training
Background:
- Training programs face challenges with holistic application reviews due to time constraints.
- Limited time windows hinder comprehensive evaluation of numerous applications annually.
Purpose of the Study:
- To create and implement a data-driven selection process for holistic application reviews.
- To facilitate timely selection of applicants for interviews.
Main Methods:
- Conducted a survey of clinical faculty and fellows to identify key attributes for success.
- Developed an automated screening tool and a faculty review form based on survey results.
- Utilized weighted scores for application triaging and selection.
Main Results:
- Survey identified leadership attributes as crucial for trainee success.
- A weighted screening score and a standardized faculty review score were implemented.
- Enabled holistic review of 306 applications by 20 faculty efficiently.
Conclusions:
- Survey methods can create weighted, standardized tools for application assessment.
- Data-supported decisions facilitate efficient and holistic fellow selection.
- This approach addresses time constraints in training program admissions.
