Fluent Essays

see attachment SOCIOLOGY: CAPSTONE PROJECT Topic: Disparities in healthcare in USA Problem statement: This paper will examine the difference in health care coverage in underrepresented American households before and after the introduction of healthcare under the Affordable Care Act. Research Question: Has the introduction of healthcare under the Affordable Care Act (Obamacare) increased significantly the percentages of minority, and lower- and middle-class households that have health insurance? Hypothesis 1: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of low-income American households with health insurance by 70\%. Hypothesis 2: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of in middle class American households with health insurance by 20\%. Hypothesis 3: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of ethnic and racial minority households in the United States with health insurance by 20\%. Independent variable tested in the hypotheses is the number of lower class/middle class/minority households with insurance before the introduction of the Affordable Care Act in 2010 and a decade after its introduction. Take into account where the ACA made the most impact and where it made the least.   How to test this: Explain that you will use peer reviewed studies and data from health organizations, etc. Theory one: Describe the first social theory you will apply to the results of your study and how it relates to your topic. I will Apply the Conflict theory to the topic Theory two: Describe the second social theory you will apply to the results of your study and how it relates to your topic. I will Apply the Interactionism theory to the topic * Is it browsing in the library? Talking to folks hanging out on a street corner, making a mental note of what they say and how they say it? A school counselor who routinely inquires, as part of an interview, about a student’s family life? These are important activities, but sociological research has very specific goals that can only be accomplished through utilizing proper procedures Is the systematic examination--or reexamination--of empirical data, collected by a scholar or scholars, concerning the social or social psychological forces operating in a social situation being investigated. It is systematic Uses empirical data: information based on actual social experiences of human beings Investigates the social (group) factors that affect human behavior 1. Four important Considerations: Is it researchable, given methodological limits in two months? Can you obtain the data you need? Practice parsimony: keep your focus narrow. You are not writing a MA thesis and have two months to complete on a tight schedule. Credibility of research: is your topic important? Can you be objective and use sociological method? Are there rival explanations for social phenomena already done that answer your Research Question? Don’t be one-sided. Researchability Can the topic be researched? Can the scientific method be used to investigate the topic? Can you obtain the data you need? Do you have the time, money, facilities, etc. to do the project? Is it too difficult to do (realistically speaking)? Parsimony Keep it simple: more is not better This is not your life’s work Keep the topic narrow and focused Credibility Is your topic important? Can you employ the scientific method and remain objective? Follow established procedures for describing your results? Rival Explanations Your research should not be one sided: sociological research is replete with alternative explanations for virtually every observable phenomenon Be certain to consider rival explanations; be prepared to account for such alternative explanations * 2. General topic areas Groups, Organizations, Social Institutions Status and Roles Social Structure Social Movements Social Construction of Knowledge Culture, Subcultures, Countercultures Social Class Race/Ethnicity Gender Sexuality Religion Families Deviance Popular culture Discover/Describe Research Predictive Research Explanatory Research Evaluation Research Discover/Describe: Attempt to discover facts or describe reality. Is divorce on the rise? Are people in the US fearful they will be killed by terrorists? Is social media an increasingly important aspect of the millennial generation experience? 2. Predictive Research: predictions about what will occur in the future based on research collected. most common are actuarial predictions, the kind insurance companies make. E.g., Who is likely to get heart attack, speed while driving, etc. also, recidivism to prison predictions, risk assessments, impact of social policy change, destigmatization of transgenderism 3. Explanatory Research: Seek to explain why or how something happened. in juvenile delinquency, for example, explanatory research goes beyond describing rates of delinquency or predictions of who will engage in delinquent acts – and focuses on why some become delinquents. Basic (or pure) research: goal is to advance our knowledge about human behavior with little concern for immediate, practical benefits Applied research: designed with a practical outcome in mind e.g., if we have a better understanding of why people become delinquents, we can better design solutions Evaluation research: uses scientific method to plan, monitor the implementation, and determine the effectiveness of programs; also, examines unintended consequences e.g. drug treatment, counseling, instructional strategies Case study analysis: actual effectiveness of a VA program. Start with a general area of interest Do some reading in the area Narrow your research topic using the guiding principles Describe the problem (PS) Develop a research question (RQ) Formulate a research hypothesis (RH) Review the relevant literature As you review the literature, look