Medicine, Education, and Socioeconomic Status

 

Robert C. Bowman, M.D.        Version as of 10/13/2004

 

Much appreciation to Ed Fryer and the Robert Graham Center for sharing data. Also thanks for the assistance of the Federal Office of Rural Health Policy and Tom Morris, and a very patient boss, Mike Sitorius. For them and for the parents, teachers, and patients that influence us the most:

 

Abstract and Summary: In this effort, the author explores the relationship between medical school admissions and socioeconomic status. Studies of individual students have demonstrated that students of higher socioeconomic status choose family medicine less often. The author uses income data applied to various ethnic groups and various birth origins to further illustrate the relationship between social status and medical school admissions probabilities and choice of family medicine. Medical schools with more urban students, more younger students, fewer students born instate, and higher Medical College Admission Test (MCAT) scores graduate fewer family physicians. There appears to be a linear relationship between socioeconomic status of student and choice of family medicine, choice of direct patient care specialties, and choice of underserved locations. Front line physician specialties in primary care, mental health, and women's health may be most at risk without broader admissions. Public education seems to play a key role in such admissions. State by state comparisons reveal that states with better graduation rates and broader distribution of education funding admit more rural born students and graduate more family physicians. Without admissions of a broader range of students, medical schools will be unlikely to graduate the physicians most needed by the nation.

 

Summary of Results

Direct Studies On Allopathic Graduates

 

% Family Practice General Practice

Family Practice General Practice

% of FP/GP

1994 - 2000 Graduates

% of Medical School Graduates

All 1994 - 2000 Allopathic Graduates

16.1%

17518

100.0%

108997

100.0%

School MCAT < 9.14

23.1%

2905

17.4%

12566

12.0%

School MCAT 9.15 - 9.38

19.5%

2995

17.9%

15321

14.6%

School MCAT 9.39 - 9.60

17.7%

2077

12.4%

11744

11.2%

School MCAT 9.61 - 9.82

16.5%

2607

15.6%

15794

15.0%

School MCAT 9.83 - 10.14

16.0%

2593

15.5%

16169

15.4%

School MCAT 10.15 - 10.49

13.0%

1579

9.4%

12150

11.6%

School MCAT 10.49 - 10.99

11.7%

1507

9.0%

12935

12.3%

School MCAT 11.00 - 12.03

5.6%

470

2.8%

8351

8.0%

Out of State Born

14.5%

9762

55.7%

67472

61.8%

Instate Born

18.7%

7769

44.3%

41631

38.2%

Urban Birth (RUCA)

15.0%

14730

84.1%

98233

90.0%

Rural Birth (RUCA)

25.8%

2801

16.0%

10870

10.0%

Urban Inf 1 Birth > 1 mill

14.6%

7496

42.8%

51173

46.9%

Urban Inf 2 Birth < 1 mill

19.1%

4828

27.6%

25262

23.2%

NonMetro Birth

25.7%

2697

15.4%

10489

9.6%

Foreign Birth

10.7%

1892

10.8%

17608

16.2%

Military Birth

19.8%

165

0.9%

834

0.8%

Younger

14.8%

12747

72.8%

86586

79.4%

Older than 30

22.5%

4770

27.2%

22410

20.6%

Age 24 – 25

10.6%

882

5.0%

8419

7.7%

Age 26

13.9%

4971

28.4%

35773

32.8%

Age 27 – 28

16.2%

5680

32.4%

35140

32.2%

Age 29 – 30

16.8%

2072

11.8%

12305

11.3%

Age 31 – 32

18.5%

1205

6.9%

6517

6.0%

Age 33 – 36

21.6%

1350

7.7%

6247

5.7%

Age 37 & up

29.5%

1358

7.8%

4596

4.2%

Over 50000 Pop Per Sq Mile

2.2%

61

0.4%

2743

2.7%

Over 5000

7.8%

1977

11.9%

25487

25.0%

2500 – 5000

12.3%

3070

18.5%

25025

24.6%

1000 – 2500

15.2%

3039

18.3%

19953

19.6%

250 – 1000

20.2%

3744

22.5%

18536

18.2%

Less than 250

37.2%

4779

28.8%

12837

12.6%

Less than 50 People/Sq Mile

75.6%

1400

0.8%

2438

2.4%

Note that these values were 30 % greater than any time in the past 20 years because of increased FP choice in the 1995 – 1998 graduating classes. These choices are now at least 10 – 20 % lower than the pre-managed care years.

