Insights from San Francisco match rank lists, part II: are programs doing it wrong?

Area of Science:

• Medical Education
• Surgical Training
• Matching Algorithms

Background:

• The "true-preference" strategy is considered optimal for match rank lists.
• Evidence suggests programs and applicants deviate from this strategy in practice.
• This study investigates adherence to optimal strategies in the Plastic Surgery San Francisco Match.

Purpose of the Study:

• To analyze program and applicant rank lists from the Plastic Surgery San Francisco Match.
• To determine if programs followed an optimal ranking strategy.
• To investigate potential modifications to true-preference ranking.

Main Methods:

• Utilized deidentified program and applicant rank lists and match results from SF Match (2010-2013).
• Performed statistical analysis using Microsoft Excel.
• Examined applicant match rates and program "number needed to match" metrics.

Main Results:

• The Plastic Surgery Match exhibited stable applicant numbers, applications, interviews, and match rates (78%-86%) over 4 years.
• The average "number needed to match" for programs was 4.
• A subset of less competitive applicants, ranked by programs, matched their top choice more frequently (46%) than average matched applicants (20%).

Conclusions:

• The Plastic Surgery Match has become less competitive.
• A high applicant match rate and low "number needed to match" support the hypothesis of modified rank lists.
• Rank list modifications may benefit certain applicants, as evidenced by noncompetitive applicants frequently matching their top choice.