Hard to describe how much I appreciate the various insights from all who
contribute to the list serve. A Global perspective is a most missing area
in medicine and perhaps in many professions.
There are indeed many strategies for minimizing minority groups from a
broad range.
Just got a note from the FP folks happy that the federal budget had
restored their own precious area. Each year the President zeroes out this
section, also the rural section, sections for teachers, sections for
various public servants, etc. Instead of being able to focus on real
reforms in primary care, health care, education, or other areas, each group
is then forced to spend all political capital defending their turf. It is
the ultimate divide and conquer. My next post Line in the Sand is a
response to this. Sorry about several.
People are primarily individuals. Data never represents individuals well. I
always have to keep remembering this, especially when much of the research
involves small percentages and only a few percentage points. This is
significant in statistical measurements, and even meets relevance since it
is national data, but the difference between 6% or 18% is still rather
small.
Concentrations of certain characteristics allow us to categorized various
groups, compare them, and understand other characteristcs.
When considering physicians, basically this is a very skewed group already
with 60% from the top 20% in income. Those with higher status
concentrations are going to be found in medicine at a higher degree,
whether all of these really want to be a physician or are willing to make
the effort is a good question, especially when parents apply so much
pressure in higher status families. Physicians are indeed a skewed group
from birth, with more coming from professionals and physicians. More Asians
enter the nation as physicians already. Foreign born populations in the US
other than Hispanic enter as adults usually with careers and education
intact.
Physicia M.D. D.O. Nurses Family US Pop US Pop
n Practice 2000 2040
Assistan
t
Active Practice 60000 763200 54300 126000 280m 377m
Active Primary Care 24000 271400 34700 114000
One of the tragedies of poor health policy is that physician assistants and
nurse practitioners have been converted away from primary care. Nurse
practitioner listings range from 100,000 to 161,000, activity levels and
true primary care levels vary greatly. The 161,000 estimate includes the
broadest range, the most inactive and part time, and the most varied type
of training. Actual activity, primary care levels are a different story.
About 65% of all forms of primary care are inside major medical centers.
Only family medicine remains 50% outside.
Composition of Practitioners By Ethnicity, Race, and Country of Origin
Physicia M.D. D.O. All Recent US Pop US Pop
n Studen Studen Nurses Family 2000 2040
Assistan t t Practice
t in
Practice
Asian/Pacific (Not 4.5% 23% 17% 3.8% 7.8% 4.3% 7.8%
Hispanic)
Black (Not Hispanic) 6.3% 7% 5.4% 5.1% 4.7% 12.0% 13.1%
Foreign Born (any) 17% 9.4% 10% 11.0% 13.2%
Hispanic/Latino Origin 5.0% 6.% 4.4% 2.2% 3.5% 10.7% 21.9%
Native American (Not 0.9% 0.7% 0.1% 0.5% 0.3% 1.0% 0.8%
Hispanic)
White (Not Hispanic) 83.4% 64% 71.8% 89.0% 81.5% 70.7% 56.3%
Sources Estimate 2005 2006 2000 1997-2003 2000 Census
d AAMC AOA HHS Residency Census Estimat
All Grads e
Nurses Masterfil
e
http://www.census.gov/population/projections/nation/summary/np-t5-f.txt
None of these groups are superior or inferior, however the various groups
do represent various concentrations of income, education, occupation, and
professional occupation
The following 3 sets of correlations involve 138132 physicians born in 1187
different counties in the United States as listed in the 2005 Masterfile.
There were 120,732 that were US MD Grads, 9543 that were US DO Grads, and
7957 that graduated from international medical schools. Three different
independent variables were considered: total admissions from the county,
admissions of those not found in family medicine, and those found in family
medicine. These were each expressed as admissions per 100,000 per year or
the particular admissions total for each county multiplied by100,000
divided by 1970 population and multiplied by ten (class years). The
significance is one tailed. I am way out of my league in methods and
explaining methods with this use, but found it useful to explain the
differences. other thoughts appreciated.