for studies/data that you can use to test your hypothesis. Start organizing your materials and writing You will write FIVE chapters in your project, according to a strict schedule; revision schedule is built into the schedule. Introduction Problem Statement (PS): what are you studying and why? Research Question(s) (RQ): what question or questions do you want to answer? Research Hypothesis/es (RH): one or more you will test Specific subtopics related to your main topic and research question Ten academically appropriate references minimum required (see syllabus). More are usual. You can build this list as you continue your research. Any studies used to test your hypothesis/es are NOT to appear in Literature Review. Theoretical or Conceptual Framework (s)—typically last paragraph of Literature Review Study name, authors, where published (if you are doing content analysis—creating your own original source of data, you will do each step, excluding publication). Setting Description of Subjects Description of Research Instrument Description of Variables: independent and dependent Definition of Terms Procedures Limitations The chapter is organized, hypothesis tested by hypothesis tested Tables, charts Statement of support, partial support, or rejection NO analysis of the results appears in this section; only a description of the results. Discussion: what do the results mean? Conclusions Recommendations ***In this chapter, your theoretical framework or frameworks are using in the analysis. At course end, you will present a 15-20 minute PowerPoint about your project. ? Topic: Disparities in healthcare in USA 1- Make revision on chapter 4 2- Write chapter 5: Discussion, Conclusions, and Recommendations 7 pages Discussion This chapter includes three sections. The first section is a discussion of the research project, including the findings, interpretation of the results, and problems and/or limitations. This latter item is one of the most important parts of your chapter. You need to discuss how the limitations of your research may have affected your results. Remember, there are two types of limitations: those that are imposed by the researcher (usually the time period and the geographic location, though there may also be limitations involving your subjects; and those that are the result of your research method. Every research method has some inherent limitations; it is important to address those that may affect the validity and reliability of your findings. Limitations may also be associated with your sample. Be systematic in your discussion of limitations: take them one at a time. You should also discuss any problems that might have occurred during your research, especially those that might affect your findings. In the Discussion section, you should also discuss how your result reflect your theoretical or conceptual framework. Are the findings consistent with what you expected? You can also be a little creative in this section. It is appropriate to speculate why you think you got the results you did. You still need to use third person, but you can make your views known. Do not repeat other parts of your research project in this section, except perhaps your research hypotheses or research question. Conclusions The second section is the Conclusions. What did we find out? What did we learn? Focus on your original objectives. Were there unintended consequences or surprises? What is the value of this research? Recommendations The final section, Recommendations, usually include three areas: 1) Is there a need for any changes to current practices? Should we be doing things differently? 2) Is there a need for any changes to current policies? Do we need new rules, new laws? 3) Is there a need for future research? This could be a replication of one or more studies, a different sample, different methodology, different variables. This is very good. One thing: You need to start the paper with a clear statement about the hypotheses being supported, partially supported or not supported by the research you later offer. Also you don’t need to summarize the articles all over again. Chapter three did that. I recommend you omit those summaries. The rest of the chapter is fine! See comments below. CHAPTER IV- DATA AND ANALYSIS Introduction Start be immediately telling the reader – in the first paragraph – if each of the hypotheses were supported, partially supported or not supported by the research you later offer. The paper examines the difference in health care coverage in the underrepresented American households before and after the implementation of the Affordable Care Act. The policy was enacted to primarily expand American’s access to insurance and improve the quality of health care services that American citizens get access to. As such, the reform has resulted in a significant impact regarding the health status of different groups living in America, especially among the minorities. Besides, the introduction of the reform has, over the years, been associated with a reduction in disparities in the U.S health care system. Notably, before A.C.A, various groups of color had limited access to health insurance coverage which adversely affected their health care conditions. Similarly, individuals from low-income families also experienced this effect. In this regard, the paper aims at answering a question related to the implementation of A.C.A and also investigate three hypotheses highlighted below. Research Question  The research question asked in the study is: Has the introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentages of minority and lower-and middle-class households with health insurance significantly? In answering g the question, the paper employs peer-reviewed studies and also data from health organizations. General Description