Evidence map›Paper›PMID 40970102›Full record

ArticleHealth science reports2025

Are Physicians' USMLE Scores Associated With Patient Mortality? A Multilevel Modeling Approach to USMLE Predictive Validity Evidence.

Mohammed A A Abulela, Daniel P Jurich, Alex J Mechaber, Irina Grabovsky

Abstract read
In one paragraph

Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohammed A A AbulelaOffice of Assessment and Evaluation University of Minnesota Medical School Minneapolis Minnesota USA.ORCID https://orcid.org/0000-0002-5397-8817
Daniel P JurichNational Board of Medical Examiners Philadelphia Pennsylvania USA.
Alex J MechaberNational Board of Medical Examiners Philadelphia Pennsylvania USA.ORCID https://orcid.org/0000-0002-0277-8428
Irina GrabovskyNational Board of Medical Examiners Philadelphia Pennsylvania USA.ORCID https://orcid.org/0000-0002-3695-0572

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Validity evidence for high-stakes licensing examinations, particularly the association between exam scores and clinical practice outcomes, is essential for supporting valid score-based inferences. However, a gap existed in understanding how variability in patient in-hospital mortality is partitioned between physicians and hospitals and how physicians' USMLE composite scores are associated with patient mortality using multilevel modeling. Thus, we examined variability in patient in-hospital mortality between physicians and hospitals and investigated the association between physicians USMLE composite scores and patient mortality, controlling for patient, physician, and hospital characteristics. Methods: Hospitalization data were sourced from the American Medical Association, USMLE program, and Pennsylvania Health Care Cost Containment Council. Deidentified data included 150,907 patients nested within 1744 physicians in 170 hospitals. Multilevel logistic regression, including a random intercept and six conditional hierarchical models, was used to account for the nested structure and control for covariates. The seven fitted models were compared descriptively and inferentially. Results: Approximately 5% and 12% of the variability in patient mortality was attributable to physicians and hospitals, respectively. A one standard deviation increase in the USMLE composite score significantly predicted a 6% reduction in patient mortality (odds ratio 0.94; 95% CI = 0.89, 0.99), controlling for patient, physician, and hospital covariates. Conclusion: Results highlight variability in mortality attributable to physicians and hospitals and underscore the predictive value of USMLE scores. Higher USMLE composite scores were associated with a lower likelihood of patient in-hospital mortality, providing additional validity evidence for the exam and supporting its use for licensure decisions.

Indexed as

mortalitymultilevel modelingpatient outcomespredictive validityUSMLE

Identifiers

PMID40970102
PMCPMC12440804

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.