Distributions of Loan Repayment

The 2007 Loan Repayment Awards to various states were recently announced to
help address needs for primary care and mental health in the United States.

These values were loaded into a preexisting state database and compared
with other variables related to health, primary care, physicians,
psychiatrists, shortage areas, and locations known to have challenges with
health access. not all states received funding, a complication for
analysis. Funding could also involve mental health or primary care. Only
the basic distribution to a state according to generic greater need could
be considered.

The correlations were weighted by the state percentage of the total United
States population.

Caution should be taken regarding such an exploratory approach as
correlations can have a variety of direct or indirect relationships. Also
there are other forms of funding at the state level, J-1 Visa waiver
obligations for international graduates, and public health sources that may
impact some results

Generally there is a potential theme to explore that lower and middle
income and rural populations did not appear to gain much, despite their
somewhat more significant needs. Also the states that distribute income and
education better, tend not to qualify for temporary grant funding efforts.
it takes more severe criteria to qualify, often in states that divide rich
from poor.

The first statistic is the Pearson Correlation (2 tailed) followed by the p
value and then the variable name and description.

Pearson Correlation     p Value     Variable
0.8514      0.0000      Public Assistance Percentage - States that had
greater percentages of state budget funding for public assistance obtained
more loan repayment funding. This may indicate greater ability to fund
programs, more state personnel devoted to such areas, or better skills at
obtaining funds. This compares to states that distribute education and
income better, have less need for public assistance, or are too poor to
fund such programs well. States such as North Carolina and Wisconsin have
long invested additional funding for maximal recruitment and retention,
infrastructure that helps in a number of grants and also the ability to
supervise the grants.

0.6733      0.0000      NIH Research Funds – States and their institutions
good at National Institutes of Health research funds are also good at loan
repayment funds.

0.6423      0.0000      Electoral 2000 – State electoral votes were related
to state loan repayment funding, even when weighted by percentage of the US
population in the state. The percentage of the population that voted was
also stacked the same way.

0.5499      0.0000      TopMCAT31per– States with the highest percentage of
physicians from top ranking medical schools (physicians graduating from the
top 31%) got more assistance. These highest ranking schools are the medical
schools that graduate the fewest generalists, primary care physicians,
family physicians, and physicians who are found in rural or underserved
locations. The graduates of these schools tend to arise from major medical
center origins (highest income, most urban, least diverse in a number of
measurements, and most connected to medical schools by parents and
geographic proximity. Those with 30 years of connections are not likely to
leave the major medical center lifestyle to live or practice in very
different environments. Only the most invasive health policies have changed
their minds in areas such as increased choice of family medicine (1995 –
1997 class years). The United States is moving toward more medical students
admitted from major medical center origins, more with higher MCAT scores,
more with higher income parents, and fewer with middle class, lower class,
rural, and underserved origins.

0.4733      0.0003      States with greater Medicaid eligibility have
greater loan repayment funding.