of Data Sources and Methods The paper uses data from six articles described in chapter three to gain insights based on the topic of study. (You can omit the following descriptions of the articles. The reader just read the summaries of the articles in chapter three. There’s no need to describe them this way again. Instead you have the sentence above and the last paragraph in this section of the paper; these explain what you will do with the results from chapter three.) The first article “Three-year impacts of the Affordable Care Act: improved medical care and health among low-income adults” by Sommers et al. (2017) investigates the ongoing changes in health care use and health care services among low-income individuals after the implementation of the reform. Sommers et al. (2017) conducted a difference-in-difference analysis by comparing the post outcomes from three states regarding the implementation of Obamacare. The second article is “Health Spending for Low-, Middle-, and high-Income Americans, 1963-2012” and it examines the level of spending among the American citizens after the implementation of the reform. In assessing this, Dickman et al. (2016) data from a national survey and performed an evaluation using linear regression. The third article in collecting data is “The Effect of the Affordable Care Act on Racial and Ethnic Disparities in Health Insurance Coverage” and the research study was conducted by Dickman et al. (2016). The research examines how health insurance coverage has changed among White, Black, and Hispanic adults after the A.C.A. Based on data collected from American Community Survey, Dickman et al. (2016) performed an analysis to identify the trends related to the income and the amount spent in acquiring health care services. The fourth article is “Change Utilization and Health among Low-income Adults After Medicaid Expansion or Expanded Private Insurance” and its authors are Sommers et al. (2016). The article asses the changes regarding care, utilization, and self-reported health among the low-income individuals after the implementation of Obamacare. In this regard, Sommers et al. (2016) used differences-in-differences analysis to get more insights. Another article that the paper depends on is “The Effects of Household Medical Expenditure on Income inequality in the United States” by Christopher et al. (2018) and the article evaluates the outlays of various American households related to their medical expenditures and income inequality. In achieving this, the researchers calculated the Gini index of various aspects related to the medical expenditure of the individuals. The last article is “Racial and Ethnic Disparities in Health Care Access and Utilization under the Affordable Care Act”. Chen et al. (2016) used the research study to examine the racial and ethnic disparities that relate to health care access and utilization after the implementation of the reform. The researchers used a multivariate linear probability model to examine the factors that affect access to health care services like socio-demographic factors. (The rest of the chapter is excellent. No changes.) The paper implements the statistical procedure used in the articles identified and whose data have been included in the research. In this regard, the paper depends on more than one method for analyzing data that will be used in answering the research questions. Additionally, the chapter explores data presented in all the articles and analyzed them to determine whether they support, partially support, or reject the hypotheses. Hypothesis #1 The first hypothesis that the paper is focused on is: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of low-income American households with health insurance by 70\%. One of the research articles that the paper uses in testing the hypothesis outlined above is the study by Sommers et al. (2017). Based on the methods used by the researchers, the study found that 72 percent of the respondents living in Kentucky were affected with chronic conditions, 69 percent in Arkansas, and 55 percent in Texas. According to the results, the disease prevalence between 2013 and 2016 decreased within the expansion states with a P-value of 0.06. Sommers et al. (2017) provided that the mean number of various conditions including depression, hypertension, and diabetes ranged from 2.0 to 2.3. According to the results of the study, the three states involved in the research began the assessment when the uninsurance rate was about 40 percent among the low-income individuals. At the end of the research period, in 2014, the uninsurance rate was at 7.4 percent in Kentucky, 11.7 percent in Arkansas, and 28.2 percent in Texas. The study realized an increase in insurance coverage, access, affordability, and prevention with a p-value of 0.05 while that of quality was at p<0.010. Figure 1: Percentage of the uninsured Low-income adults between 2013 and 2016 The second article used in testing the hypothesis is by Sommers et al. (2016) and it addresses changes in utilization and health among low-income adults after the expansion of Medicaid. The study found that the expansion regarding health uninsurance rate reduced by 22.7 percent as of 2015 with a p-value less than 0.001. The expansion rate of insurance cover was associated with an increased rate of 12.1 percent and a p-value of less than 0.001. The results indicate that there was a reduced level of out-of-pocket spending for the respondents during the research period. The quality-of-care rating indicated significant improvement with a 7.1 percentage point indicating “fair/poor” care quality and a p-value of 0.03. Considering the states, Sommers et al. (2016) found that Arkansas realized an increased level of private insurance coverage while Kentucky showed an increased Medicaid