title: The effects of the change in the NRMP matching algorithm. National Resident Matching Program.
abstract: BACKGROUND
  Following 2 years of heated controversy about the resident match, the National Resident Matching Program (NRMP) recently voted to replace the existing matching algorithm with a newly designed applicant-proposing algorithm.
  
  
  OBJECTIVE
  To design an applicant-proposing algorithm for the match and compare it with the existing NRMP algorithm to determine how many applicants and residency programs could be expected to receive better or worse matches from the 2 algorithms, how the different algorithms influence the opportunity for strategic behavior, and what advice can be given to participants.
  
  
  METHODS
  Computational experiments compared the newly designed applicant-proposing algorithm with the existing NRMP algorithm on the rank order lists (ROLs) submitted by all applicants and residency programs in the 1987 and 1993 through 1996 NRMP matches.
  
  
  RESULTS
  Differences in the matchings produced by the 2 algorithms are small: fewer than 1 in 1000 applicants would have received a different match. Most (but not all) of the few applicants who are matched to different positions by the 2 algorithms do better when the applicant-proposing algorithm is used; the opposite is true for programs. Opportunities for profitable strategic behavior are very rare for both applicants and programs under either algorithm. With either algorithm, both applicants and programs can be advised that trying to get a preferred match by behaving strategically is far more likely to harm than to help them.
  
  
  CONCLUSIONS
  The existing NRMP algorithm and the newly designed applicant-proposing algorithm perform similarly. Both algorithms make it sensible for applicants and residency programs to arrange their ROLs based solely on their preferences for possible matches. The choice of algorithms will systematically affect the matches of only a small group of applicants (<0.1%). The NRMP's recent decision to use the applicant-proposing algorithm starting in 1998 reflects a judgment about the impact of this difference on applicants and programs.
authors.affiliation: Department of Economics, University of Pittsburgh, Pa 15260, USA. alroth+@pitt.edu
authors.forename: A E
authors.initials: AE
authors.lastname: Roth
authors.forename: E
authors.initials: E
authors.lastname: Peranson
mesh_terms: D000465:Algorithms; D002321:Career Choice; D006801:Humans; D007396:Internship and Residency / Q000458:organization & administration*; D008389:Marketing of Health Services; D008511:Medicine; D017145:Models, Educational; D010820:Physicians / Q000600:supply & distribution; D013038:Specialization; D014481:United States