A Study on the Relation among Primary Care Professionals Serving the Disadvantaged Community, Socioeconomic Status, and Adverse Health Outcome
During the post-Civil War era, the city of Nashville,
Tennessee, had the highest mortality rate in the United States. The
elevated death and disease rates among former slaves were
attributable to lack of quality healthcare. To address the paucity of
healthcare services, Meharry Medical College, an institution with the
mission of educating minority professionals and serving the
underserved population, was established in 1876.
Purpose: The social ecological framework and partial least squares
(PLS) path modeling were used to quantify the impact of
socioeconomic status and adverse health outcome on primary care
professionals serving the disadvantaged community. Thus, the study
results could demonstrate the accomplishment of the College’s
mission of training primary care professionals to serve in underserved
areas.
Methods: Various statistical methods were used to analyze alumni
data from 1975 – 2013. K-means cluster analysis was utilized to
identify individual medical and dental graduates in the cluster groups
of the practice communities (Disadvantaged or Non-disadvantaged
Communities). Discriminant analysis was implemented to verify the
classification accuracy of cluster analysis. The independent t-test was
performed to detect the significant mean differences of respective
clustering and criterion variables. Chi-square test was used to test if
the proportions of primary care and non-primary care specialists are
consistent with those of medical and dental graduates practicing in
the designated community clusters. Finally, the PLS path model was
constructed to explore the construct validity of analytic model by
providing the magnitude effects of socioeconomic status and adverse
health outcome on primary care professionals serving the
disadvantaged community.
Results: Approximately 83% (3,192/3,864) of Meharry Medical
College’s medical and dental graduates from 1975 to 2013 were
practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the
PLS path modeling demonstrated that alumni served as primary care
professionals in communities with significantly lower socioeconomic
status and higher adverse health outcome (p < .001). The PLS path
modeling exhibited the meaningful interrelation between primary
care professionals practicing communities and surrounding
environments (socioeconomic statues and adverse health outcome),
which yielded model reliability, validity, and applicability.
Conclusion: This study applied social ecological theory and
analytic modeling approaches to assess the attainment of Meharry
Medical College’s mission of training primary care professionals to
serve in underserved areas, particularly in communities with low
socioeconomic status and high rates of adverse health outcomes. In
summary, the majority of medical and dental graduates from Meharry
Medical College provided primary care services to disadvantaged
communities with low socioeconomic status and high adverse health
outcome, which demonstrated that Meharry Medical College has
fulfilled its mission. The high reliability, validity, and applicability of
this model imply that it could be replicated for comparable
universities and colleges elsewhere.
[1] A. C. Epps and P. M. Hammock, An Act of Grace: The Right Side of the
Story, Nashville, TN: Privately Printed, 2009.
[2] J. A. Friedman, A. Thind, P. L. Davidson, and C. Farmer-Dixon, The
Pipeline Program at Meharry Medical College School of Dentistry, J
Dent Educ., 2009, Feb;73(2 Suppl):S83-94; discussion S94-5.
[3] C. W. Johnson, The spirit of a place called Meharry: The strength of its
past to shape the future, 2000.
[4] J. A. Youngclaus, P. A. Koeheler, L. J. Kotlikoff, and J. M. Wiecha, Can
Medical Students Afford to Choose Primary Care? A Economic
Analysis of Physician Education Debt Repayment, Academic Medicine,
2013, 88, 16-25.
[5] R. M. Andersen, D. C. Carreon, P. L. Davidson, T. T. Nakazono, S.
Shahedi, and J. J. Gutierrez, Who will serve? Assessing Recruitment of
Underrepresented, 2010.
[6] D. E. Pathman and T. R. Konrad, Growth and changes in the national
health service corps (NHSC) workforce with the American recovery and
reinvestment act. Journal of the American Board of Family Medicine:
JABFM, 25(5), 2012, 723-733.
[7] R. A. Cooper, T. E. Getzen, H. J. McKee, and P. Laud, Economic and
Demographic Trends Signal and Impending Physician Shortage, Health
Affairs, 2012, 21, 140-154.
[8] Council on Graduate Medical Education (COGME), Physician
Workforce Policy Guidelines for the U.S. for 2000-2020, U.S.
Department of Health and Human Services, Rockville, MD. 2005.
[9] J. Hawkins, J. Mcrritt, and P. B. Miller, Will the last physician in
America Please Turn off the lights? A Look at America’s Looming
Doctor Shortage, Practice Support Resources, Inc., Irving, TX, 2004.
[10] C. K. Chen, Nationwide Physician Shortages Likely to Occur Beyond
2015 Based on Grey Forecasting Model, Journal of Education,
Informatics, and Cybernetics, 2009, 1, 14-18.