of 1.3 percent. The uninsurance rate reduced from 41.1 to 14.2 percent in Arkansas, from 40.2 to 8.6 percent in Kentucky, and from 38.5 to 31.8 percent in Texas. During the research period, private coverage gains showed greater values in Kentucky and Arkansas. However, the two states showed the lowest Medicaid gains. Besides, the minority experienced a significant increase in insurance coverage which showed a p-value of 0.004. Both the two studies that address the first hypothesis realized an increase in the rate of insurance coverage expansion while the rate of uninsurance greatly reduced. The studies indicate high number of insurance rates for most respondents in the three cities between the starting and ending period of the research. The increase in health insurance coverage led to a reduced level of income spending on health care services and out-of-pocket spending among low-income individuals. In this regard, the two studies support the first hypothesis. They both realized an increase in the insurance coverage among the low-income individuals after the implementation of A.C.A thus supporting the hypothesis that: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of low-income American households with health insurance by 70\%. Hypothesis 2 The second hypothesis is: The introduction of healthcare under the Affordable Care Acct (Obamacare) increased the percentage of middle-class American households with health insurance by 20\%. The first study that relates to the above hypothesis is by Dickman et al. (2016) and it addresses low-, middle- and high-class individuals’ spending on health. The results of the study indicate that the per capita health expenditure grew between 1963 and 2012. The researchers found that the health expenditure for the high-class income groups outpaced those of the middle-class individuals. Notably, individuals from low-class indicated the worst health status before the implementation of A.C.A. The study found an increase in prescription drug spending for the income groups after 2004. However, the high-income group showed an increased inpatient and outpatient expenditures while the middle-class indicated a flat growth and a declining growth for the low-class. Based on the research study, the researchers found that the participants from the high-class made 40 percent more outpatient visits per capita than the remaining groups with a higher spending per visit approximately $303 compared to $241 for the remaining groups by2012 (Dickman et al., 2016). The results indicate that private insurance expenditures for the three income groups became different after 2004. In this regard, the expenditures rose rapidly for the wealthiest groups while it fell for the low-income group. Concerning the per capita Medicare expenditure growth, the low-class individuals realized a slower growth than the middle- and high-class groups. Private insurance expenditures per enrollee for individuals younger than 65 years fluctuated for the low-class group indicated a modest growth for the middle-class and sharply increased for the wealthiest individuals. According to Dickman et al. (2016), the Medicaid spending for every nonelderly recipient significantly declined during the research period. However, the study did not realize any trend associated with the proportion of the total spending for the low-income group. Besides, the faster growth of expenditures realized among the poor before 2004 was driven by the costliest. However, the expenditures for both low-cost and high-cost after year surged. Figure 2: Diagram showing spending per capita The second study related to the hypothesis is “The Effects of Household Medical Expenditure on Income inequality in the United States.”  From the study, Christopher et al. (2018) indicated that the Gini index was 46.77 at the start of the research in 2010. However, subtracting medical outlays led to an increase in the index to 48.22. The researchers realized a Gini index of 47.84 in 2014 which increased to 49.21 after subtracting medical outlays. When premium contributions of employers were treated as additions to employee income, the research realized outlays redistribution of about 1.7 percent for all income groups, the poor, middle class, and wealthier individuals. The results indicate that the medical outlays in 2013 led to a decrease in income for the low-income individuals by 49.2 percent, 10.7 percent for the middle-income population, and 2.5 percent for the wealthiest group. This indicates unequal pattern that slightly improved in 2014 based on the research findings. Additionally, the medical outlays reduced for the median income individuals by 47.6 percent and 2.7 percent for the same group in the top decile. According to Christopher et al. (2018), about nine million American citizens whose incomes before subtracting their medical outlays for their family income were above the poverty level were pushed into the 150 percent federal poverty level in 2014. The two studies provide data on medical expenditures and income inequality regarding a section of the American population. Based on the data, there was a significant decrease after the implementation of Medicaid under Obamacare for all the income groups involved in the two studies. As such, the introduction of A.C.A among the Americans realized positive results, especially for the low- and middle-class individuals. Therefore, the data from the studies support the hypothesis that: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of middle-class American households with insurance by 20\%. Hypothesis 3 The third hypothesis that the paper focuses on is: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of ethnic and racial minority households in the United States with health insurance by 205. The first study that is related to the hypothesis is “The Effect of the Affordable Care Act on Racial and Ethnic Disparities in Health Insurance Coverage.”   