Robert C. Bowman, M.D.
Based on AMA Masterfile Data regarding 1987 - 1999 graduates of allopathic schools in 2005 careers and locations. The birth county income levels were divided into quintiles
| Income Quintile | FP Choice by pop density quintile | Rural Choice by pop density quintile | Major Medical Center % | Office IM by Pop Density quintile | Office FP by County Income Quint | Rural by County Income Quint | Office IM by County Income Quint | Cardiology by County Income Quint | Orthoped by County Income | Office Rural FP by county income | Off Primary Care poverty by county income | Off PC Poverty by pop density |
| Lowest | 18.16 | 20.52 | 65 | 9.39 | 16.15 | 18.60 | 9.60 | 1.89 | 2.88 | 5.85 | 5.59 | 5.28 |
| 2nd | 13.57 | 12.73 | 70 | 9.51 | 11.93 | 11.70 | 9.80 | 2.24 | 3.21 | 3.19 | 3.18 | 3.95 |
| 3rd | 11.35 | 9.75 | 72 | 10.14 | 12.19 | 10.80 | 9.53 | 1.99 | 3.23 | 2.63 | 2.99 | 3.29 |
| 4th | 10.47 | 9.59 | 73 | 9.47 | 11.35 | 8.60 | 10.22 | 2.08 | 3.16 | 2.19 | 3.16 | 2.95 |
| Richest | 7.34 | 6.47 | 75 | 10.59 | 9.28 | 7.80 | 10.36 | 2.37 | 3.02 | 1.72 | 2.87 | 2.44 |
Top Quintile Income for Birth County - The income proxy of birth county origin shown above reveals distribution by the proxy of birth county income level. This group appears to have the least choice of family medicine, rural locations, and primary care poverty. There is supporting data for income and family medicine by Cooter using Jefferson data and others. I verified the family medicine, rural, and office primary care poverty choices by student origins from the income levels of the top income counties, the counties with the top population density, and by top quintile of medical school based on MCAT scores. The income, population density, and income proxy variables did not appear to influence office based internal medicine, Cardiology, and Orthopedics.
This quintile involves mostly white and Asian students and high income
students of other ethnicities. Foreign born students are also contributors.
There are fewer rural born students and older students. This group is likely to
be the youngest students, those who are potentially less mature, and are the
ones who are more easily influenced by surroundings such as charismatic faculty,
medical school environment, peers, and health policy. In the Asian and white
students of all income levels, there is very little difference between the
scores and grades of those admitted or not. Ranking based on the MCAT or any
other socioeconomic variable is certain to give the advantage to a student of
slightly higher score, most probably due to socioeconomic advantage.
2nd Quintile Birth County Income - This group is
average in income and has a
balanced choice of family medicine, rural, and poverty careers at the national
averages. this group has at least some income and some access to better schools
by ability to move, live in a nicer area, or private school. The 2nd Quintile in
birth county income also reflects a mid point in physician distribution.
The remaining Quintiles by Birth Origin groups have increasingly difficult
education,
schools with teachers who are less likely to be qualified in subject areas,
schools that are not college prep, and schools where there are fewer parents
involved. In the less organized rural counties much of the county is rural with
few organized into cities. The counties with greater levels of organization have
greater levels of admission but the students that are admitted do not have the
same levels of distribution. Across the board, less urban, less organized, less
educated, and less income means more distribution, making admissions for
distribution a challenging area.
Moving to lower groups increases the potential for school failure. The lowest
group will have 10 - 15% failure rates. It is possible to determine who
"might" fail, but studies demonstrate
that it is impossible to predict the individuals who will pass and who will
fail. Admissions committees that deny admission based on higher potential for
failure, even though well intentioned, are taking away perhaps the only chance
that these students will have at a level playing field in their entire lives.
This is the group that is most likely to choose primary care, rural locations,
and poverty primary care locations, especially in states where education has not
been such a barrier so that only those with elite test taking ability survived.
It is also a group that may well be able to best understand those who are
underserved.
Without saturating the needs for professionals of all types that are more likely
to serve the underserved, there will always be "losses" that are not accounted
for until the nation has more equitable distribution of education and income.
The author was not granted income or MCAT data, but there are proxies for
income such as birth county income and birth county population density. The
distribution of rural physicians and the choice of family medicine and office
based primary care in poverty locations is clearly related to socioeconomic
origins.
As a practical note, the most dominant groups are higher income, and these students numerically are the most likely to be found in underserved areas and rural areas in practice. However when percentages are considered, fewer of the urban high income types are found where they are most needed. Gaining on health access is about graduating those with a higher probability of distribution, and enhancing the probability of distribution. Admitting those of the lowest probability and then detracting from this with health policy is not a reasonable course of action.
Admissions Income Quartiles - companion piece comparing admissions by actual quintiles and reflecting on distribution
Admissions Ratios and US Medical Students - by ethnicity, race, background, geographic origin