Exclusivity Index Table
Comparisons include Exclusive Birth Origins, Exclusive Career Choices, Exclusive Medical Schools and Training, and Exclusive Practice Locations
Themes: The Most Exclusive in Origin, the Most Exclusive in Career Choice, and the Most Exclusive in Training are all related to half of the probability of needed health access. When combined together in so many physicians, the result is the lowest rural, the lowest underserved, and the lowest basic health access primary care of all. See this theme confirmed in multiple comparisons.
A Higher Exclusivity Index for a Physician Career is a Measure of the Ratio of Most Exclusive to More Normal. Most Exclusive Is Birth Origin in a County with Over 2500 People Per Square Mile and More Normal is a county with less than 125 PPSM. The Index is a comparison with family physicians that only increase 55% across these origins. Family medicine, rural, and underserved careers are the only ones with constant levels arising from the population. The family practice rate is about 1 per 100,000 per class year for 1990s graduates as compared to 1970 birth origins.
More average rural or urban values were selected. Also the following represent 2005 career choices. It is important to remember that those specializing are more exclusive in origin and leave the less exclusive behind as seen in general internal medicine, general surgery, etc. The first column lists the percentage increase across the span of origins, the second column is the specialty as listed in the 2005 Masterfile self-designated by the physician, the third column is the Exclusivity Index comparison to family meeting at 55% increase, the data for the origins from each county is listed in number per 100,000 per class year.
|
Increase Across Origins |
1987–2000 US Med School Physicians (n = 316,000) |
Exclusivity Index |
PPSM 1 - 62 |
125 - 250 |
250 - 500 |
500 - 1000 |
1000 - 2500 |
2500 and up |
US Born |
Asian Born |
Foreign Not Asian |
|
55% |
Family Medicine |
1.00 |
0.862 |
0.953 |
1.092 |
1.115 |
1.085 |
1.335 |
1.057 |
1.596 |
0.483 |
|
195% |
Pathology |
3.55 |
0.078 |
0.119 |
0.142 |
0.140 |
0.155 |
0.229 |
0.144 |
0.210 |
0.068 |
|
203% |
General Surgery |
3.70 |
0.146 |
0.215 |
0.239 |
0.274 |
0.314 |
0.442 |
0.264 |
0.738 |
0.200 |
|
218% |
Anesthesia |
3.98 |
0.213 |
0.331 |
0.379 |
0.405 |
0.422 |
0.677 |
0.385 |
1.025 |
0.228 |
|
239% |
Obstetrics-Gyn Careers |
4.36 |
0.229 |
0.325 |
0.403 |
0.454 |
0.516 |
0.776 |
0.442 |
0.952 |
0.334 |
|
253% |
US Born Admission Rate |
4.62 |
3.587 |
5.424 |
6.294 |
7.140 |
7.941 |
12.672 |
6.936 |
17.314 |
4.099 |
|
277% |