The results of the study indicate that the percentage of adults in various groups, White, Black, and Hispanic of the uninsured individuals increased between 2008 and 2010. However, the values significantly declined between 2010 and 2013. Buchmueller et al. (2016) found an average coverage gap between Blacks and whites to be 11 percentage points while the average gap between Hispanics and whites was about 27 percentage points. The study found that the percentage of the uninsured reduced by 7.1 percent among Hispanic, 5.1 percent among Blacks, and 3 percent among whites in 2014. The results indicate a decline in public insurance coverage for all the three groups between 2008 and 2013 before realizing an increase between 2013 and 2014. During the period in which public insurance increased, the percentage point and gain were greater for the two minority groups than the Whites. In this regard, Buchmueller et al. (2016) indicated that private coverage for Hispanics increased by 4.3 percentage points, 3 percentage points for the Blacks, and 1.5 percentage points for the Whites. The public coverage between 2013 and 2014 increased by 2.8 percentage points for Hispanics, 1.9 percentage points for the Blacks and the whites realized an increase of 1.5 percentage points. Before A.C.A insurance expansions, about 60 percent of the Hispanic noncitizens were uninsured while only 28 percent of the Hispanic citizens were uninsured. Between 2013 and 2014, the percentage point change was 7.0 for Hispanic noncitizens and 6.7 for Hispanic citizens. In regards to the adults from families whose income was below 138 \%, the results indicate more decline for Hispanics (9.3 percentage points) than for the non-Hispanics (6.1 percentage points). The percentage of Blacks without health insurance reduced by 5.6 percentage points in 2013 considering the expansion states while the group realized a decrease of 4 percentage points in the non-expansion states. Figure 3: Uninsured percentage of the Nonelderly between 2008 and 2014 The second study that is related to the hypothesis is “Racial and Ethnic Disparities in Health Care Access and utilization under the Affordable Care Act.”  According to Chen et al. (2016), the study found that the implementation of A.C.A significantly reduced the rate of uninsured for all ethnicities and races. Based on the research study, the uninsured rate decreased by 7 percent for the African Americans and Latinos, 3 percent for the Whites, and 5 percent for the remaining racial and ethnic groups in 2014 compared to 2011. Additionally, the results show that 5 percent of the Latinos were likely to visit physicians, 3 percent for African Americans, and 2 percent for whites in 2014 compared to 2011. The implementation of Obamacare led to a significant reduction of the likelihood of an individual getting uninsured with a coefficient value of -0.03 and p-value <0.01. The delay in any necessary care was reduced with a coefficient value of -0.03 and a p-value <0.001. The reduction in the uninsured rates was more pronounced in 2014. Besides, the possibility of being uninsured in 2014 was 3 percentage points for the whites and 4 percentage points for the African Americans and Latinos. However, the likelihood of delayed or forgone care decreased by 2 percentage points for the Latinos. On the other hand, Chen et al. (2016) indicated that there was no significant difference for the African Americas compared to the Whites in regards to forgone care or physician visits in 2014. The data from the two studies indicate an increase in health care access among the ethnic and racial groups after the implementation of the A.C.A relative to the periods before the reform. Based on the data, the rate of uninsured also reduced significantly over the years after A.C.A implementation. As such, the data support the hypothesis that: The introduction of healthcare under the Affordable Care Act (Obamacare) increased the percentage of ethnic and racial minority households in the United States with health insurance by 20\%. The next chapter will contain three main sections, the first section is a Discussion of the findings. The second section is Conclusions and the final section addresses recommendations. References Buchmueller, T. C., Levinson, Z. M., Levy, H. G., & Wolfe, B. L. (2016). Effect of the Affordable Care Act on racial and ethnic disparities in health insurance coverage. American journal of public health, 106(8), 1416-1421. Chen, J., Vargas-Bustamante, A., Mortensen, K., & Ortega, A. N. (2016). Racial and ethnic disparities in health care access and utilization under the Affordable Care Act. Medical care, 54(2), 140. Christopher, A. S., Himmelstein, D. U., Woolhandler, S., & McCormick, D. (2018). The effects of household medical expenditures on income inequality in the United States. American Journal of Public Health, 108(3), 351-354. Dickman, S. L., Woolhandler, S., Bor, J., McCormick, D., Bor, D. H., & Himmelstein, D. U. (2016). Health spending for low-, middle-, and high-income Americans, 1963–2012. Health Affairs, 35(7), 1189-1196. Sommers, B. D., Blendon, R. J., Orav, E. J., & Epstein, A. M. (2016). Changes in utilization and health among low-income adults after Medicaid expansion or expanded private insurance. JAMA internal medicine, 176(10), 1501-1509. Sommers, B. D., Maylone, B., Blendon, R. J., Orav, E. J., & Epstein, A. M. (2017). Three-year impacts of the Affordable Care Act: improved medical care and health among low-income adults. Health Affairs, 36(6), 1119-1128. CHAPTER III- METHODOLOGY The chapter describes the research methodology used in collecting data for answering the research question. Essentially, the study relies on previously published studies that relate to the hypotheses of the research. In this regard, the study will offer a detailed analysis of the concepts presented in the documents and data from health organizations. Besides, it will outline the setting, subjects, research instruments, procedures, and limitations to each study included in testing the outlined hypotheses.  