The research team, led by Carl Berghult, Joseph Mellberg, Lachlan Anderson, Erica Olfson, and David Shau of the Anne Marion Burnett School of Medicine at Texas Christian University and the Texas Hip and Knee Foundation in Fort Worth, undertook an ambitious cross-sectional analysis of the entire population of orthopaedic surgery residents in ACGME-accredited programs. Rather than sampling, they assembled a census: 3,844 residents across 215 orthopaedic residency programs. The investigators built their dataset from publicly accessible sources, including program rosters, institutional directories, social media profiles, and medical school websites, a method that allowed them to map the educational origins of virtually every orthopaedic resident in the United States without touching any private or identifiable information.

The analytical design is what gives the study its distinctive angle. Because the researchers could not determine the exact date each resident sat for Step 1, they used postgraduate year, or PGY level, as a temporal proxy for the scoring era. Residents in their first through third years of training, PGY-1 through PGY-3, would have entered the Match during or after the transition period surrounding the pass/fail switch, while PGY-4 and PGY-5 residents represented cohorts that matched under the old numeric scoring regime. This stratification allowed the team to compare whether the relationship between medical school characteristics and residency program rank differed between Match eras, effectively using the resident population itself as a natural archive of the transition.

The central finding is striking. Among PGY-1 through PGY-3 residents, the more recent Match-era cohorts, medical school rank correlated significantly with the rank of the residency program the graduate ultimately joined. Among PGY-4 and PGY-5 residents, who matched under numeric Step 1 scoring, no such significant association was observed. In other words, before the scoring change, a graduate’s medical school pedigree showed no measurable statistical relationship with the standing of their orthopaedic program; after the transition, that relationship emerged. The authors are careful to frame this as a temporal association observed in an observational, cross-sectional study, not proof of causation, but the pattern is consistent with the hypothesis that when a familiar screening metric disappears, selection processes shift toward other signals, including institutional prestige.

The magnitude of some institutional effects deserves attention. Graduates of Tier 1 medical schools, as ranked by U.S. News & World Report, had the highest median residency program rank in the dataset, at 47. Even more dramatic was the divide between allopathic and osteopathic graduates: MD students had approximately ten-fold higher odds of training in a higher-ranked orthopaedic residency program compared with DO students. The study also examined what the authors call orphan status, meaning medical schools with no affiliated orthopaedic residency program of their own. Graduates of such schools faced roughly 40 percent lower odds of matching into a higher-ranked program. These are not trivial differences; they suggest that structural features of a medical school, some of them dating back to decisions made long before an applicant ever matriculated, are woven into match outcomes.

Methodologically, the team treated residency program rank as an ordinal outcome and deployed a battery of statistical tools appropriate to that structure. Chi-square tests assessed categorical associations, while univariate and multivariate ordinal logistic regression quantified the odds of landing in a higher-ranked program across school characteristics, controlling for other variables. Spearman correlation coefficients measured the rank-order relationship between medical school rank and residency program rank. Ordinal logistic regression is particularly well suited to this kind of question because residency program quality is inherently a ranked, non-continuous quantity, and the approach allows researchers to model the probability of falling into a higher rather than a lower category without assuming equal spacing between ranks.

The categorization scheme the researchers used reveals how many dimensions of medical school identity they considered. Beyond the U.S. News & World Report rankings and the Tier 1 designation, schools were classified as allopathic versus osteopathic, public versus private, and orphan versus non-orphan status. Each of these categories captures a different facet of institutional infrastructure. Allopathic versus osteopathic status reflects two parallel systems of medical education in the United States with different historical pathways to licensure. Public versus private status often correlates with funding structures and state-based admissions pipelines. Orphan status speaks to the presence or absence of an in-house orthopaedic residency, which can shape access to mentorship, research opportunities, letters of recommendation from orthopaedic faculty, and early exposure to the specialty, all factors long suspected to influence match success.

Why would the pass/fail transition amplify the role of institutional characteristics? The logic articulated in the study is straightforward. Before 2022, Step 1 scores served as a standardized, nationwide screening tool that programs could apply uniformly to every applicant, regardless of origin. With the numeric signal gone, programs lost their most convenient common denominator and may have turned to alternative applicant characteristics to fill the gap. Where a candidate went to school, whether that school hosts its own orthopaedic department, and the degree-granting tradition behind the diploma are all visible on an application in ways that raw ability is not. If programs lean more heavily on such proxies, the statistical imprint of institutional background on match outcomes would be expected to deepen, exactly the pattern the PGY-stratified analysis detected.

The authors are explicit about the limitations that bound their conclusions. The use of PGY level as a proxy for Step 1 scoring era is an approximation, not a direct measurement, since individual examination dates were unavailable and some residents delay graduation or take the examination at different points in their training. The cross-sectional design captures a single snapshot of the resident population rather than following individuals over time, and observational data of this kind cannot establish that the scoring change caused the observed associations. Residency program rank itself, derived from reputation-based rankings, is an imperfect measure of training quality. The study also relied on publicly available information, which, while ethically clean and free of privacy concerns, may contain occasional inaccuracies in self-reported credentials or affiliations.

Nevertheless, the implications ripple outward across medical education. For applicants, the findings suggest that in the pass/fail era, the road to a top orthopaedic residency may run more visibly through institutional channels, making mentorship, research access, and home-program support more decisive than ever. For osteopathic medical students and graduates of schools without affiliated orthopaedic residencies, the ten-fold and 40 percent odds differences quantify a structural headwind that predates any individual performance. For residency programs and policy makers, the results raise a pointed question about equity: if removing a standardized numeric metric shifts selection toward characteristics that track institutional privilege, the profession may need to develop new, fairer ways to evaluate the growing pool of pass/fail-era applicants. With no external funding and no declared competing interests, the study offers an open-access, data-driven starting point for that conversation as the first fully pass/fail-era Match cohorts continue to move through training.

Subject of Research: The association between medical school characteristics and orthopaedic residency match outcomes before and after the USMLE Step 1 pass/fail transition

Article Title: Medical school ranking and orthopaedic match outcomes in the USMLE Step 1 pass/fail era: a PGY-stratified analysis

Article References: Berghult, C., Mellberg, J., Anderson, L., Olfson, E., & Shau, D. (2026). Medical school ranking and orthopaedic match outcomes in the USMLE Step 1 pass/fail era: a PGY-stratified analysis. BMC Medical Education. https://doi.org/10.1186/s12909-026-10594-z

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10594-z

Keywords: orthopaedic surgery residency, USMLE Step 1, pass/fail scoring, medical school ranking, residency match, medical education, applicant selection, MD versus DO, ordinal logistic regression, ACGME, PGY-stratified analysis, health equity