A reexamination of the NRMP matching algorithm. National Resident Matching Program

Acad Med. 1995 Jun;70(6):470-6; discussion 490-4. doi: 10.1097/00001888-199506000-00007.


Most graduating medical students in the United States find their first professional appointments through the National Resident Matching Program (NRMP). This service receives rank-order lists of preferences from students and from hospitals, and then generates final assignments of students to hospitals through the use of a specific computerized matching algorithm. The author uses recent findings from the mathematics and economics literatures to demonstrate three difficulties with the NRMP's matching algorithm and the official descriptions thereof. First, the algorithm favors hospitals over students, a feature known to the NRMP since at least 1976, but, in the author's opinion, not made clear in NRMP literature for students. Second, the author argues that the NRMP's justification that its algorithm mimics orderly, noncentralized admission processes is not correct. Institutions operating under non-centralized procedures must typically make more initial offers than there are positions, in the realization that some fraction of their offers will be declined. This arrangement enlarges the choices available to many applicants, and thereby benefits them, whereas the NRMP's algorithm unrealistically assumes that no institution would ever send out any extra offers. Third, the NRMP's algorithm contains incentives for students to misrepresent their true preferences when constructing their rank-order lists. This feature is a substantial disadvantage of the current algorithm and is incorrectly described in literature distributed to students and in published articles from the NRMP.(ABSTRACT TRUNCATED AT 250 WORDS)

Publication types

  • Review

MeSH terms

  • Algorithms
  • Bias
  • Choice Behavior
  • Humans
  • Internship and Residency*
  • Job Application*
  • Motivation
  • Personnel Selection
  • Software Validation
  • Statistics, Nonparametric
  • Students, Medical / psychology*
  • United States
  • Workforce