American Council of Academic Plastic Surgeons
Back to 2022 Abstracts
Alexander Sun MD MHS1; Melanie Major MD1; Fan Liang MD2; Michele Manahan MD1; Scott Lifchez MD1
1Johns Hopkins Hospital, Baltimore, MD, USA, 2University of Maryland Medical System, Baltimore, MD, USA

Background: Plastic and Reconstructive Surgery is one of the most competitive specialties for the National Resident Matching Program. This study assesses candidate attributes that may contribute to a successful match and provides information that may guide both programs and students.
Methods: This study was IRB-approved. Data was collected from applications submitted to the authors’ institution for the 2020-2021 residency application cycle. Additional publicly-available information was gathered from the Internet. Data for groups with n?5 are not reported to preserve anonymity.
Results: Of 271 applicants, 162 matched (match rate 59.8%). Demographics are reported in Table 1. USMLE scores did not vary by training type, but research productivity did (Table 2). For U.S. MDs, research productivity was significantly associated with both medical school research ranking and taking a gap year. Matched individuals were ranked in the top 5 on the ACAPS form, while non-matched individuals were ranked between 5-10. A multiple logistic regression model was built for U.S. MD applicants using the following variables: presence of a home program, coming from a highly-ranked research institution, Step 1 score, taking a gap year, AOA status, total academic productivity (the sum of published works, presentations and submitted work), reference letters from academic plastic surgeons, overall average on the ACAPS form, and average rank on the ACAPS form. Of these, Step 1 score, total academic productivity and average rank were found to be significant (p<0.01). This model correctly predicted 87.6% of successful matches and 63.0% of non-matches (Table 4).
Conclusion: Applicants from top-ranked research institutions were associated with having greater academic productivity and taking gap years. A regression model found Step 1 score, total academic productivity and ACAPS average rank to be significantly associated with match status. This model can accurately predict match status, but does not capture factors such as qualitative assessments or contact between faculty. Especially in the setting of changes to the USMLE and the Plastic Surgery application process, awareness of these factors will allow programs to reflect on the attributes that they find most important, while also reflecting on the pitfalls of emphasizing attributes which may promote algorithmic bias.

Back to 2022 Abstracts