Rural Workforce Past, Present, Future
Rural Health Workforce Issues
Changes in birth to admission, admission, training, career choice, and policy (neglect) will result in grossly insufficient physician and non-physician workforce for rural areas. The US has violated Basic Health Access Principles by moving steadily more exclusive (highest income, most urban) in the children who do well enough for medical school, more exclusive in the medical students admitted, most exclusive entering the workforce from other nations, fewer family physician graduates that triple rural distribution above origins (the most important rural workforce since FM turns any origin or training into rural workforce), and policy that sends 90% of the health funding related to physicians to just 4% of the land area.
Steady changes not only reflect problems for basic health access, the changes reflect deteriorations of US education in lower and middle income areas, rapidly risking problems with rural and lower income males, and all segments of the population left behind.
Robert C. Bowman, M.D. rcbowman@atsu.edu
Physician databases such as the American Medical Association Masterfile can be used to determine the career and location decisions of physicians. When combined with census data and data from medical associations, this database becomes a powerful analytic tool. Birth origins data can be used to track physicians from birth to training to practice locations.
A confirmation of the value of Birth Origins illustrates the relationship of admission to distribution for Family Practice Rural Practice and Underserved Practice In each case, as the probability of admission increases for a type of physician, the probability of most needed health access decreases. The rate of family practice, rural, or underserved careers does not change. What happens is the more exclusive higher income and more urban children get more changes for admission to more schools and have backgrounds associated with top probability of admission. As they choose exclusive schools and exclusive careers, they end up in the most exclusive locations in 4% of the land area. They are following a design for birth to admission, admission, training, and policy that leaves 65% of the population in 4% of the land area behind.
Summary
The 293,978 physicians from the 1987 1999 class years of graduates from all medical school sources set the standards for distribution with 9.8% in rural locations, 3.0% in underserved urban zip codes, 2.7% in rural underserved locations, 29.7% in office based primary care, and 14.2% in family medicine or general practice. About 73% are found in major medical center locations. This is over 40% of the active physicians in the
Key questions can be asked in medical education regarding rural born admissions and rural .
A database coded with birth origins, shaped by workforce literature and association data, integrated with census data, and categorized by city, state, and county origins; medical school; type of medical school; career type; class year of graduation; age of graduates; and practice locations can help answer these questions.
Methods
The birth origins Masterfile was used as the database. About 97% of US MD Grads can be linked to a birth origin geographic location. Even international graduates can be linked to their country of origin or city of origin for an origin coding. Consistent relationships are found between origins, career choices, and US practice locations.
Birth origins, medical school training, and practice zip codes were compiled by categories such as birth income, birth geographic origin, instate birth compared to medical school, birth in a city or county with a medical school, younger or older age at medical school graduation, medical school, medical school type, medical school state and county location, career choice, and practice outcomes such as rural location, major medical center location, and underserved zip code. Physicians were also coded by the income level of their birth county. The counties were also divided into 4 quartiles of 50 million population each for per capita income level and physicians were assigned a birth county income quartile for 1969 census data, the approximate tim eof birth of the 1987 - 2000 graduates.
Medical schools were divided by state rural composition in 1992. The schools in states with 0 10%, 10 20%, 20 30%, 30 40%, 40 50%, and greater than 50% were compared. In addition schools with a rural mission, as defined by Rosenblatt,6 were compiled in an additional group for comparison. The rural born admissions for each group were compared over recent decades. Percentages of rural physicians, underserved physicians, family physicians, and office primary care physicians were generated for each medical school. Medical schools were also divided by types of admissions. These included Puerto Rican schools, Historically Black schools,
Physician birth origins were also compiled using 1993 Urban Influence Codes at the county level. Counties in this coding system were kept constant over the decades. The percentage of medical students from each type of county was compared to the percentage of population in the United States in each type of county. The works of Calvin Beale, Thomas Ricketts, Gary Hart, and others are acknowledged. The same United States Department of Agriculture sites were used to divide counties into agricultural, manufacturing, and other types of counties.
The allopathic graduates of medical schools in the
Additional studies are listed in this report. The Association of American Medical Colleges identified approximately 300 senior medical students as interested in rural practices of less than 2500 people. This cohort was compared to 13,000 non-rural interested seniors who responded to the 1995 Graduation Questionnaire.
Results
Setting the Standards for Comparison
The most complex challenges involving physician distribution involve separations of the various influences. Even before birth, parent factors influence career choice and distribution. Birth origins are a reflection of a starting point. Birth data allows the contributions of origins to be considered for location and career choice.
Rural Origins and Rural Location
Rural Location Factors
Logistic regression can help screen for the factors most related to rural location.