Setting The first article is, “Three-year impacts of the Affordable Care Act: improved medical care and health among low-income adults” and it is authored by Sommers et al. It was published online in 2017 by Chan School of Public Health. The study was conducted between 2013 and 2016, and it included three states, Kentucky, Arkansas, and Texas. Texas was selected as a control for the remaining two states. The second article, “Health Spending for Low-, Middle-, and high-Income Americans, 1963-2012,” is authored by Dickman et al. and was published in 2016. The study involved details regarding the health expenditures of representatives of the American population over fifty years.  The third article is “The Effect of the Affordable Care Act on racial and ethnic disparities in Health Insurance coverage.” Its authors are Buchmueller et al. The study was published in 2016. It provides the extent of health insurance coverage for groups such as Whites, Blacks, and Hispanic adults under A.C.A. implementation. The fourth study that this research will use is “Change in Utilization and Health among Low-income Adults After Medicaid Expansion or Expanded Private Insurance.” Its authors are Sommers et al., and the study was published in 2016 in JAMA. The study was conducted in three different states, Kentucky, Arkansas, and Texas. Additionally, the research was occurred between 2013 and 2015. Another study whose data is to be used in testing the hypotheses is “The Effects of Household Medical Expenditure on Income inequality in the United States.” Its authors are Christopher et al., and the article was published in 2018. The study was based on the information regarding the United States’ population. The last study related to the hypotheses of the research is “Racial and Ethnic Disparities in Health Care Access and Utilization under the Affordable Care Act.” The authors of the study are Chen et al. and it was published in 2016. The research is based on a previous study that covers information regarding the United States’ population.  Description of the Subjects The participants involved in the study included United States citizens whose ages range between 19 and 64 years. According to Sommers et al. (2017), the population composed of individuals with household earnings below the federal poverty level percentage. The authors recruited the participants within the selected states every year from 2013 up to 2016. The yearly sample-sized that was used during the research period was between 2,209 individuals and 3 011. Thus, 10 885 people participated in the research during the four years. The study included the three states because they all covered various elements of private marketplace insurance expansion and Medicaid expansion under the Affordable Care Act (A.C.A.).  According to Dickman et al. (2016), the research implemented document review as the data collection method, and it involved 22 nationally representative surveys. It involved data from Health Services Utilization and Expenditure survey, National Medical Care Utilization and expenditure surveys, National Medical Expenditure Survey, and Medical Expenditure Panel Surveys. The authors provided that the surveys collected demographic information that includes details regarding income and family size. The research by Buchmueller et al. (2016), on the other hand, used data from a previously conducted survey that contains details of different minority groups living in the United States and are affected by the implementation of the Affordable Care Act. The information included respondents whose ages range from 19 to 64 years. Additionally, the researchers observed the characteristics that led to differences among the White, Black, and Hispanic such as income and education levels. The research by Sommers et al. (2016) included 8676 participants who were citizens of the United States. According to the authors, the minimum age for the participants was 19 years, while the maximum was 64 years, with an income level below the federal poverty level. The researchers surveyed about 1000 different people in each of the three states annually. Christopher et al. (2018) used existing data from the Annual Social and Economic Supplement of 2011 up to 2015 as the source of data for their research. According to the authors, the Current Population Surveys required the respondents to provide information on their income and expenditures for 2010 through 2014 to ensure a broad view of the impacts of household medical expenditures. The subjects to the study conducted by Chen et al. (2016) involved various American groups, including Whites, African Americans, and Latinos. The researchers focused on the groups regarding their health care access and utilization before the implementation of A.C.A. and after its implementation.  Description of Research instruments The researchers used different instruments in their studies. Sommers et al. (2017) implemented a survey that they conducted through random-digit dialing over the telephone. The method automatically generates telephone numbers of individuals to participate in a given study at random. It included both English and Spanish languages for contacting the selected individuals. The method is beneficial since it captures respondents with unlisted numbers which could be missed while using a phone book. Additionally, the method limits challenges associated with the telephone directory as the sampling frame. Dickman et al. (2016) used a document review based on the survey information from different organizations. This gave the researchers a broad view of the American’s health expenditure. Besides, the method is beneficial in collecting detailed information over a large coverage within a short period, making it possible to reduce research biases resulting from the sample included in a study.  