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. 2018 Dec;23(1):1489691.
doi: 10.1080/10872981.2018.1489691.

Beyond 'charting outcomes' in the radiation oncology match: analysis of self-reported applicant data

Samuel Jang  1 , Stephen A Rosenberg  1   2 , Craig Hullett  1 , Kristin A Bradley  1   3 , Randall J Kimple  1   3
Affiliations

Beyond 'charting outcomes' in the radiation oncology match: analysis of self-reported applicant data

Samuel Jang et al. Med Educ Online. 2018 Dec.

Abstract

The Charting Outcomes resource is useful in gauging an applicant's competiveness for a given specialty. However, many variables are not reported in Charting Outcomes that may influence an applicant's ability to match. A significant proportion of applicants record their experiences in an anonymous, self-reported applicant spreadsheet. We analyzed factors associated with a successful match using this dataset to test the hypothesis that research productivity and high academic performance correlates with success rates. A retrospective analysis of "RadOnc Interview Spreadsheet" for the 2015, 2016, and 2017 radiation oncology match was performed. Data were accessed via studentdoctor.net. Board scores, research characteristics, Sub-I participation, and interview invitation rates were available. Mann-Whitney U, Kruskal-Wallis, and chi-square tests were used for statistical analysis. When possible, results were compared to those reported in the National Residency Match Program's "Charting Outcomes" report. A total of 158 applicants were examined for the applicant characteristics. Applicants applied to a median of 61 programs and received a median of 14 interviews. The mean step 1 score was 248 (range: 198 to 272) and most were in the highest grade point average quartile (68.3%). 21.7% participated in additional research year(s), and 19% obtained a PhD. The majority of applicants took three radiation oncology electives (48.7%). On multivariate analysis, alpha-omega-alpha (AOA) honors society status (p=0.033), participating in a research year (p=0.001) and number of journal publications (p=0.047) significantly correlated with higher interview invitation rates. In summary, this study identifies important considerations for radiation oncology applicants that have not been previously reported, such as induction into AOA and number of journal publications.

Keywords: Radiation oncology; applicant; match; online database; student doctor network.

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References

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