[11] J. N. Katz, Patient Preferences and Health Disparities, Jama, 286, 2001,
1506-1509.
[12] B. D. Smedley, A. S. Butler, and L. R. Bristow, In the Nation’s
Compelling Interest: Ensuring Diversity in the Health-care Workforce,
The National Academies Press, Washington, DC. 2004.
[13] U.S. Department of Health & Human Services. Shortage areas,
Retrieved from http://datawarehouse.hrsa.gov/topics/
shortageAreas.aspx, 2014.
[14] John Hopkins Medicine, What are disadvantaged students, Retrieved
from http://www.hopkinsmedicine.org/
geneticmedicine/resideny/Disadvantaged.html, 2013.
[15] T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman,
and A. Y. Wu, An efficient k-means clustering algorithm: Analysis and
implementation. IEEE Transactions on Pattern Analysis and Machine
Intelligence, 2002, 24(7).
[16] IBM SPSS Advanced Statistical 20, 2011.
[17] V. V. Esposito, W. W. Chin, J. Henseler, and H Wang, Handbook of
Partial Least Squares: Concepts, Methods and Applications, Springer
Handbooks of Computational Statistics Series, Volume II, Springer:
Berlin/Heidelberg, 2010.
[18] D. Gefen, D. W. Straub, and M. Boudreau Gefen, Structural Equation
Modeling Techniques and Regression: Guidelines for Research Practice
by Straub, and Boudreau Communications of AIS, 2000, Volume 4,
Article 73.
[19] J. Henseler, C. M. Ringle, and R. R. Sinkovics, The use of partial least
squares path modeling in international marketing, in: Sinkovics, R. R. /
Ghauri, P. N. (eds.), Advances in International Marketing (AIM), Vol.
20, Bingley 2009, pp. 277-320.
[20] G. Green and J. Coder, Household income trends: Retrieved from
Sentier Research, LLC website: http://sentierresearch.com/index.html,
issued July 2014.
[21] Bureau of Labor Statistics, Labor force statistics from the current
population survey, (Data file), Retrieved from
http://data.bls.gov/timeseries/ LNS14000000.20, 2014. [22] U.S. Census Bureau, Current population survey, 1960 to 2013: Annual
social and economic supplements, Retrieved from
http://www.census.gov/hhes/www/poverty/data/incpovhlth/2012/figure4
.pdf, 2013.
[23] Federal Education Budget Project, 2014.
[24] P. Galewitz, 48 million Americans remain uninsured, Retrieved from
uninsured-numbers-remain-nearly-unchanged.aspx, Census Bureau
reports Kaiser Health News, 2013, Sept. 17.
[25] J. McCarthy, In U.S., adult obesity rate now at 27.7%: Blacks are still
most likely to be obese among demographic groups, Retrieved from
http://www.gallup.com/poll/170264/adult-obesity-rate.aspx, 2014.
[26] Centers for Disease Control and Prevention. National diabetes statistics
report: Estimates of diabetes and its burden in the United States, 2014.
Atlanta, GA: U.S. Department of Health and Human Services, 2014,
http://www.cdc.gov/diabetes/pubs/statsreport14/national-diabetesreport-
web.pdf.
[27] P. L. Remington, B. B. Catlin, and D. A. Kindig, Monitoring progress in
population health: Trends in premature death rates, Preventing Chronic
Disease, 10, 2013, E214. doi: http://dx.doi.org /10.5888/pcd10.130210.
[28] Bureau of Labor Statistics, May 2014, retrieved from
http://data.bls.gov/search/query/results?cx=013738036195919377644%
3A6ih0hfrgl50&q=physicians, 2014
[29] XLSTAT, Addinsoft, Paris, France, (www.xlstat.com), 2009.
[30] W. W Chin, The partial least squares approach to structural equation
modeling, In:Marcoulides GA (Ed.) Modern Methods for Business
Research, Lawrence Erlbaum Associates, Mahwah, NJ, 1998, pp 295–
336.
[31] J. Henseler, PLS Path Modeling with SmartPLS, Foundations,
Applications, Extensions, Advances, Inforte Seminar Jyvaskyla, 2012.
[32] C. Dolea, L. Stormont and J. M. Braichet, Evaluated strategies to
increase attraction and retention of health workers in remote and rural
areas, Bulletin of the World Health Organization, 2010, 88(5), 379-385.
[1] A. C. Epps and P. M. Hammock, An Act of Grace: The Right Side of the
Story, Nashville, TN: Privately Printed, 2009.
