Most Needed Health Access - Rural Location

Robert C. Bowman, M.D.

Using the Principles of Health Access, four independent variables can be loaded to compared to the dependent variable of rural practice location. In this case the rural physicians were RUCA defined practice locations as of the 2005 Masterfile. These were active rural physicians from a complete population of physicians that graduated from any medical school from 1987 – 2000. This is a cross section that has had time to distribute to representative careers and locations rather than a distorted group in their first practice shaped by transitions or obligations.

The independent variables include birth origins typically linked to birth county demographics, career choice, training type, and age at medical school graduation.

Lower or middle income origins, lower or middle population density origins, and the more normal and less than most exclusive origins are associated with 1.5 to 3 times odds ratios of rural practice location. Those most associated with lower concentrations (toward the rural or toward the lower income dimension) have the highest probability of rural practice location. This is also problematic as each of these origins is associated with lower probability of medical school admission as well as decreasing percentages admitted to US medical schools.

A great failure in workforce studies is only to consider rural origins or lower income origins. At the opposite end of the spectrum is most urban typically combined with highest income origins. About 33 counties have the top population density origins with top income as well as greatest concentrations of physicians, medical schools, and graduate medical education. The most urban origins that are most urban and highest income county origins are associated with 0.5 odds ratios or half of the probability of rural location.

Those familiar with cardiac risk factors such as smoking, hypertension, and cholesterol can easily translate the findings. These factors increase the probability of adverse cardiac events by 1.2 to 2 times. Origins, age, and training increase the “risk” of rural practice location by 1.3 to 2 times. Choice of family medicine results in 3 times odds ratios of rural location. Since the other three factors are loaded in the same equation, the tripling effect remains with controls for birth origins, age, and training type.

Odds Ratio Probability of Rural Practice Location

	Exclusive	Normal	Least Exclusive

Origin	Highest income, most urban, foreign born, Asian	Upper middle income or population density	Lower or lower middle income, lower or middle population density
Origin	0.5	1.2	2 to 3

	Younger than 26	26 - 27	28 to 32 years
Age at Graduation	0.7	0.8 – 0.9	1.2 – 1.6

	Subspecialty or Hospital Support Specialty	Office Internal Medicine Office Pediatrics	Family Medicine
Career	0.4 – 0.6	1.1 – 1.2	3 – 3.5
	3 – 4% rural and usually in rural zip codes with 75 – 500 docs	4 – 8% rural 6% avg But leaving primary care and moving to specialty	14 – 30% rural 20% avg. Remaining Steady

	Allopathic private, Top 20 MCAT schools	Allopathic public or Osteopathic	Rural Focused Health Access Schools such as Duluth and West Virginia School of Osteopathic
Training	0.5 – 0.6	1.2 – 1.6	1.8 – 2
Cumulative Effect of Origins, Career Choice, Age, and Training	3 – 4% rural	8 – 20% rural	30 – 40% rural
	Less likely to change as exclusive origins, youngest ages, few or no FP, exclusive training	But decreasing due to changing origins and decreasing FP choice with some training changes. Score increases and parent income increases and declining rural, lower income, and middle income admissions are an indicator of change in origins	Some change in origins and family practice
	Lowest rural %, lowest underserved %, lowest primary care %, lowest family practice %	10 times more rural primary care compared to a top 20 MCAT Medical School Graduate	64 times more rural primary care compared to a top 20 MCAT Medical School Graduate

The exclusive schools also admit, train, and graduate the most exclusive. More normal in origins, career choice, and training results in entirely different outcomes. Schools such as Duluth or West Virginia Osteopathic admit the least exclusive students from rural and lower and middle income origins or the least densely populated urban origins, admit the oldest students, graduate the most family physicians, and train in the least exclusive environments with the least exclusive physicians.

1987 – 2000 Graduates	Duluth	WVSOM	University of Washington	Cornell, Columbia, Yale Harvard
% Rural Outcomes	30%	42%	15%	3 - 4%
Standard Primary Care Years per Grad	16	14	8	2 - 3
Rural Standard Primary Care Years per grad	6.4	6 – 7	1 - 2	0.1
Instate Office Primary Care	40%	16%	23%	2 – 6%

% FM Graduates	40 – 50%	38%	10%	2%
% Rural Origin	40%	40%	19%	5%
% Older	30%		24%	17%
Mean Age at Graduation	29	32	29.2	28
Born in Med School County	41%	44%	58%	80 – 86%
Instate Born	60%	70%	42%	20 – 30%
MCAT score average of matriculants	9.2	8	10.4	11.3 - 12
Foreign origin	3%	2%	10%	15 - 18%
Asian	2%	3%	10%	15%
Researchers 1965 - 1994	0%	0%	3%	6 - 10%
Practice in Super Center with 200 or more docs	27%	20%	42%	62 - 67%

2009 Class Year Estimates	Duluth	WVSOM	University of Washington	Cornell, Columbia, Yale Harvard
Expected % Rural Outcomes	25%	30%	8%	2%
Expected Rural Outcomes for Primary Care Grads	35%	40%	15%	4%
Standard Primary Care Years per Graduate	13	9 - 10	6	1.5
Rural Standard Primary Care Years per grad	4	4	0.6	0.06
Estimated Rural Origin	30%	20%	10%	3%

One of the great distractions of bivariate studies is the relationship of rural origin to rural practice location. By focusing on this very small part of the solution for rural workforce, many other more important solutions are minimized. As an illustration, caffeine consumption has been associated with various cancers until studies correctly identified the smoking factor when proper controls were included instead of a simple bivariate caffeine to cancer relationship.