Neonatal Perinatal |
5.06 |
0.014 |
0.026 |
0.031 |
0.033 |
0.032 |
0.053 |
0.033 |
0.045 |
0.010 |
|
288% |
Emergency Medicine |
5.26 |
0.181 |
0.296 |
0.348 |
0.406 |
0.468 |
0.701 |
0.387 |
0.616 |
0.206 |
|
289% |
Orthopedic Careers |
5.27 |
0.125 |
0.220 |
0.232 |
0.296 |
0.316 |
0.484 |
0.271 |
0.419 |
0.117 |
|
307% |
Internal Med (general) |
5.59 |
0.390 |
0.570 |
0.690 |
0.841 |
0.947 |
1.588 |
0.815 |
2.968 |
0.597 |
|
309% |
Otorhinolaryngology |
5.64 |
0.046 |
0.076 |
0.080 |
0.113 |
0.122 |
0.190 |
0.106 |
0.329 |
0.056 |
|
322% |
Pediatrics |
5.86 |
0.243 |
0.421 |
0.492 |
0.555 |
0.672 |
1.024 |
0.552 |
0.909 |
0.279 |
|
341% |
Dermatology |
6.21 |
0.048 |
0.086 |
0.083 |
0.120 |
0.129 |
0.213 |
0.110 |
0.291 |
0.066 |
|
346% |
Diagnostic Radiology |
6.31 |
0.148 |
0.268 |
0.298 |
0.339 |
0.394 |
0.661 |
0.341 |
1.147 |
0.182 |
|
346% |
Psychiatry Careers |
6.32 |
0.157 |
0.244 |
0.320 |
0.331 |
0.388 |
0.702 |
0.348 |
0.442 |
0.161 |
|
389% |
Urology |
7.09 |
0.037 |
0.068 |
0.079 |
0.100 |
0.111 |
0.181 |
0.100 |
0.300 |
0.061 |
|
391% |
Ophthalmology |
7.13 |
0.071 |
0.129 |
0.135 |
0.183 |
0.182 |
0.350 |
0.172 |
0.685 |
0.101 |
|
420% |
Endocrinology |
7.66 |
0.014 |
0.026 |
0.030 |
0.030 |
0.034 |
0.070 |
0.034 |
0.107 |
0.023 |
|
464% |
Neurosurgery |
8.46 |
0.019 |
0.034 |
0.040 |
0.052 |
0.055 |
0.107 |
0.053 |
0.197 |
0.037 |
|
468% |
Plastic Surgery |
8.54 |
0.024 |
0.046 |
0.056 |
0.060 |
0.071 |
0.134 |
0.068 |
0.224 |
0.050 |
|
473% |
Physical Medicine |
8.63 |
0.037 |
0.064 |
0.081 |
0.096 |
0.101 |
0.212 |
0.099 |
0.309 |
0.046 |
|
476% |
Nephrology |
8.68 |
0.018 |
0.029 |
0.044 |
0.043 |
0.054 |
0.103 |
0.050 |
0.247 |
0.043 |
|
476% |
Vascular Surgery |
8.68 |
0.009 |
0.021 |
0.021 |
0.030 |
0.029 |
0.051 |
0.032 |
0.084 |
0.019 |
|
492% |
Neurology |
8.98 |
0.038 |
0.081 |
0.092 |
0.102 |
0.134 |
0.224 |
0.111 |
0.263 |
0.073 |
|
493% |
Cardiology |
8.99 |
0.066 |
0.123 |
0.136 |
0.151 |
0.181 |
0.389 |
0.167 |
0.752 |
0.118 |
|
519% |
Pediatric Cardiology |
9.47 |
0.007 |
0.014 |
0.013 |
0.016 |
0.024 |
0.045 |
0.024 |
0.042 |
0.009 |
|
579% |
Gastroenterology |
10.55 |
0.032 |
0.056 |
0.072 |
0.085 |
0.098 |
0.218 |
0.092 |
0.424 |
0.060 |
|
580% |
Infectious Disease |
10.58 |
0.018 |
0.042 |
0.046 |
0.053 |
0.063 |
0.121 |
0.056 |
0.125 |
0.048 |
Those arising equitably from all origins include family physicians (1 per 100,000 per class year), rural physicians (0.7), and physicians in underserved locations (0.6). Those most likely to gain admission are most likely to have exclusive origins, exclusive top MCAT medical schools, and exclusive specialty careers.