Pearson Correlations Comparing Birth Origin County Characteristics and
Career Choice
1987 – 1996 Class | All | Admits | Non- | Admits | FM | Admits
Years | | | FM | | |
-------------------------+---------+----------+---------+-----------+---------+----------
1187 U.S. Counties and | Correl | p value | Correl | p value | Correl | p value
1969 or 1970 | | | | | |
Demographics | | | | | |
-------------------------+---------+----------+---------+-----------+---------+----------
1969 Per Capita Income | 0.160 | 1.4E-08 | 0.194 | 7.8E-12 | -0.028 | 0.17177
-------------------------+---------+----------+---------+-----------+---------+----------
Pop Per Sq Mile | 0.316 | 3.4E-29 | 0.358 | 1.5E-37 | 0.040 | 0.08244
-------------------------+---------+----------+---------+-----------+---------+----------
% College Educated | 0.372 | 1.5E-40 | 0.397 | 2.4E-46 | 0.146 | 2.3E-07
-------------------------+---------+----------+---------+-----------+---------+----------
% Professional & | 0.393 | 1.9E-45 | 0.406 | 1.2E-48 | 0.205 | 4.6E-13
Manager | | | | | |
-------------------------+---------+----------+---------+-----------+---------+----------
% HS Grads in County | 0.190 | 1.8E-11 | 0.191 | 1.8E-11 | 0.124 | 9.9E-06
About 620 counties had no admission. Those with 1 - 7 were excluded to
obtain this table. Including the counties with less than 8 admissions only
strengthened the correlations. Removing over 2000 counties and 7395
physicians in the counties with 1 - 7 admits decreased individual county
variations and insured a more realistic and conservative measure. Omission
of the top 20 counties with over 1000 admissions each did not change the
correlations. Direct measures such as parent income, education, and
occupation or student MCAT scores are likely to have much higher
correlations.
Those with the concentrations noted above and also born in counties or
cities with medical schools are going to have higher levels of medical
school admission, in any nation.
Those becoming family physicians are different than other physicians, less
likely to have professional parents, less likely to have college educated
parents, they depend upon broad distributions of education rather than
concentrations.
Consistently those choosing family medicine seem to have more individual
factors and less parent factors involved.
Various types of students decide for medicine at various time periods, also
shaped by background and parent factors. - sorry a jpg file
Diagram of Choice of Medicine by year of life is at
http://www.unmc.edu/Community/ruralmeded/awareness.htm
What we do not know is what happens to those that do not gain admission,
who usually were different in one or more significant ways from those
gaining admission. If some do not decide early and work longer to get
admitted at later ages, they are less likely to gain admission at all.
The characteristics of family medicine and rural born types and lower
income types are more like the bottom groups in older age at admission,
scores, barriers, and more. They are also far more likely to distribute.
Although distribution is important, the real issues involve cost and
quality.
Each group has a different barrier related to cost and quality, actually
each individual has various barriers. Some individuals have poor people
skills and they are unable to assess any people. Some have backgrounds that
make it difficult to care for those most different. Not admitting those
with poor people skills is a good idea. Changes that would encourage and
actually force all medical students to relate to those different than them
would likely improve cost, quality, and access. Others lack the structuring
and focus necessary.
Those rich or poor have various combinations of these strengths and
weaknesses. Many of those from lower and middle income groups cannot
overcome the lower scores and the lower levels of focus. Too much focus on
people can also make academics weaker. This tends to select out certain
types for a career such as medicine. Medicine can have more realistic
academic standards and clearly shift the admissions toward those with other
characteristics. When admitting only the narrow range with the top scores,
there is some level of baggage that goes with the narrow admissions. One of
the areas that seems to be lost is people skills abilities.
Health care costs are high because we fail in people interactions and
prioritize the wrong areas of care.
Patient Dimension - We fail to have people and patients that have the
education and socialization and structure to make the best health care
decisions.
Professional Dimension - We fail to have practitioners that have the
necessary people skills and awareness that should be the most important
prerequisites for a physician, or any service oriented professional from
teaching to nursing to public service to family practice.
Robert C. Bowman, M.D.
[log in to unmask]
well, I guess I can no longer play the martyr as well. AAMC accepted my
Rural Location in Recent US MD Graduates Using Logistic Regression for the
Physician Workforce conference. It is nice to be 1 for 24 rather than 0 for
24. But the rates will have to improve.
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