The research by Buchmueller et al. (2016) used document analysis as the research instrument for data collection. Based on the data from the survey, the researchers examine the percentage of individuals with health insurance coverage and those without. The analysis provided a broad view of the impact of A.C.A. on the minority groups in the U.S. The research by Sommers et al. (2016) implemented a random-digit telephone survey that involved the use of landlines and cellphones to select and contact the respondents. The researchers used survey questions that were taken from national surveys such as Oregon Health Insurance Experiment and government surveys. Christopher et al. (2018) reviewed existing data as the research instrument for their study. The method is beneficial as it provides adequate background information and broad coverage of data that the researchers might not have collected using the other data collection methods. Additionally, the method allows researchers to study subjects to which they may not have easy physical access. Chen et al. (2016) also used existing data to answer their research question. This broadens their understanding based on the data that they can access.  Description of Variables Regarding the research, the independent variable is the implementation of the Affordable Care Act whiles the dependent variable is health care coverage. Based on the information provided by the authors, the level of health coverage is measured in terms of the number of people with insurance coverage since it directly affects access to health care services. In this regard, the level of health care coverage has been operationalized. Based on the information that Buchmueller et al. (2016) provided in their research, they operationalized access to health insurance coverage for different groups. As such, the study measured the effect that the implementation of A.C.A. resulted in among the minority groups.  Chen et al. (2016) in their research to determine the racial and ethnic disparities in health care access and utilization under A.C.A. defined the measured outcome variables in three main aspects that included the probability of insurance, probability of having medical care delay, and the probability of having foregone medical care. Through the defined aspects, the researchers measured the changes in the dependent variable which is the health care coverage among the racial and ethnic groups.  Definition of Terms The Federal Poverty Level (F.P.L.) indicates the lowest amount of yearly income of a household which provides that they are eligible for receiving certain welfare benefits. Random-digit dialing is a probability sampling technique that uses randomly generated telephone numbers in statistical surveys. Nonresponse bias is an error that occurs when participants of a study are unwilling to respond to a survey due to an aspect that makes them differ from those who respond.  Procedures The research uses document review to collect appropriate data to accept or reject the hypotheses of the study. This allows the study to obtain results quickly and at a low cost. By using six different studies, it is possible to provide accurate information and also eliminates errors that might result due to data collection from primary subjects. The statistical procedure used in testing the hypotheses of the study relates to techniques that the researchers, whose data have been included in the research, used in answering their research questions or testing hypothesis. As such, this study does not depend on a single technique but rather draws conclusions based on different techniques. The following are procedures that the researchers used in their studies.  Sommers et al. (2017) used a survey to collect data from various participants that they selected through the random-digit dialing method. The study then implemented a linear regression model on the data they collected during the four years and from different states. The data was then taken through an instrumental variable analysis that included a two-stage least squares regression. In the first step, the researchers predicted the probability of an individual having health insurance, and the second stage involved the provision of an estimate of the impact of A.C.A.  Based on data presented from different surveys used in the study, Dickman et al. (2016) examined the trends related to per capita health spending. The analysis method that the authors used explored trends related to income according to data of individuals on payment, service type, and self-reported health status. The researchers then divided the population represented in the survey into equal quintiles and used the federal poverty level to categorize income from different families as a percentage of poverty. Additionally, Dickman et al. (2016) categorized health services into groups including inpatient care, outpatient care, dental care, and prescription medicines to accurately calculate the total health expenditure.  