 

 

Medical school studies

The following involved 111 allopathic medical schools. The correlations involve the medical school of origin for the 1997 - 2003 ACGME family medicine residency programs. There is no difference using match data, FPGP data for 1994 - 2000 graduates, or groups with fewer years of graduates. This is a study comparing medical schools, not individual students!

Descriptives

Correlations

 

Mean

Std. Devia-tion

FP Cohort

MCAT Avg

High School Grad 1986

Long-itude

Pop per Sq Mile Cnty

FP Cohort

17.58

36.02

1.000

-0.668

0.406

-0.391

-0.452

MCAT Average

9.73

3.59

-0.668

1.000

-0.037

0.105

0.319

HS Grad 1986

74.72

37.48

0.406

-0.037

1.000

-0.155

-0.096

Longitude

-88.41

62.81

-0.391

0.105

-0.155

1.000

0.217

Pop per Sq Mile Cnty

2346.33

25442

-0.452

0.319

-0.096

0.217

1.000

 

 

 

 

 

 

 

 

Over 30 yrs graduate

22.91

39.43

0.531

-0.484

0.154

-0.258

-0.228

Born County > 1 mill

37.988

76.910

-0.623

0.612

-0.106

0.199

0.431

Foreign Born %

12.01

28.59

-0.605

0.479

-0.131

0.125

0.557

Asian Student %

11.05

43.37

-0.484

0.392

-0.072

-0.096

0.461

Rural Born %

18.45

55.27

0.671

-0.572

0.243

-0.179

-0.399

White Male %

43.77

51.54

0.326

-0.455

-0.118

0.082

-0.325

NIH Amount

61745057

3.E+08

-0.495

0.805

-0.055

0.066

0.203

FP Dept 92

0.87

1.68

0.574

-0.539

0.119

-0.118

-0.448

Non Metro % 2000

33.37

86.72

0.427

-0.427

0.259

-0.038

-0.406

State Median Income

40.08

27.06

-0.231

0.477

0.312

0.007

0.225

Instate Avg (JAMA)

71.75

134.70

0.549

-0.608

-0.217

-0.234

-0.257

Instate Born %

40.61

84.17

0.503

-0.549

-0.024

-0.174

-0.073

Rural Mission/Person

0.45

2.47

0.594

-0.412

0.189

-0.031

-0.263

Avg MCAT 00

9.58

3.49

-0.634

0.964

-0.008

0.069

0.301

Avg MCAT 01

9.78

3.72

-0.668

0.976

-0.038

0.074

0.327

Avg MCAT 02

9.78

3.81

-0.627

0.979

-0.008

0.133

0.283

Avg MCAT 03

9.76

3.72

-0.672

0.973

-0.087

0.129

0.332

Bioscience MCAT 03

9.96

3.86

-0.644

0.954

-0.037

0.078

0.327

MCAT Avg1

9.68

3.51

-0.675

0.993

-0.046

0.090

0.340

Researchers 87-94

0.73

4.15

-0.602

0.806

-0.016

0.203

0.288

ResidentFellow Index

4.48

14.06

-0.371

0.559

-0.052

0.039

0.289

Orthopedics

3.19

5.76

1.000

0.659

0.005

0.235

0.234

Cardiology

1.68

4.20

1.000

0.417

-0.399

0.288

0.348

Obstetrics-Gyn

6.55

8.40

1.00

-0.384

-0.174

0.168

-0.070

Internal Medicine

15.68

15.26

1.00

0.397

-0.285

0.126

0.451

Office Based Proportion of IM

59.45

38.27

1.00

-0.607

0.169

-0.253

-0.295

All Office-Based Primary Care

0.33

0.28

1.00

-0.733

0.213

-0.343

-0.427

Weighted Least Squares Regression - Weighted by rural % pop in 92

 

The variables associated with greater density of income and population associate negatively with FP choice and positive with the MCAT scores. Older, instate, rural, white male, FP department, and rural mission/person variables are positively correlated with family medicine choice and negative with the MCAT. The MCAT was chosen because of its primary importance in admissions. Other variables were considered, but were rejected because of collinearity with the MCAT. Longitude, high school graduation, and population density were other variables that contributed, but had the least association with the MCAT.

 

Only OB-Gyn, office-based primary care, and the proportion of students choosing office-based internal medicine have the same negative correlation with the MCAT as does family medicine. Orthopedics has the strongest positive correlation and internal medicine and IM subspecialties and pediatrics also share a positive correlation. In eastern medical schools student choices steer toward internal medicine, pediatrics and obstetrics-gynecology and moving west the choices are more toward family medicine.