0.4552      0.0005      OffPCnotFP – States with a higher percentage of
internal medicine and pediatric generalists were able to obtain more
funding. About 70% of office based internal medicine and pediatric
physicians are located in major medical centers with 75 or more physicians
at a zip code. Family physicians are much more likely to be found outside
with only 50% in major medical center locations. States with more
concentrations of physicians were rewarded with more loan repayment
funding.
0.4336      0.0009      OffPCper - The overall primary care percentage
including office based forms of IM, PD, and FPGP was related to greater
loan repayment funding. As seen above, the funded primary care portion most
connected with loan repayment involved non-family physicians. States with
more family physicians did not receive greater funding.
0.4270      0.0011      MMCper07 - States with a higher percentage of
physicians concentrated into major medical center zip code locations were
rewarded with more loan repayment funding.
-0.4051     0.0019      rural92 – Loan repayments did not go to states with
greater percentages of rural population as of 1992 data. It is important to
remember that this was weighted for percentage of state population so that
population-related values were less likely to skew the results.
-0.4046     0.0020      perChildrenBothParentsWork – Funding did not go to
states with children with more working parents, again a middle to lower
middle income measure.
0.3925      0.0026      genIMprop87t99mf - States with a higher proportion
of office based general internal medicine compared to all found in internal
medicine careers did receive more loan repayment funding. States with
slightly lower levels of specialty internal medicine compared to primary
care did receive more funds. Of course with less than 30% remaining in
office based internal medicine, with declines in nurse practitioners below
50% and less than 40% of physician assistants remaining in primary care,
with further declines expected and funding going to the states with the
fewest family physicians (90% remaining in primary care and holding, but
lower numbers choosing FM), it may be difficult to find remaining primary
care to fund.
-0.3890     0.0029      HPSA rank – Loan Repayments decreased with
increased number of HPSA areas.
0.3889      0.0029      medhouseinc05 – Loan Repayments increased with
greater state income.
-0.3750     0.0040      prRuralBottomIncomeQuartile – Loan Repayments
decreased with more physicians practicing in Rural Locations in the Bottom
US quartile of county income.
-0.3736     0.0041      PRurbbottomquart - Loan Repayments decreased with
more physicians practicing in urban bottom income quartiles.
0.3387      0.0086      Medicaid Scope – Loan Repayments increased with
increased scope of services.
-0.3366     0.0090      Homeownerrate – Loan Repayments decreased with
increased home owner rates.
0.3334      0.0096      Unemployment – Loan Repayments decreased with
increased unemployment.
0.3191      0.0127      Medicaid Overall Evaluation  – States with better
rated Medicaid programs overall received more loan repayment funding, again
a possibility that those who are more organized do better in such
allotments or possibly in all of the various temporary grant funded
programs involving child development, education, public security, and
health care. This would of course make it appear that funding was provided,
but would make it more likely to appear that government programs would
fail, since the funding was not going where it most was needed and since
the funding was not coordinated together for maximal impact. (Medicaid
evaluations)
0.2923      0.0208      SuperMMCper – States with a greater percentage of
physicians packed into zip code locations with 200 or more physicians
obtained greater loan repayment funding.
-0.2812     0.0252      Perdisenfran – States with higher percentages of
disenfranchised population obtained lower levels of funding.
-0.2749     0.0280      Quality United Health Rank – States with lower
quality rankings obtained more funding.
-0.2740     0.0284      prPredomHisp - States with more physicians
practicing in predominantly Hispanic Counties obtained less funding.
0.2656      0.0326      Health Cost Estimate – States with higher health
care costs received more loan repayment funding.
0.2489      0.0423      State Budget Higher Ed – States with more spent on
higher education received more loan repayment funding
-0.2471     0.0435      Employ Ratio 05 – States with higher employment
received more loan repayment funds.
-0.2221     0.0626      Born whole county primary care – States where more
physicians are born in whole county primary care shortage areas receive
less funds.

In the rest of the comparisons the expected correlation for a loan
repayment distribution would be positive or at least a trend toward loan
repayment distribution to states that have difficult physician location
factors (rural, low income, high minority, shortage area, child well being,
family practice physicians, general practitioner levels, underserved
populations, or psychiatrists). This was not the case.

-0.1866     0.0996      Underserved per – States with a greater percentage
of physicians in underserved areas receive less loan repayment funding.
-0.1863     0.1000      MarriedCoupleBothWorkingper05  – Funding did not go
to states with children with more working parents, again a middle to lower
middle income measure.
-0.1798     0.1081      Practice in Rural Predominantly Black County
-0.1571     0.1405      Voting Rate
-0.1569     0.1409      Practice in an Urban Whole County Shortage Area
-0.1553     0.1434      Practice in any Predominantly Black County
-0.1436     0.1624      Practice in a Whole County Shortage Area
0.1279      0.1906      % of working poor in a state
-0.1209     0.2041      Practice in a Rural Whole County Shortage Area
-0.1129     0.2199      State Percentage in Poverty 2005
-0.1038     0.2390      Child Poverty % in 2005
-0.1035     0.2395      Practice in any Predominantly Native County
-0.1035     0.2395      Practice in a Rural Predominantly Native County
-0.0993     0.2486      Child Well Being Score
0.0971      0.2534      Gini Index Household Income 1999 – Not related to
inequity in income distribution.
-0.0876     0.2747      Teen pregnancy rate
-0.0632     0.3331      Underserved Not in Major Medical Centers
0.0517      0.3621      General Practitioners per10000 Area Resource File
2003
0.0405      0.3911      Underserved Even in a Major Medical Center
(inclusive measure that allows over 75 physicians at a zip code to be coded
underserved when sharing a shortage designation)
-0.0266     0.4281      Office FP percentages of total physicians in a
state
-0.0258     0.4302      Practice in a rural Predominantly Hispanic County
0.0197      0.4466      Medicaid Percentage
0.0056      0.4847      Percentage of Psychiatrists of all types in the
State

Robert C. Bowman, M.D.
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