Multivariable analysis of factors associated with USMLE scores across US medical schools

被引:17
作者
Ghaffari-Rafi, Arash [1 ,2 ]
Lee, Rachel Elizabeth [1 ]
Fang, Rui [1 ]
Miles, J. Douglas [1 ]
机构
[1] Univ Hawaii Manoa, John A Burns Sch Med, Honolulu, HI 96822 USA
[2] UCL, Queen Sq Inst Neurol, London, England
关键词
United States medical licensing examination; USMLE; Evaluation; Student learning; Curriculum; Assessment; COLLEGE ADMISSION TEST; STEP; 2; UNITED-STATES; MCAT SCORES; PERFORMANCE; VALIDITY; STUDENTS; PHYSICIANS; BOARD;
D O I
10.1186/s12909-019-1605-z
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
BackgroundGauging medical education quality has always remained challenging. Many studies have examined predictors of standardized exam performance; however, data sets do not distinguish by institution or curriculum. Our objective is to present a summary of variables associated with the United States Medical Licensing Examination (USMLE) scores, and thus identify institutions (and therefore curriculums) which deviate from trend lines by producing higher USMLE scores despite having lower entrance grade point averages and medical college admissions test (MCAT) scores.MethodsData was obtained from U.S. News and World Report's 2014 evaluation of allopathic U.S. medical schools. A univariate analysis was performed first for each variable using two sample t-test or Wilcoxon rank sum test for categorical variables, and Pearson or Spearman correlation coefficients for continuous variables. A multivariable linear regression model was developed to identify the factors contributing to USMLE scores. All statistical analyses were two-sided and performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC).ResultsUnivariate analysis reveals a significant association between USMLE Step 1 and 2 scores with medical college admissions test scores, grade point averages, school type (private vs. public), full-time faculty-to-student ratio, National Institute of Health funds, residency director assessment score, peer assessment score, and class size. Of these nine variables, MCAT scores and Step 1 scores display the strongest correlation (corr=0.72, P<.0001). Multivariable analysis also supports a significant association between MCAT scores and Step scores, meanwhile National Institute of Health funding size demonstrates a negative correlation with USMLE Step 2 scores. Although MCAT scores and National Institute of Health funds are significantly associated with USMLE performance, six outlier institutions were identified, producing higher USMLE scores than trend line predictions.ConclusionsOutlier institutions produce USMLE scores that do not follow expected trend lines. Their performance might be explainable by differences in curriculum. Having identified these institutions, their curriculums can be further studied to determine what factors enhance student learning.
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页数:7
相关论文
共 23 条
[1]  
[Anonymous], 2017, CHART OUTC MATCH CHA
[2]  
[Anonymous], 2017, FACTS TABL 16
[3]  
[Anonymous], 2017, USMLE SCOR INT GUID
[4]   Undergraduate institutional MCAT scores as predictors of USMLE step 1 performance [J].
Basco, WT ;
Way, DP ;
Gilbert, GE ;
Hudson, A .
ACADEMIC MEDICINE, 2002, 77 (10) :S13-S16
[5]   Student performances on Step 1 and Step 2 of the United States Medical Licensing Examination following implementation of a problem-based learning curriculum [J].
Blake, RL ;
Hosokawa, MC ;
Riley, SL .
ACADEMIC MEDICINE, 2000, 75 (01) :66-70
[6]   The relationship between clinical science performance in 20 medical schools and performance on step 2 of the USMLE licensing examination [J].
Case, SM ;
Ripkey, DR ;
Swanson, DB ;
Andreatta, AG ;
Barry, W ;
Carlson, P ;
Davis, W ;
Edwards, J ;
Epps, A ;
Feldman, L ;
Fincher, RM ;
McCahan, J ;
McMahon, T ;
Mosely, J ;
Peppler, R ;
Pestana, C ;
Perkowski, L ;
Smith, J ;
Smith, M ;
TitusDillon, P ;
Waechter, D ;
Wheeler, R ;
Willoughby, TL .
ACADEMIC MEDICINE, 1996, 71 (01) :S31-S33
[7]   The predictive validity of the MCAT for medical school performance and medical board licensing examinations: A meta-analysis of the published research [J].
Donnon, Tyrone ;
Paolucci, Elizabeth Oddone ;
Violato, Claudio .
ACADEMIC MEDICINE, 2007, 82 (01) :100-106
[8]   Do MCAT scores predict USMLE scores? An analysis on 5 years of medical student data3 [J].
Gauer, Jacqueline L. ;
Wolff, Josephine M. ;
Jackson, J. Brooks .
MEDICAL EDUCATION ONLINE, 2016, 21
[9]   What Makes a Top Research Medical School? A Call for a New Model to Evaluate Academic Physicians and Medical School Performance [J].
Goldstein, Matthew J. ;
Lunn, Mitchell R. ;
Peng, Lily .
ACADEMIC MEDICINE, 2015, 90 (05) :603-608
[10]   Selection Criteria for Residency: Results of a National Program Directors Survey [J].
Green, Marianne ;
Jones, Paul ;
Thomas, John X., Jr. .
ACADEMIC MEDICINE, 2009, 84 (03) :362-367