[2] J. A. Friedman, A. Thind, P. L. Davidson, and C. Farmer-Dixon, The
Pipeline Program at Meharry Medical College School of Dentistry, J
Dent Educ., 2009, Feb;73(2 Suppl):S83-94; discussion S94-5.
[3] C. W. Johnson, The spirit of a place called Meharry: The strength of its
past to shape the future, 2000.
[4] J. A. Youngclaus, P. A. Koeheler, L. J. Kotlikoff, and J. M. Wiecha, Can
Medical Students Afford to Choose Primary Care? A Economic
Analysis of Physician Education Debt Repayment, Academic Medicine,
2013, 88, 16-25.
[5] R. M. Andersen, D. C. Carreon, P. L. Davidson, T. T. Nakazono, S.
Shahedi, and J. J. Gutierrez, Who will serve? Assessing Recruitment of
Underrepresented, 2010.
[6] D. E. Pathman and T. R. Konrad, Growth and changes in the national
health service corps (NHSC) workforce with the American recovery and
reinvestment act. Journal of the American Board of Family Medicine:
JABFM, 25(5), 2012, 723-733.
[7] R. A. Cooper, T. E. Getzen, H. J. McKee, and P. Laud, Economic and
Demographic Trends Signal and Impending Physician Shortage, Health
Affairs, 2012, 21, 140-154.
[8] Council on Graduate Medical Education (COGME), Physician
Workforce Policy Guidelines for the U.S. for 2000-2020, U.S.
Department of Health and Human Services, Rockville, MD. 2005.
[9] J. Hawkins, J. Mcrritt, and P. B. Miller, Will the last physician in
America Please Turn off the lights? A Look at America’s Looming
Doctor Shortage, Practice Support Resources, Inc., Irving, TX, 2004.
[10] C. K. Chen, Nationwide Physician Shortages Likely to Occur Beyond
2015 Based on Grey Forecasting Model, Journal of Education,
Informatics, and Cybernetics, 2009, 1, 14-18.
[11] J. N. Katz, Patient Preferences and Health Disparities, Jama, 286, 2001,
1506-1509.
[12] B. D. Smedley, A. S. Butler, and L. R. Bristow, In the Nation’s
Compelling Interest: Ensuring Diversity in the Health-care Workforce,
The National Academies Press, Washington, DC. 2004.
[13] U.S. Department of Health & Human Services. Shortage areas,
Retrieved from http://datawarehouse.hrsa.gov/topics/
shortageAreas.aspx, 2014.
[14] John Hopkins Medicine, What are disadvantaged students, Retrieved
from http://www.hopkinsmedicine.org/
geneticmedicine/resideny/Disadvantaged.html, 2013.
[15] T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman,
and A. Y. Wu, An efficient k-means clustering algorithm: Analysis and
implementation. IEEE Transactions on Pattern Analysis and Machine
Intelligence, 2002, 24(7).
[16] IBM SPSS Advanced Statistical 20, 2011.
[17] V. V. Esposito, W. W. Chin, J. Henseler, and H Wang, Handbook of
Partial Least Squares: Concepts, Methods and Applications, Springer
Handbooks of Computational Statistics Series, Volume II, Springer:
Berlin/Heidelberg, 2010.
[18] D. Gefen, D. W. Straub, and M. Boudreau Gefen, Structural Equation
Modeling Techniques and Regression: Guidelines for Research Practice
by Straub, and Boudreau Communications of AIS, 2000, Volume 4,
Article 73.
[19] J. Henseler, C. M. Ringle, and R. R. Sinkovics, The use of partial least
squares path modeling in international marketing, in: Sinkovics, R. R. /
Ghauri, P. N. (eds.), Advances in International Marketing (AIM), Vol.
20, Bingley 2009, pp. 277-320.
[20] G. Green and J. Coder, Household income trends: Retrieved from
Sentier Research, LLC website: http://sentierresearch.com/index.html,
issued July 2014.
[21] Bureau of Labor Statistics, Labor force statistics from the current
population survey, (Data file), Retrieved from
http://data.bls.gov/timeseries/ LNS14000000.20, 2014. [22] U.S. Census Bureau, Current population survey, 1960 to 2013: Annual
social and economic supplements, Retrieved from
http://www.census.gov/hhes/www/poverty/data/incpovhlth/2012/figure4
.pdf, 2013.
[23] Federal Education Budget Project, 2014.
[24] P. Galewitz, 48 million Americans remain uninsured, Retrieved from
uninsured-numbers-remain-nearly-unchanged.aspx, Census Bureau
reports Kaiser Health News, 2013, Sept. 17.
