Background Although the concept of medical specialty competitiveness may seem intuitive, there are very little existing empirical data on the determinants of specialty competitiveness in USA. An understanding of the determinants of specialty competitiveness may inform career choices among students and their advisors. Specialty competitiveness correlates with availability and appeal.
Methods This narrative review examines 2019 National Resident Matching Program (NRMP) data and the existing literature to define the determinants of specialty competitiveness. A statistical analysis of key elements of the 2019 NRMP data was performed.
Results Using US senior applicant fill rate as a measure of competitiveness, medical specialty competitiveness follows general principles of supply and demand. The demand, or appeal, of a specialty correlates with several factors, including salary, prestige and lifestyle. Salary correlates strongly with US senior fill rate (r=0.78, p=0.001). Relatively few positions are available for the most competitive specialties in the NRMP match. The negative correlation between US senior fill rate and position availability is also strong (r=−0.85; p<0.0001).
Conclusion A ‘competitive specialty’ correlates strongly with high earnings potential and limited position availability. In an ideal world, a student’s pursuit of a medical specialty should be guided by interest, qualifications and ability to succeed in that field. However, students must contend with the realities of competition created by the residency matching system.
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Contributors All co-authors made meaningful and substantive contributions to this work including conceptual design, data collection, data analysis, literature review, manuscript preparation/review.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available in a public, open access repository.
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