Rural origins appear to be most important, but rural origin physicians also tend to be older and also are more likely to choose family medicine. In addition osteopathic or allopathic public schools are more likely to have rural origin, older, and family practice graduates. Bivariate studies comparing rural origins to rural outcomes without considering these interactions magnify the single dependent variable chosen whether rural origin, type of training, or family medicine career choice.

With only 6% of the physicians entering the workforce from rural origins and with only 18% of rural origin physicians found in rural practice (compared to 8% for urban origin), it is easy to see why other solutions are more important. Older graduates and family physicians that are urban origin have greater rural distribution and have substantially greater numbers. Only the most exclusive medical education fails in rural workforce production as allopathic public and osteopathic graduates have greater than average rural distribution (or at least did have in the 1990s policies supporting rural, underserved, and family medicine careers at higher levels).

With multiple variables added, the stability of the equations can be illustrated. When new variables are added to most logistic regression equations, one or more other variables lose significance. This is common when small numbers of subjects are involved in a research study. But when studies include complete populations of hundreds of thousands of physicians, the problems of sampling bias and small numbers are minimized. Various factors can be compared to one another or within one another as in younger versus older age graduates.

Greater understanding of most needed health access is required. Few understand that most of the United States population is distant from the concentrations of health services generated under the current national design. With 75% of physicians and 90% of the funding related to physicians concentrated in 3400 zip codes, the 65% of the population outside of these few zip codes is left behind.

There is no such representation in workforce studies or reports to Congress demonstrating Why Physician Workforce Needs New Tools and New Perspectives.

Rural populations and rural workforce outcomes can use various geographic coding systems, population density, or coding by physician concentrations. It would seem to be common sense that physicians distribution by concentrations of physicians but studies commonly utilize concentrations of people (urban, rural; metro, non-metro) or concentrations of income (highest, higher, poverty). Health care coverage is a consideration that involves geographic considerations, income factors, and employment. A consideration of physicians concentrating in concentrations of physicians is helpful, particularly when 75% of physicians are found practicing in zip codes with 75 or more physicians where 90% of the health resources related to physicians are directed according to US health care design and policy.

Logistic Regressions Involving Rural Practice Location

Parameter Estimates	% of Docs	B	Std. Error	Wald	df	Sig.	Exp(B)	95% Confidence Interval for Exp(B)
All Rural Physicians(a)	9.5%							Lower Bound	Upper Bound
Intercept		0.159	0.024	42.68	1	6.46E-11
Older than 29 Yrs at MS Grad	20.9%	0.289	0.014	431.7	1	7.03E-96	1.336	1.300	1.373
Family Medicine	13.8%	0.920	0.014	4495.8	1	0.00E+00	2.509	2.442	2.577
Rural Birth Location	8.4%	0.693	0.021	1081.9	1	2.82E-237	1.999	1.918	2.084
Born Bottom Income Quartile County	9.6%	0.238	0.020	135.8	1	2.22E-31	1.269	1.219	1.321
Born in a County/City with a Medical School	55.6%	-0.185	0.013	211.36	1	6.95E-48	0.831	0.811	0.852
Bottom 30 Medical Schools By MCAT	31%	0.410	0.012	1112.2	1	7.4E-244	1.506	1.471	1.543

Generally four factors are loaded with age, career choice, training, and an origin factor. With fewer variables the 2 or 3 variables acquire greater odds ratios as is common when understanding is limited.

More variables can be loaded for origins and each variable still retains a contribution. This tends to confirm multiple dimensions of origins as related to health access rather than a single variable such as income or geographic origins or race or ethnicity or proximity to concentrations of physicians.

Probabilities of rural practice location (shaded column) are generated along with 95% confidence intervals. Physician distribution to rural areas is more than just rural origins. Actually family medicine choice contributes more to rural workforce and there are far more family medicine graduates compared to rural origin physicians entering the workforce. The other variables (too many loaded in the above) provide more than adequate controls to assure a valid result for the major factors (shaded rows). Older age at medical school graduation, lower income origins, and graduation from a lower MCAT medical school (not a special admission school such as in Puerto Rico, Osteopathic, Historically Black, Early Admission, or Military) also increase contributions to rural and to rural underserved locations. Highest status origins, birth in a city or county with a medical school, younger age, and graduation from a higher ranking MCAT school are related to lower levels of physician distribution to rural areas.