Buchmueller et al. (2016) used the data from the American Community Survey to examine the differences in healthcare coverage in terms of health insurance cover of the individuals. The researcher implemented three approaches in evaluating disparities. The approaches included comparing unadjusted differences in means, calculating means after controlling health needs and preferences of the individuals, and lastly, getting differences in mean for various variables that significantly affect the health status of individuals like socioeconomic status. Regarding the study conducted by Sommers et al. (2016), the researchers used multivariable linear regression which is a statistical technique for predicting an outcome based on the response of a given variable. The study used the technique to analyze the outcomes before the expansion of Medicare under A.C.A. and after its expansion. The researchers then compared the outcome from Arkansas and Kentucky with the control state, Texas, to assess the impact of health insurance coverage expansion. Based on the data from Annual Social and Economic Supplement, Christopher et al. (2016) used the Gini index, a technique for measuring income distribution across a population, to evaluate income inequality. First, the researchers calculated the Gini index based on the total income of a family and then subtracted medical outlays. Additionally, the researchers further explored the data by calculating the net income changes that are attributable to the outlays to explore the difference existing for groups. Chen et al. (2016) used survey weights to adjust sample characteristics thus preventing the occurrence of nonresponse bias. The authors implemented linear probability models for the estimation of trends in health care access and utilization for the groups after the introduction of A.C.A. The models took into account factors such as predisposing factors, enabling factors like family income, and the need factors for the population. Additionally, the researchers examined the different exposures of Obamacare for specific ethnic and racial groups to determine the relation between A.C.A. indicator and racial or minority groups. Limitations The research on the impacts of the Affordable Care Act: improved medical care and health among low-income adults may be limited by the sample since it uses a sample from only three states and therefore might not apply to the general American population. This may affect the research due to the sampling method. Additionally, using the random-dialing digit may make it difficult to recruit targeted respondents thus affecting the outcome of the research. Some of the limiting factors to the research on Health Spending For Low-Middle- And High-Income Americans regard the method of data collection as it might not cover all the necessary information that addresses the aspects of the study.  The study conducted by Buchmueller et al. (2016) might be limited by the accuracy of the information presented in the existing data sources. As such, this might also limit this research since the information is due to dependence on the already presented data where there is no control over data included in the research. The various potential limitations to the study conducted by Sommers et al. (2016) include nonresponse bias which might result from the data collection method, random-digit dialing survey. This results in low response rates, below the federal government surveys. However, using weighting for the population features has the potential of mitigating nonresponse bias. Another potential limitation to the study regards the states involved in the research. This may not adequately reflect the situation of the general population in American. As such, this will limit the application of the research’s findings. Various limitations that might affect the outcomes of research conducted by Christopher et al. (2018) on the medical expenditures on Income inequality include the method of data collection the researchers implemented. In this regard, they have no control of the data that should be included and the ones to be excluded in the research and as a result, it might significantly affect the results of the study. Another limitation to the study relates to the scope provided by the data that was implemented in the study. According to the authors, the data provides a scope that is beyond their study. Some of the factors that might limit the use of Chen et al.s (2016) findings include being too much dependent on the existing data which affects the outcome of the research. However, this might result in the wrong prediction. The study investigated a portion of the aspects that regards the changes in health care quality and outcomes under the implementation of A.CA. Besides, the data might not provide specific information on the various racial and ethnic subgroups that significantly impact the outcome of the research. References Buchmueller, T. C., Levinson, Z. M., Levy, H. G., & Wolfe, B. L. (2016). Effect of the Affordable Care Act on racial and ethnic disparities in health insurance coverage. American journal of public health, 106(8), 1416-1421. Chen, J., Vargas-Bustamante, A., Mortensen, K., & Ortega, A. N. (2016). Racial and ethnic disparities in health care access and utilization under the Affordable Care Act. Medical care, 54(2), 140. Christopher, A. S., Himmelstein, D. U., Woolhandler, S., & McCormick, D. (2018). The effects of household medical expenditures on income inequality in the United States. American Journal of Public Health, 108(3), 351-354. Dickman, S. L., Woolhandler, S., Bor, J., McCormick, D., Bor, D. H., & Himmelstein, D. U. (2016). Health spending for low-, middle-, and high-income Americans, 1963–2012. Health Affairs, 35(7), 1189-1196. Sommers, B. D., Blendon, R. J., Orav, E. J., & Epstein, A. M. (2016). Changes in utilization and health among low-income adults after Medicaid expansion or expanded private insurance. JAMA internal medicine, 176(10), 1501-1509. Sommers, B. D., Maylone, B., Blendon, R. J., Orav, E. J., & Epstein, A. M. (2017). Three-year impacts of the Affordable Care Act: improved medical care and health among low-income adults. Health Affairs, 36(6), 1119-1128.