Abstract
The current program-centric algorithm for the National Resident Matching Program (NRMP) primarily uses the program's ranking of students to determine a match. Concerns that the existing algorithm favors programs over students, recent findings that the program's ranking of applicants is not associated with resident performance, and disruptions of existing screening methods and metrics have prompted reevaluation of the current algorithm relative to a student-centric algorithm, in which student ranking of programs is primary and program ranking of students is secondary. To compare program-centric and student-centric algorithms for the NRMP participants. This cross-sectional study used randomized computer-generated data reflecting the NRMP match for 2018, 2019, and 2020, capturing more than 50 000 students and more than 4000 programs in 23 specialties, to compare the 2 algorithms. The same simulated students, programs, and rankings were exposed to the 2 algorithms, running 2300 simulations in the overall analysis and 1000 simulations in each of 23 specialties. The percentage of students who did and did not match, the percentage of students who matched to their top-ranked and top-5-ranked programs, and the program's rank of the last student matched per position were examined. The 2 algorithms were not different in percentage of students matched overall (eg, for 2020, program-centric: 59% [95% CI, 57%-61%]; student-centric: 58% [95% CI, 56%-60%]; P = .73). The student-centric algorithm, relative to the program-centric algorithm, matched a significantly higher percentage of students to their first-ranked program (eg, for 2020, 50% [95% CI, 48%-52%] vs 14% [95% CI, 13%-15%]; P < .001) and to their top-5-ranked programs (eg, for 2020, 60% [95% CI, 58%-62%] vs 46% [95% CI, 44%-48%]; P < .001). However, the last position was filled with students who had lower program rankings in the student-centric algorithm vs the program-centric algorithm (2 [95% CI, 1-2] vs 8 [95% CI, 6-10]; P < .001). In this study, the 2 algorithms were not different in the percentage of students matched overall. However, the student-centric algorithm matched a significantly higher percentage of students to their preferred programs. The program-centric algorithm was associated with a lower program's last matched student rank. Further research is needed on the algorithms' associations with cost and time demands in the match, postmatch resident and program performance, and fit with a changing environment.
Highlights
The National Resident Matching Program (NRMP) has grown to serve more than 50 000 student applicants to more than 30 000 positions in more than 4000 medical residency programs
The last position was filled with students who had lower program rankings in the student-centric algorithm vs the program-centric algorithm (2 [95% CI, 1-2] vs 8 [95% CI, 6-10]; P < .001)
The studentcentric algorithm, relative to the program-centric algorithm, matched a significantly higher percentage of students to their first-ranked program and to their top-5–ranked programs; the last position was filled with students who had lower program rankings in the student-centric algorithm vs the program-centric algorithm
Summary
The National Resident Matching Program (NRMP) has grown to serve more than 50 000 student applicants to more than 30 000 positions in more than 4000 medical residency programs. Programs invite selected student applicants for interviews. Programs and students submit their rank-ordered lists to the NRMP for possible matching through its algorithm. The process is exhausting for students and programs.[1] Students have to apply, be selected for interviews, schedule interviews, manage and pay for travel, interview, and submit postinterview rankings, in addition to their ongoing academic and clinical work. The match process has been legally challenged as uncompetitive, but Congress deemed that the process is ”highly efficient, pro-competitive, and longstanding.”[8]
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