Driving Difficulty or Distinction

Robert C. Bowman, M.D.

The medical schools with higher MCAT scores have lower levels of physician distribution. The humble origin student types that are found in rural locations, underserved locations, primary care, or family medicine careers are also the ones that have the lower MCAT scores (Characteristics of the MCAT Examinees). These are all groups that also have the lowest probability of admission. Changes in Admissions in Allopathic Medical Schools involve increasing income levels of students. This is also likely to be associated with the increasing MCAT scores for admitted medical students. The MCAT scores, standardized to 1993 levels by AAMC (Julian), have been steadily increasing since that time. The bioscience component is rising at nearly 0.1 unit a year. MCAT Changes Since 1992

There is little doubt that allopathic medical students are a more narrow representation of higher income populations and those found nearest medical schools in the United States. This includes highest income, foreign born, Asian, and those born in counties with medical schools. Over 60% of US medical students were born in cities or counties with medical schools in this or in other nations. For some schools the levels approach 90%. Understanding the differences in race, ethnicity, education, income, and proximity to medical schools is important in understanding admissions and distribution. See tables in Shaping a Nation: Physicians Who Serve

Asian medical students are perhaps the best representation of the direction of medical school admissions. Asian students have increased the most rapidly from a few percent to 23% of medical students. Asian students are the best representation of combinations of concentration, especially Asian Indian populations that have top rates of income, higher education, and professional education in census studies; top income, professional parents, physician parents, and dual professional parents in medical student studies; highest percentages (over 50%) found in just 1% of the land area closely associated with top concentrations of people, income, physicians, and medical schools. Asian students are a concentration of all of the factors most related to admission and also to poor distribution. It is indeed unfortunate that studies fail to illustrate the parent influences. This tends to perpetrate differences according to race when the real factors are about concentrations. Whites and other students with the same higher status combinations and concentrations have the same higher probability of admission and the same poor distribution.

Asian students have an advantage in admissions as they have a higher MCAT score compared to USMLE 1 scores. Whites have a lower MCAT and higher USMLE 1 (Veloski reference) These studies did not compare origins but whites are less than the ultimate urban concentrations found in Asian (and some Hispanic), are less connected to medical schools by proximity, and are more of a mix of ages and income levels. One interpretation would be that students with every advantages of income and education as represented by Asian students, have a peak level as noted by the MCAT. Asian populations are at their peak concentrations in the most densely populated areas in counties with the most medical schools. Whites are at their lowest concentration in these areas with only 44%. White medical students are a greater mix of rural born and older and lower income that have not had the same consistent advantages as highest income whites, Asians, or any other group. The comparison of their scores reveals that their performance is still improving. They also have had life experiences such as marriage that may also help them with medical school performance. Asian students are the youngest, have the fewest life experiences, and are the least likely to be married.

Studies based on experiential place demonstrate that those spending the first 30 years of life in the top concentrations are least likely to be found in marginal and underserved practice locations.

Ranking students by socioeconomics, scores, college power ratings, or proximity to medical schools can make it difficult to distribute physicians. Those least likely to distribute would be admitted and those most different and diverse would be excluded. The loss of lowest income and rural born student types is some level of confirmation that the nation is Changing Admissions in Allopathic Medical Schools. Whether this is deteriorations in education, fewer pursuing medical education, debt, legal actions with reversals of affirmative actions, national pressures such as US News and World Report Rankings or other factors is unknown, but all are likely.

Medical educators such as Mark Albanese have researched the concept of thresholds where students are evaluated for a minimal academic value and placed into an acceptable pool. The final selections involve much less emphasis on scores. Schools noted to distribute have also a different focus in admissions. Also it is an advantage in broader admission to be in a state that has a more lower and middle income and rural origin students doing well enough to gain higher education. Duluth 20 Questions

It is helpful to have visual renditions of the changes in Difficulty and Distinction with changing MCAT scores in students.

The source of this data is Ellen Julian's article on MCAT and performance in Academic Medicine Vol 80, Number 10 October 2005. On page 916 there are a number of graphics in the article .

The charts make the point of Mark Albanese and others regarding thresholds. Beyond a level of approximately 8, there is little to gain and potentially much to lose. Admitting higher MCAT scores narrow admissions without improving the relative rates of difficulty or distinction which are flat.

The rates of physician distribution in relationship to MCAT scores, income, or rural origins are not flat.


You can drive a truck though the pathway between difficulty and distinction. Significant numbers of lower scoring students still achieve distinction levels. Trying to admit students 1 point higher means very little in terms of difficulty or distinction for nearly all of the students who are typically admitted. Performance is more and more likely to be related to individual factors and not related to MCAT scores.

However from the perspective of health access and physician distribution, a 1 point MCAT score means 3 - 5 percentage points lower choice of family medicine for a typical medical school.

MCAT and Choice of Rural Practice

The following scatterplot (from Robert Bowman) compares medical school MCAT scores collected from medical school web sites with Match Data on FP choice for allopathic US schools.

As with other regression studies, the schools with the lower MCAT scores have higher choice of family medicine. A 1 point higher MCAT score translates to 5 - 9 fewer family physicians in a typical class of 131 students. The loss of 3000 lower and middle income students out of 16,000 admissions and their replacement by 3000 of the highest income origin students is a concern for more than family medicine. This has been the effect of changing admissions in just the past 10 years. Changing Admissions in Allopathic Medical Schools. Increases in the income levels of those taking standardized tests results in higher scores.