 

Internal medicine and its subspecialties contrast with family medicine in the location of the medical school. Family medicine is a more common choice at medical schools in less densely populated areas, even controlling for MCAT, longitude, nonmetro population, and education. Medical schools in the most densely populated areas are not as likely to graduate physicians that distribute.

 

Age can be considered a socioeconomic variable with older students the lowest on the scale.

Rural birth can be considered socioeconomic with those from the least densely populated areas lowest on the scale.

Those with the lowest MCAT scores are lowest on the scale in many ways. Direct MCAT scores have not been accessible so far so direct confirmation awaits those privileged with such access. Given the other relationships, this is hardly a guess however.

 

The students least likely to be admitted to US medical schools are the ones most likely to choose family medicine and distribute where needed as physicians.

 

 

Introduction

The distribution of physicians to underserved areas of the nation has been a vexing problem for decades. Cures for the maldistribution of physicians by location and specialty have been a focal point for billions of dollars in grants by governments, foundations, and associations as well as some of the most innovative efforts in medical education.

 

It is instructive that the major gains in distribution did not result from expansion of medical schools or grant funding. They have been the result of a few dedicated individuals working with admissions at the local level to facilitate the admission of students who were "different."   Best Models Admissions

 

Also the national accountability efforts known as managed care impacted the medical school classes graduating from 1994-2000. This period of accountability was predicted by medical education experts such as Butler in Academic Medicine's Season of Accountability and Social Responsibility.

 

This brief time period gave hope to those "pushing" primary care and family medicine. This time of accountability mainly has served to mask the  longer term decline in choice of family medicine and primary care.

 

This decline in family medicine may be more related to who is admitted

when compared to what happens after admission.

 

The nation has again resumed the search for solutions, including multimillion dollar efforts from family medicine alone (FFM). In the mean time, proven solutions remain unreplicated. Those most successful in locating physicians in the most underserved areas have even been "reformed" or terminated. Others have lost their best leadership. Best Models  

Despite these successes, medical leaders deny responsibility for physician distribution, noting market forces at work. Cohen, Why Doctor's Don't Go Where They Are Needed It is easy to see that there are leaders that have a narrow viewpoint regarding non-urban parts of the nation.

The nation's workforce leaders are at odds with "market forces" leadership and "social responsibility" leadership. Both agree that better education and preparation are needed and government support is necessary for the financing of medical education, but the groups differ in many other areas. Market force leaders blame poor distribution upon the poor economies of rural and inner city areas while social responsibility leaders note that admissions of students with more humble origins results in physicians who will go to underserved areas and help address needs for jobs, services, education, leadership.

Admissions models have not been widely implemented, admissions research has been largely neglected, and medical schools continue to focus on medical school influences instead of those having impact long before admissions. There have also been great proposals that have high probability of working (see Cohen on Admissions at the end of this page).

The likely resolution is that both market forces and social responsibility approaches are correct, but there are potentially some physician specialties that must have social responsibility admissions. This is becoming a more and more difficult problem with new studies demonstrating a widening gap between poor and rich school districts, between rural and inner city and suburban, and between school districts with white students as compared to minorities (Education Trust Study Funding Gap 2004 published in fall 2004).

New research has directly associated admissions of students of lower socioeconomic status with the graduation of more family physicians (Cooter R Economic Diversity in Medical Education). This longitudinal study of Jefferson medical students matched up data from origins, admission, medical school performance, and residency evaluations. Students admitted from the highest quartile of parent income chose family medicine 13% of the time, compared to 22% from the lowest quartile.

 

Secondary data noted below may allow this longitudinal study to be translated across the nation and throughout past decades to help understand the impact of socioeconomic status upon medical school admissions, particularly physician workforce in primary care and for underserved areas.

 

In the following, the choice of family medicine is highest in the lowest income areas and areas slightly less urban and in schools with slightly lower MCAT scores

 

Choice of Family Medicine

Urban Influence  Code

RUCA

Cooter and Jefferson Longitudinal

MCAT Averages By School

Asian Ethnicity

Urban/Highest Income

Code 1

13.3 %

Urban/Urban-focused

10 %

Highest Quartile

13 %

Top 30

7 %

Indian-Pakistani 2.2 %

Other/Lowest Income

Others

20+ %

Large Rural 20% to Isolated Rural 28 %

Lowest Quartile

22 %

Bottom 30

17 % *

Vietnamese

24 %

* Excluded 15 lowest MCAT schools and osteopathic. See above summary table for new data

 

For those who might dismiss lower income admissions as impossible in today's environment,  studies in Iowa by Kreiter have already outlined methods of economic-based admissions that are likely to meet legal standards. 

