Introduction: The US Health Care and Social Services sector (North American Industrial Classification System 'sector 62') has become an extremely important component of the nation's economy, employing approximately 18 million workers and generating almost $753 billion in annual payrolls. At the county level, the health care and social services sector is typically the largest or second largest employer. Hospital employment is often the largest component of the sector's total employment. Hospital employment is particularly important to non-metropolitan or rural communities. A high quality healthcare sector serves to promote economic development and attract new businesses and to provide stability in economic downturns. The purpose of this study was to examine the intensity of hospital employment in rural counties relative to the nation as a whole using location quotients and to draw conclusions regarding how potential changes in Medicare and Medicaid might affect rural populations. Methods: Estimates for county-level hospital employment are not commonly available. Estimates of county-level hospital employment were therefore generated for all counties in the USA the Census Bureau's County Business Pattern Data for 2010. These estimates were used to generate location quotients for each county which were combined with demographic data to generate a profile of factors that are related to the magnitude of location quotients. The results were then used to draw inferences regarding the possible impact of the Patient Protection and Affordable Care Act 2010 (ACA) and the possible imposition of aspects of the Budget Control Act 2011 (BCA). Results: Although a very high percentage of rural counties contain medically underserved areas, an examination of location quotients indicates that the percentage of the county workforce employed by hospitals in the most rural counties tends to be higher than for the nation as a whole, a counterintuitive finding. Further, when location quotients are regressed upon data related to poverty, county demographics, and the percentage of the population insured, a relationship between the proportion of the population over 65 years, the percentage of the population living in poverty, the percentage of the population without insurance and county density was found. Conclusion: The results of the analysis suggest that hospital employment in rural communities is higher than would be expected in the absence of programs that provide external funding to support hospital hiring. The most important public programs providing this support are Medicare and Medicaid. Social Security is another source of federal funding important for rural populations. Sequestration and other cuts in funding could impact rural communities significantly. This can be even worse in states that fail to expand Medicaid and in states that fail to increase Medicaid reimbursements for services important in rural communities.

Introduction: The US Health Care and Social Services sector (North American Industrial Classification System 'sector 62') has become an extremely important component of the nation's economy, employing approximately 18 million workers and generating almost $753 billion in annual payrolls. At the county level, the health care and social services sector is typically the largest or second largest employer. Hospital employment is often the largest component of the sector's total employment. Hospital employment is particularly important to non-metropolitan or rural communities. A high quality healthcare sector serves to promote economic development and attract new businesses and to provide stability in economic downturns. The purpose of this study was to examine the intensity of hospital employment in rural counties relative to the nation as a whole using location quotients and to draw conclusions regarding how potential changes in Medicare and Medicaid might affect rural populations. Methods: Estimates for county-level hospital employment are not commonly available. Estimates of county-level hospital employment were therefore generated for all counties in the USA the Census Bureau's County Business Pattern Data for 2010. These estimates were used to generate location quotients for each county which were combined with demographic data to generate a profile of factors that are related to the magnitude of location quotients. The results were then used to draw inferences regarding the possible impact of the Patient Protection and Affordable Care Act 2010 (ACA) and the possible imposition of aspects of the Budget Control Act 2011 (BCA). Results: Although a very high percentage of rural counties contain medically underserved areas, an examination of location quotients indicates that the percentage of the county workforce employed by hospitals in the most rural counties tends to be higher than for the nation as a whole, a counterintuitive finding. Further, when location quotients are regressed upon data related to poverty, county demographics, and the percentage of the population insured, a relationship between the proportion of the population over 65 years, the percentage of the population living in poverty, the percentage of the population without insurance and county density was found. Conclusion: The results of the analysis suggest that hospital employment in rural communities is higher than would be expected in the absence of programs that provide external funding to support hospital hiring. The most important public programs providing this support are Medicare and Medicaid. Social Security is another source of federal funding important for rural populations. Sequestration and other cuts in funding could impact rural communities significantly. This can be even worse in states that fail to expand Medicaid and in states that fail to increase Medicaid reimbursements for services important in rural communities.

The Patient Protection and Affordability Act of 2010 (PPACA) addressed the access to healthcare in the United States. One of the problems of this healthcare access was rooted in disproportionally lower access among minority populations. The purpose of this quantitative study, guided by the consumer behavior theory, was to examine the association between race/ethnicity and enrollment within the Covered California-?¢ (CoveredCA) Insurance Exchange. A cross-sectional study design was used to investigate the association between race/ethnicity and the use of Covered CA health benefit exchange. Logistic regression analysis was used to examine the relationship between enrollment and race/ethnicity, having adjusted for covariates of age, gender, and literacy. The results revealed that, while all other race/ethnicity groups were less likely to purchase Bronze level versus Silver and above coverage compared to the Hispanic race/ethnicity, Asians (OR =1.16, 95% CI: 1.11, 1.20) and Whites (OR = 1.12, 95% CI: 1.02, 1.14) were more likely to purchase Bronze level versus Silver and above coverage compared to the Hispanic group. Chi-square test results indicated a statistically significant difference in the proportion of individuals selecting the Bronze level coverage compared to the Silver and above among the various race/ethnicity groups ï?£2 (13, N= 763,531), 1922.083, p < 0.0001. The Hispanic race/ethnicity was more likely to enroll in the Bronze versus Silver and above compared to other race/ethnicities. The results of this study may contribute to positive social change by informing policy that besides income and age, race/ethnicity is an important determinant of the likelihood of enrollment in the Covered CA health exchange.