Rural workforce can also be tracked to school MCAT with higher scoring schools contributing the least

Duluth graduates contribute 64 times the rural primary care of a top 20 medical school graduate ranked by MCAT scores.

From Cooter's study from Jefferson Longitudinal Data   See also Attrition Rates

  Family Med Difficulty
Lowest Quartile 22% 6%
Middle Quartiles 17% 3%
Highest Quartile 13% 1%

Note the 1990s health policy effect that boosted family medicine choice to twice the current levels.

Basically medical school evaluations can identify 90% of those at risk of academic failure which are also those with the highest probability of a return to the populations of their birth. Of these students 80% or more will graduate. And those that are most different will distribute at the highest levels, particularly when Choosing Family Medicine, the career that facilitates physician distribution

Admissions Income Quartiles - for admissions probabilities and distribution probabilities

MCAT and Choice of Family Medicine

Physician Workforce Studies



1.         Albanese MA, Farrell P, Dottl S. Statistical criteria for setting thresholds in medical school admissions. Adv Health Sci Educ Theory Pract. 2005;10(2):89-103.

2.         Albanese MA, Farrell P, Dottl SL. A comparison of statistical criteria for setting optimally discriminating MCAT and GPA thresholds in medical school admissions. Teach Learn Med. Spring 2005;17(2):149-158.

3.         Albanese MA, Snow M, Skochelak S, Huggett K, Farrell PM. Matriculating student perceptions of changes to the admissions interview process at the University of Wisconsin Medical School: a prospective, controlled comparison. Wmj. 2003;102(2):30-33.

4.         Albanese MA, Snow MH, Skochelak SE, Huggett KN, Farrell PM. Assessing personal qualities in medical school admissions. Acad Med. Mar 2003;78(3):313-321.

5.         Basco WT, Jr., Gilbert GE, Blue AV. Determining the consequences for rural applicants when additional consideration is discontinued in a medical school admission process. Acad Med. Oct 2002;77(10 Suppl):S20-S22.

6.         Cooter R, Erdmann JB, Gonnella JS, Callahan CA, Hojat M, Xu G. Economic Diversity in Medical Education. Evaluation and the Health Professions. September 2004;27(3):252-264.

7.         Crump R, Byrne M, Joshua M. The University of Louisville Medical School's comprehensive programs to increase its percentage of underrepresented-minority students. Acad Med. Apr 1999;74(4):315-317.

8.         FairTest Home Page. FairTest: The National Center for Fair & Open Testing Available at www.fairtest.org/ Accessed April, 2005. 2006.

9.         Hart B, and Risley, T. Meaningful Differences in the Everyday Experience of Young Children. Baltimore: Paul H. Brookes; 1995.

10.       Julian ER. Validity of the Medical College Admission Test for predicting medical school performance. Acad Med. Oct 2005;80(10):910-917.

11.       Kassebaum DG, Szenas PL. Rural sources of medical students, and graduates' choice of rural practice. Acad Med. Mar 1993;68(3):232-236.

12.       Kay-Lambkin F, Pearson SA, Rolfe I. The influence of admissions variables on first year medical school performance: a study from Newcastle University, Australia. Med Educ. Feb 2002;36(2):154-159.

13.       Koenig JA, Sireci SG, Wiley A. Evaluating the predictive validity of MCAT scores across diverse applicant groups. Acad Med. Oct 1998;73(10):1095-1106.

14.       Nickens HW, Ready TP, Petersdorf RG. Project 3000 by 2000. Racial and ethnic diversity in U.S. medical schools. N Engl J Med. Aug 18 1994;331(7):472-476.

15.       Reeves TJ, Bennett CE. We the People: Asians in the United States Available at www.census.gov/prod/2004pubs/censr-17.pdf Accessed April, 2005. Washington DC: U.S. Bureau of the Census; 2004.

16.       Wheat JR, Brandon JE, Carter LR, Leeper JD, Jackson JR. Premedical education: The contribution of small local colleges. J Rural Health. Spring 2003;19(2):181-189.

17.       Xu G, Fields SK, Laine C, Veloski JJ, Barzansky B, Martini CJ. The relationship between the race/ethnicity of generalist physicians and their care for underserved populations. Am J Public Health. May 1997;87(5):817-822.

18.      Veloski JJ, Callahan CA, Xu G, Hojat M, Nash D. Prediction of students' performances on licensing examinations using age, race, sex, undergraduate GPAs, and MCAT scores. Acad Med. Oct 2000 2004;75 (10 Suppl):S28-30.

rcbowman@atsu.edu for comments or questions

Physician Workforce Studies


wolf grey 3s jordan 6 sport blue cheap jordans wolf grey 3s cheap jordan shoes sport blue 3s nike kd vii kate spade outlet kate spade outlet wolf grey 3s cheap air jordans kate spade outlet jordan 3 sport blue michael kors outlet michael kors outlet jordan 3 sport blue louis vuitton outlet louis vuitton outlet lebron 12 Michael Kors Outlet