Logistic Regression Equations Characteristics of Rural Physicians Using Recent US Medical School Graduates 1987 - 1998 in 2005 Careers and Locations
|
|
B |
Std. Error |
Wald |
df |
Sig. |
Exp(B) |
95% Confidence Interval for Exp(B) | |
|
|
|
|
|
|
|
|
Lower Bound |
Upper Bound |
|
Intercept |
0.744 |
0.027 |
784 |
1 |
0.0000 |
|
|
|
|
Family Practice |
1.032 |
.016 |
3996 |
1 |
.00000 |
2.806 |
2.718 |
2.898 |
|
Rural Birth (RUCA) |
.963 |
.018 |
2765 |
1 |
.00000 |
2.621 |
2.528 |
2.717 |
|
Age over 27 MS Grad |
.292 |
.015 |
390 |
1 |
.00000 |
1.339 |
1.301 |
1.378 |
|
Allopathic Private School |
-.506 |
.018 |
797 |
1 |
.00000 |
.603 |
.582 |
.625 |
|
Reduced Contributions for Exclusive Training |
|
|
|
|
|
|
|
|
|
Enhanced Contributions for Origins Outside, Family Practice, Older Age |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Intercept |
3.150 |
.037 |
7251 |
1 |
.00000 |
|
|
|
|
Allopathic Public US |
.275 |
.015 |
344 |
1 |
.00000 |
1.317 |
1.379 |
1.356 |
|
Foreign Born US school |
-0.765 |
0.027 |
779 |
1 |
.00000 |
.465 |
.441 |
.491 |
|
Normal Age 26-29 |
-.298 |
.015 |
393 |
1 |
.00000 |
.742 |
.720 |
.764 |
|
Hospital Based Specialty |
-.360 |
.027 |
183 |
1 |
.00000 |
.697 |
.662 |
.735 |
|
Reduced contributions for Specialists, Normal Age, Exclusive Most Urban or Highest Income Origins |
|
|
|
|
|
|
|
|
|
Enhanced contributions for Public Schools |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Intercept |
4.331 |
.060 |
5222 |
1 |
|
|
|
|
|
Birth Top Quartile Income County |
-.199 |
.020 |
97 |
1 |
.00000 |
.819 |
.787 |
.852 |
|
Birth Med School County/City |
-.603 |
.016 |
1472 |
1 |
.00000 |
.547 |
.530 |
.564 |
|
Younger Than 26 |
-0.578 |
.037 |
249 |
1 |
.00000 |
.561 |
.522 |
.603 |
|
Top 20 MCAT School |
-.657 |
.021 |
948 |
1 |
.00000 |
.518 |
.497 |
.541 |
|
Subspecialty |
-.710 |
.045 |
255 |
1 |
.00000 |
.492 |
.451 |
.537 |
|
Each of the factors reduces rural distribution resulting in 3% rural. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Intercept |
-.049 |
.025 |
3.749 |
1 |
.053 |
|
|
|
|
Not Born MS County |
.316 |
.018 |
305 |
1 |
.00000 |
1.371 |
1.324 |
1.421 |
|
Age 33 or over at MS Graduation |
.380 |
.020 |
361 |
1 |
.00000 |
1.462 |
1.406 |
1.520 |
|
Lowest 30 US MD by MCAT |
.473 |
.015 |
994 |
1 |
.00000 |
1.605 |
1.559 |
1.653 |
|
Rural Born (RUCA) |
.746 |
.022 |
1143 |
1 |
.00000 |
2.108 |
2.019 |
2.202 |
|
Family Practice |
1.011 |
.016 |
3792 |
1 |
.00000 |
2.749 |
2.662 |
2.839 |
Family physicians are three times as likely to be found in rural locations, rural birth contributes at 2 times, and 30 60% increases are found for birth outside of a county with a medical school, older age, and graduates of lower ranking MCAT schools.
The themes of outside origins resulted in most needed health access, family practice choice multiplying health access, and less exclusive and more normal related to health access are all supported.
Changes in Admission - Social Organization Changes, Economic Changes, Political Changes
Declining Rural Admissions By Urban Influence Coding Birth origins in US physicians can be tracked to birth county and counties were coded using Urban Influence Coding (1993 Parker and Ghelfi). The percentage of the US physicians admitted from each county type was compared to the percentage of the US population in the county type for each time period 1940 to 2005. The most urban and most organized counties remained with admission ratios over 100%. The Urban Influence 2 county type maintained 100% or a 1 to 1 admissions ratio of medical students to population. The Urban Influence 7 counties separated from metro influences (many micropolitan) had the highest rural rates of admission and declined the least to 80%. Counties adjacent to metro counties but still with population more organized lost down to 50% or half as many admitted relative to population. Rural origins have a consistent 50% and declining probability of admission to medical school. The least organized counties with population spread throughout the county or counties adjacent to larger metro areas (compromised by adjacency) had the lowest admissions at 25%. Some caution is needed in the coding as some of the medical students may have listed the major metro city nearby as their birth origin which would result in fewer admitted from adjacent counties. The data on admissions changes is consistent with coding by race, ethnicity, and income levels. The foreign born medical students admitted to US medical schools were compared to foreign born population census figures. Over half are Asian. Asian medical students are about 22% of US medical students and Asian populations are about 4% for over 5 to 1.
Social Organization Outline with Race and Ethnicity Changes More detailed explanations regarding those inside of concentrations with higher ratios of admission and increasing probability of admission over time and those outside of concentrations (lower and middle income, first generation to college, lower and middle population density)
Declining Rural Admissions By Farming and Manufacturing Dependent The rural origin counties were coded by economic factors and compared over time. Separations are seen with fewer admitted in the 1990s. These are numbers, not rates, so declining rural population does represent some of this change, but the abrupt changes since the 1990s suggest much more than population decline involved likely economics, education, and other distributions.
Decling Rural Admissions For States Switching From Rural to Urban Dominant with some Preservation by Rural Mission States moving from majority rural to majority urban populations had the greatest decline in rural born admission in the past 30 years. Lesser declines were seen for states dominant rural or dominant urban. Medical schools with a mission for rural health had a lesser rate of decline compared to any group.
Older Age Graduates Demonstrate Rural Health Access Principles
Basic Proofs Regarding Admission and Distribution
Birth Origins Confirmation Graphics Family Practice Rural Practice Underserved Practice
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