The physicians can also be tracked to birth origins and compared across practice locations. A rural bias is noted since a marker of population density is used. Parent income or student MCAT score would be a more neutral exclusivity marker. Physicians arising from concentrations of people are more likely to be found in concentrations of people, physicians, and more.
|
|
|
|
Birth County Origins Admissions per 100,000 per class yr |
Admit Rate | |||||||
|
|
Increase Across Origins |
Exclusivity Index |
1-62 PPSM |
125-250 |
250-500 |
500-1000 |
1000-2500 |
2500 Up |
US Born |
Asian Nation |
Not Asian Nation |
|
RUCA Coding |
|
|
|
|
|
|
|
|
|
|
|
|
Urban Practice Location |
329% |
6.00 |
2.73 |
3.72 |
4.57 |
5.42 |
6.25 |
7.13 |
11.70 |
16.37 |
3.77 |
|
Large Rural Practice |
11% |
Rural Bias |
0.46 |
0.53 |
0.49 |
0.45 |
0.48 |
0.42 |
0.51 |
0.55 |
0.18 |
|
Small Rural Practice |
-15% |
Rural Bias |
0.21 |
0.19 |
0.15 |
0.18 |
0.17 |
0.15 |
0.18 |
0.14 |
0.06 |
|
Isolated Rural Practice |
-15% |
Rural Bias |
0.09 |
0.07 |
0.07 |
0.07 |
0.07 |
0.07 |
0.08 |
0.03 |
0.03 |
|
Physician Distribution by Concentration Coding |
|
|
|
|
|
|
|
|
| ||
|
Marginal Urban Practice |
225% |
4.10 |
0.52 |
0.67 |
0.80 |
1.03 |
1.07 |
1.17 |
1.71 |
2.24 |
0.57 |
|
Urban Underserved |
208% |
Outlier <62 |
0.14 |
0.20 |
0.23 |
0.25 |
0.29 |
0.29 |
0.42 |
0.68 |
0.22 |
|
Marginal Rural Practice |
5% |
Rural Bias |
0.31 |
0.29 |
0.29 |
0.29 |
0.27 |
0.27 |
0.33 |
0.27 |
0.10 |
|
Rural Underserved |
-23% |
Rural Bias |
0.27 |
0.27 |
0.21 |
0.21 |
0.24 |
0.18 |
0.20 |
0.22 |
0.09 |
|
Major Center 75-199 |
231% |
4.21 |
1.01 |
1.30 |
1.55 |
1.75 |
1.93 |
2.15 |
3.33 |
4.95 |
1.10 |
|
Super Center 200 up |
420% |
7.66 |
1.24 |
1.77 |
2.20 |
2.58 |
3.14 |
3.70 |
6.46 |
8.69 |
1.94 |
|
Military Zip Practice |
114% |
2.08 |
0.09 |
0.11 |
0.14 |
0.17 |
0.18 |
0.17 |
0.20 |
0.22 |
0.06 |
|
Medical School Type for US Birth Origin Graduate of the Following School |
|
|
|
|
|
|
| ||||
|
Allopathic Private School |
658% |
12.00 |
0.72 |
0.97 |
1.38 |
1.62 |
2.04 |
2.71 |
5.45 |
7.28 |
1.67 |
|
Allopathic Public School |
132% |
2.41 |
2.55 |
3.27 |
3.60 |
4.09 |
4.45 |
4.60 |
5.90 |
9.06 |
2.16 |
|
Osteopathic Private |
291% |
5.31 |
0.18 |
0.22 |
0.24 |
0.33 |
0.32 |
0.34 |
0.70 |
0.75 |
0.20 |
|
Osteopathic Public |
92% |
1.68 |
0.09 |
0.10 |
0.13 |
0.16 |
0.18 |
0.12 |
0.18 |
0.22 |
0.06 |
|
International n=1347 |
2124% |
38.73 |
0.01 |
0.01 |
0.02 |
0.02 |
0.03 |
0.05 |
0.17 |
|
|
|
Caribbean n=1920 |
488% |
8.90 |
0.03 |
0.03 |
0.04 |
0.05 |
0.07 |
0.08 |
0.17 |
|
|
|
Central American n = 689 |
646% |
11.78 |
0.01 |
0.01 |
0.01 |
0.02 |
0.02 |
0.02 |
0.07 |
|
|
|
Allopathic US Medical Schools by Matriculant MCAT Scores 2000 - 2003 |
|
|
|
|
|
|
| ||||
|
MCAT 10.5-12 |
655% |
11.91 |
0.37 |
0.54 |
0.72 |
0.94 |
1.07 |
1.51 |
2.77 |
1.69 |
0.82 |
|
MCAT 10-10.5 |
325% |
5.91 |
0.62 |
0.83 |
1.13 |
1.01 |
1.23 |
1.64 |
2.64 |
1.88 |
0.76 |
|
MCAT 9.5-10 |
409% |
7.44 |
0.75 |
1.13 |
1.47 |
1.59 |
1.92 |
2.10 |
3.80 |
2.60 |
1.17 |
|
MCAT 9.25-9.5 |
76% |
1.38 |
0.61 |
0.75 |
0.70 |
0.89 |
1.17 |
0.87 |
1.07 |
1.14 |
0.43 |
|
MCAT 8.5-9.25 |
-20% |
-0.36 |
0.68 |
0.76 |
0.64 |
0.99 |
0.58 |
0.58 |
0.55 |
0.89 |
0.23 |
Physicians can also be linked to birth origins categorized by individual medical schools or types of medical schools. In this case the ranking of 2000 - 2003 MCAT scores of matriculants was used.