[25] J. McCarthy, In U.S., adult obesity rate now at 27.7%: Blacks are still
most likely to be obese among demographic groups, Retrieved from
http://www.gallup.com/poll/170264/adult-obesity-rate.aspx, 2014.
[26] Centers for Disease Control and Prevention. National diabetes statistics
report: Estimates of diabetes and its burden in the United States, 2014.
Atlanta, GA: U.S. Department of Health and Human Services, 2014,
http://www.cdc.gov/diabetes/pubs/statsreport14/national-diabetesreport-
web.pdf.
[27] P. L. Remington, B. B. Catlin, and D. A. Kindig, Monitoring progress in
population health: Trends in premature death rates, Preventing Chronic
Disease, 10, 2013, E214. doi: http://dx.doi.org /10.5888/pcd10.130210.
[28] Bureau of Labor Statistics, May 2014, retrieved from
http://data.bls.gov/search/query/results?cx=013738036195919377644%
3A6ih0hfrgl50&q=physicians, 2014
[29] XLSTAT, Addinsoft, Paris, France, (www.xlstat.com), 2009.
[30] W. W Chin, The partial least squares approach to structural equation
modeling, In:Marcoulides GA (Ed.) Modern Methods for Business
Research, Lawrence Erlbaum Associates, Mahwah, NJ, 1998, pp 295–
336.
[31] J. Henseler, PLS Path Modeling with SmartPLS, Foundations,
Applications, Extensions, Advances, Inforte Seminar Jyvaskyla, 2012.
[32] C. Dolea, L. Stormont and J. M. Braichet, Evaluated strategies to
increase attraction and retention of health workers in remote and rural
areas, Bulletin of the World Health Organization, 2010, 88(5), 379-385.
@article{"International Journal of Business, Human and Social Sciences:69916", author = "Chau-Kuang Chen and Juanita Buford and Colette Davis and Raisha Allen and John Hughes and Jr. and James Tyus and Dexter Samuels", title = "A Study on the Relation among Primary Care Professionals Serving the Disadvantaged Community, Socioeconomic Status, and Adverse Health Outcome", abstract = "During the post-Civil War era, the city of Nashville,
Tennessee, had the highest mortality rate in the United States. The
elevated death and disease rates among former slaves were
attributable to lack of quality healthcare. To address the paucity of
healthcare services, Meharry Medical College, an institution with the
mission of educating minority professionals and serving the
underserved population, was established in 1876.
Purpose: The social ecological framework and partial least squares
(PLS) path modeling were used to quantify the impact of
socioeconomic status and adverse health outcome on primary care
professionals serving the disadvantaged community. Thus, the study
results could demonstrate the accomplishment of the College’s
mission of training primary care professionals to serve in underserved
areas.
Methods: Various statistical methods were used to analyze alumni
data from 1975 – 2013. K-means cluster analysis was utilized to
identify individual medical and dental graduates in the cluster groups
of the practice communities (Disadvantaged or Non-disadvantaged
Communities). Discriminant analysis was implemented to verify the
classification accuracy of cluster analysis. The independent t-test was
performed to detect the significant mean differences of respective
clustering and criterion variables. Chi-square test was used to test if
the proportions of primary care and non-primary care specialists are
consistent with those of medical and dental graduates practicing in
the designated community clusters. Finally, the PLS path model was
constructed to explore the construct validity of analytic model by
providing the magnitude effects of socioeconomic status and adverse
health outcome on primary care professionals serving the
disadvantaged community.
Results: Approximately 83% (3,192/3,864) of Meharry Medical
College’s medical and dental graduates from 1975 to 2013 were
practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the
PLS path modeling demonstrated that alumni served as primary care
professionals in communities with significantly lower socioeconomic
status and higher adverse health outcome (p < .001). The PLS path
modeling exhibited the meaningful interrelation between primary
care professionals practicing communities and surrounding
environments (socioeconomic statues and adverse health outcome),
which yielded model reliability, validity, and applicability.
Conclusion: This study applied social ecological theory and
analytic modeling approaches to assess the attainment of Meharry
Medical College’s mission of training primary care professionals to
serve in underserved areas, particularly in communities with low
socioeconomic status and high rates of adverse health outcomes. In
summary, the majority of medical and dental graduates from Meharry
Medical College provided primary care services to disadvantaged
communities with low socioeconomic status and high adverse health
outcome, which demonstrated that Meharry Medical College has
fulfilled its mission. The high reliability, validity, and applicability of
this model imply that it could be replicated for comparable
universities and colleges elsewhere.", keywords = "Disadvantaged Community, K-means Cluster
Analysis, PLS Path Modeling, Primary care.", volume = "9", number = "5", pages = "1618-8", }