 

For those concerned about implementing such admissions, branch models such as Duluth have existed for years with a focus on rural and family medicine. Decentralized training has also worked at WWAMI and other locations. It may be that training locations outside of the counties of over 1 million pop may be considered enough of an impediment that the most urban students will not consider them. Working with community colleges may also screen out the more urban-oriented Small Colleges and Admissions

 

Also rural, older, and "different" students have been attempting admissions for years, but have been turned down. The Jefferson study by Cooter brings decades of denial into sharp focus. For years there has been a game played about admissions with many medical leaders saying that different admissions will not graduate physicians that will go to underserved areas or stay there, or both. Now the question becomes:

Will admissions committees take the time and effort to admit the physicians most needed by the nation and risk a few percentage points more of attrition, or will admissions continue in a pathway almost certain to lead to less and less direct patient care preferences for physicians and fewer physicians for underserved areas. Admissions already includes 61% of students born in counties of over 1 million population even though only 48% of US population resides there.

 

There is also a real possibility that narrow admissions will accelerated physicians quality problems.

Side Effects of Selecting for Family Medicine

 

As Don Madison noted in his studies of the 1985 graduates of the University of North Carolina:

 

"If an admission committee informs itself of "what finally happens" to those it admits, its decisions can contribute to achieving whatever policy its medical school adopts with respect to the mix of physicians it wishes to produce." Madison, Donald L Medical School Admission and Generalist Physicians A Study of the Class of 1985,  Academic Medicine Vol 69 Number 10 October 1994 p 825 - 831

See a review of this and other articles at Service Orientation

 

Methods

The author worked with the Robert Graham Center data files and the AMA Masterfile and assembled family medicine "match rates" by ethnicity and by type of birth origin via RUCA coding (urban, large rural, medium rural, isolated rural) and Urban Influence Coding (1993). The parent incomes listed in AAMC Minorities in Medicine XII were linked to these match rates. Also the income levels of various birth origins at the time of birth were also linked to known family medicine "match rates" by rurality.

 

Computations of Age and Determination of Birth Origins

 

Details on FP Match Rates by Ethnicity and Rurality

 

Plotting parent income and FP choice via ethnicity leads to the following:

 

Figure 1: Parent Income and Ethnicity and FP Choice 

 

Figures 2: Broader Distributions of Parent Income

 

Figure 3,4  Higher Income Distribution and Comparison

 

A comparison of the income distributions of the highest and lowest parent incomes is useful in understanding the importance of the lower income levels. The previous tables illustrate that the Vietnamese have the lowest income levels of any Asian group. The Vietnamese also have the broadest income distribution of any group. Korean parents are in between. The Indian-Pakistani group is the highest income group and therefore most skewed to the right with 45% having income levels over $100,000. This compares to the Vietnamese student applicants with only 12% at the highest income levels. The Vietnamese students chose FP at 28.9% while Indian/Pakistani chose FP 2 % of the time. All other ethnicities and birth origin markers fall between these extremes.

 

Mexican American, Black, and Native American origin students have a broader parent income distribution more like the Vietnamese group. Koreans and “Other Hispanic” students tend to be in the middle in mean income, distribution, and FP choice.

 

The Asian group as a whole closely resembles the Indian-Pakistani group suggesting much higher admission ratios for the higher income Asian subgroups. The Asian group as a whole and the Indian-Pakistani group are both similar in income distribution to the White group, with higher income shifts in all three.  There are relatively few lower income students compared to total students for Whites and Asians. Both groups together determine 85% of the output of US allopathic medical schools.

 

Birth Origin, Income, and Choice of Family Medicine: the Rural Component

 

There appear to be other markers for lower socioeconomic status. Rural background students are known to choose family medicine at higher rates. The following is a table comparing match rates by county type for family medicine graduates from 1997 - 2003. The income data used for each Urban Influence Code (1993 set) is the median income of the county of birth for 1959 (in 1989 dollars). This was averaged for the counties within each code.

 

Table of Birth Origins of Allopathic Medical Students 1987 - 2000

Birth Origins

Not FPGP

FPGP

Total

% FPGP

% of Students

% US Pop 1970-2000

US Born outside 50 states

3511

372

3990

9.3%

1.8%

 

Foreign Born

27655

3001

31028

9.7%

14.2%

 

Missing Birth Data

1751

231

2151

10.7%

1.0%

 

Code 1 Counties 1 million pop

92762

13161

106904

12.3%

48.8%

49-51%

 

 

 

 

 

 

 

Totals and FP Average

186407

30563

219226

13.9%

100.0%