To understand rural workforce, primary care, health access - the concepts of exclusive concentrations must be understood. Much more about epidemiology and public health needs review.
To obtain optimal results from control of hypertension, it would seem to involve addressing the highest risk populations. While this is better for some individuals, the overall result is best for populations by lowering all blood pressures by a small fraction.
FP is able to convert any birth origin to greater than 10% rural workforce, the national average. That is the power of tripling. Usually the family medicine contribution boosts rural location rates past 20%. It is only the most exclusive origins that attend the most exclusive schools that have lowest rural contributions as family physicians. There are contributions in underserved dimensions for all family physicians.
FP can increase to satisfy all primary care rural needs because of this, especially when combined with appropriate admission, medical school training, and FP training. FPs can also, with the right training and policies, extend women's health, mental health, ER, inpatient, basic procedures, basic orthopedics, minor surgery, and even anesthesia as noted in Canada and Australia.
A national design that favors the above can actually meet the needs of every specialty and location. The current national design is suitable mainly for zip codes with 200 or more physicians.
When a national design fails to include the needs of 100% of the nation, it will always fail.
National designs should always err toward primary care, public health, and health access. Once those who have little awareness of those 50 - 55% left behind gain full control, soon 65% are left behind.
One of the huge advantages of a Duluth design or any design admitting normally, training normally, training hands on, and training with broad scope physicians is meeting all of the difficult workforce areas - rural general surgery, rural pediatrics, neonatology, women's health, geriatrics, rural primary care, and underserved primary care (except mental health which also needs a complete redesign). A design favoring Duluth and health access still supplies zip codes with 200 or more physicians, urban specialists, and urban primary care in saturations of primary care, but at lower ratios. Schools such as Duluth are universal workforce donors. Allopathic private top 20 MCAT schools have graduates that supply a very narrow range of workforce needs. Currently this fits the US health care design, but just as surely this design will have to change.
In the past century, the US has always been able to create subspecialists from more general categories, and often with advantages in such transitions (better teaching, better awareness). with a fully subspecialized training situation, there is no way to return to more generalized and little understanding of how the pieces fit together for best health care delivery.
When nations focus on exclusive origins, exclusive admissions, exclusive training, exclusive careers, and all of this is rewarded by exclusive health policy and the leaders are born, bread, prepared, trained, and practice exclusively, you have the United States health care design with 65% of the population left behind.