A focus on higher concentrations involving preparation of medical students, medical school admission, physician training, and health policy will continually be seen as an impediment to physician distribution and most needed health access in primary care, rural, and underserved components.

In regression equations involving ever more challenging rural locations, family medicine contributions increase to 3.2 times odds ratios for rural areas outside of major medical centers, 3.95 for rural whole county primary care shortage areas, 4.3 times for isolated rural locations, and 4.6 times for isolated and underserved locations. Even with dependent location variables including predominantly African-American, Hispanic, or Native counties that are also rural counties (arguably the most challenging health care access areas involving 6 million people in the nation), family medicine career choice doubles location.

Current trends indicate declining rural contributions from international medical graduates (declining J-1 Visa Waivers, short duration, rapid decrease in primary care), physician assistants (1 percentage point per year in rural locations), nurse practitioners (also departing the family practice mode that contributes above average to rural workforce), pediatricians,^{2, 3} and internists (declines in primary care retention). These physicians and practitioners have become less dependable sources of primary care and rural health access. These trends only increase the need for family physicians, the best trained family physicians, the most specifically trained family physicians for needed health access, and the family physicians with the characteristics related to the highest levels of long term rural retention. Family practice physician assistants could meet these needs as they have 30% rural location rates, but departures from the family practice mode during training, at graduation, and each year after graduation defeat rural workforce for physician assistants.

The nation’s workforce is moving a different direction toward combinations of concentration and away from most needed health access. Family medicine itself is moving a different direction. It continues to look internally for problems. Throughout this web site the consistency of family medicine with regard to most needed health access will be demonstrated.

It is not family medicine that needs to change. The United States needs to change in birth to admission, admission, training, and health policy to graduate more family physicians. It is the only way that the nation will address cost, quality, and access although once again it is not family physicians that will make the difference.

The changes in children that will result in more lower and middle income children doing well will improve graduation rates of family physicians as well as improve health care quality. Each of the following will improve the graduation rates of family physicians, but will result in much needed improvements in even more important areas.

Improvements in the lower and middle income children with higher probability of family medicine choice - Children who do better in the early years of life do better in education, jobs, and the most important decisions such as when to access health care and when not to access health care.

Changes in medical education to admit more who will become family physicians as well as health access schools – The admission and training changes most likely to increase family medicine graduates also rural and underserved workforce, result in pediatric and internal medicine graduates most likely to remain in primary care, contribute to care of the elderly, address mental health, increase women’s health workforce, and address other needed career choices. The best example is Duluth with a complete health access family physician focus and the ability to meet all of these needs at much higher levels. Medical education focused on the exclusive can address only the exclusive careers and locations.

Medical students must trust health policy to be able to choose most needed health access careers such as family medicine, rural careers, or careers serving the underserved - Changes in health policy to shift funding to lower and middle income populations for basic health care and to shift funding to primary care also help restore health care infrastructure for lower and middle income people, improve economics and jobs for lower and middle income people, and increase the efficiency and effectiveness of health care.

A focus on lower and middle income children also is a focus on more and better teachers, nurses, and public servants as these are the other essential infrastructure required by the nation that also require better lower and middle income children for optimal performance at minimal cost.

There is no waste in a focus that results in more of the physicians most needed for health access. The benefits are far more than physician and health system benefits.

A narrow perspective of rural focus in admission misses the many different types of physicians found in rural areas in higher concentration including those who are older (20%), those born outside of medical school cities and counties (30%), physicians with lower and middle income origins (30%), physicians from schools with lower MCAT scores (30%), and physicians trained in specific types of schools and programs (full scope, procedural focus) who are likely to be comfortable only in practice in a smaller or rural location where they can use all of their training and preparation.

When closer examination of rural workforce is needed in the area of primary care, the Standard Primary Care year measuring tool can be combined with the percentage found in rural practice to obtain a Rural Standard Primary Care Year contribution. The advantage of a family practice form with enhanced rural distribution is seen.

Graphic of Rural Standard Primary Care Years with 5 – 6 Rural SPC years for family physicians and 0.2 to 0.6 for NP, PA, IM.

More pediatricians fails for rural primary care as pediatricians have been moving away from rural locations for decades. More internal medicine graduates is a total failure for rural health access as internal medicine remains only 10% in primary care and less than 10% in rural locations. Also internal medicine gradutes tend to move toward hospital and hospitalist careers and away from basic health access. Nurse practitioner and physician assistant contributions are also falling in primary care and in rural location as nurse practitioners and physician assistants depart family practice with each passing year. Only the family practice broad generalist mode is associated with above average rural location rates. Family practice physician assistants have 30% rural location rates, 6 - 7 times greater Community Health Center location rates, and 30 times the federally qualified rural health clinic location rates compared to non-family practice physician assistants. Only 20% of physician assistants began careers in family practice in 2008, an indicator of declines to come as the average physician assistant is 25% in family practice.