In the case of rural workforce, primary care, or family practice that require normal origin admissions or anyone less exclusive (not the lowest scoring, not those that cannot make it past boards, just less exclusive) it takes consistent efforts at every level to move steadily toward more normal and broader improvements
1. family structure, child development, early education
2. opportunity shaped to higher education
3. medical school admission
4. medical school training
5. shaping of career choice toward health access and FP
Trying to build backwards fails, because the efficiency and effectiveness is built from the earliest ages forward. Without sufficient health policy for support, specific fp training fails because the superior outcomes for distribution must be supported by policy. Specific FP rural or underserved training in turn depends upon enough choosing family medicine. In the US family medicine is still a permanent primary care form where the single decision is shaped by all previous and all future anticipated factors, which is why it is at the lowest point of all time.
This can all be traced to birth to age 6 or family stability and structure.
There is also incredible value in boosting opportunity. What is clear is that opportunities for education and higher education are made by individuals, stimulated by others in their lives. Something about their situation makes them turn on to education as more than just passive and the move into active pursuit, integration, and more. Without this, opportunities vanish.
Rural kids working with a set of sequential rural mentors over time is powerful.
Lower and middle income kids working with such a set is even more powerful as they become the teachers, public servants, family physicians and nurses that role model new generations and can launch future advances into higher education
Rural, FP, underserved workforce requires a focus on origins, admissions, and training that results in greater concentrations of rural workforce, FP workforce, underserved workforce. Simply expanding medical students, PA students, or NP students will no longer work.
Physicians from the most urban, highest income, highest status, most professional parents are not a good solution for the workforce needs of an entire nation as they are the least likely to leave concentrations to do family practice, primary care, rural, and underserved careers.
When entire populations of admitted medical students shift 0.1 units in bioMCAT scores each year for more than a decade (compared to 1993 standardization), some very exclusive changes are taking place that are only partially explained by each new year record parent income averages in matriculants. These are verified in parent income increases in matriculants. Also osteopathic matriculants have MCAT scores increasing 30% faster than allopathic US matriculants.
Schools that hold their own in any health access area are doing well since no school has resisted the trend to more exclusive in many dimensions.
I set up an exclusiveness index to gauge just how exclusive each major physician specialty, type of training, and physician source of training was. This involved the increase in the probability of highest income and most urban origins. I was conservative and did not take the most extreme higher income urban counties as this would have basically doubled the exclusiveness for the most exclusive careers seen below.
Viewed from top status down, odds look pretty good for an exclusive career. Viewed from the bottom up, odds of a more normal child gaining admission or an exclusive specialty is not as good.
Now be careful because these are essentially bivariate representations. The entire series of career outcome variables (exclusive birth to admission, admission, exclusive type of medical school), is represented in a single variable of a career choice.
Exclusive types of medical schools exist and they admit the most exclusive in terms of highest income and most urban birth county origins. Remember that this is just the US born component, but it appears that exclusive origins are seen in those US born to international, Caribbean, and Central American schools.
Allopathic private schools are most exclusive also, not a surprise. I did not break down allopathic public by MCAT scores, but they would have also had top ranking MCAT schools with exclusiveness ratings the same as allopathic private with other schools down as low as osteopathic public or lower.
In addition the scores, parent incomes, and other markers related to exclusiveness are also increasing with each passing year in those becoming physicians.
Only in the 1950s, the 1970s, and the 1990s has the US made any headway toward less exclusive in higher education and each involved more emphasis on lower and middle income with better distributions of resources this way - GI Bill, major investments in education, retraining admission committees to focus on the individual, not their scores or parent influences
That medical schools and medical school leaders have done little to address the need for better preparation for lower and middle income populations to become better children, better students, better patients, and better citizens is quite depressing.
One hundred years ago, medical education leaders identified better preparation of physicians as a major need and forced these important changes on America across education and higher education.
Changes at medical schools and in medical education are only a small part of why health access improves or why health care quality improves or why nations improve.
Why they deteriorate is more obvious, except to those who are leading who are most exclusive and least aware.
Exclusive Careers and More Normal By MCAT and Other Medical School Types
www.physicianworkforcestudies.org