Insurance is a vital factor in the billed cost to the patient, but to what degree does insurance explain the amount a patient is left to pay? Also, does obesity further influence patient’s billed cost? This thesis assesses the type of thoracic trauma patient, insurance status, and their billed cost. Database variables were analyzed in IBM SPSS 25. Table 1 characteristics were evaluated based on demographics and systematic hospital factors. Linear regressions used Private0_Government1 and BMI Obese n_y_ as independent variables while Total Patient Cost was the dependent variable. Private0_Government1 insurance explained .03% of Total Patient Charges. Private0_Government1 and BMI Obese n_y_ explained 1.4% of Total Patient Charges. Private0_Government1 and BMI Obese n_y_ explained a low percentage of Total Patient Charges. This shows that there are factors other than insurance type and obesity that are influential upon patient charges.

Valvular disease affects the heart's valves and can lead to complications if left untreated. In 2017, about 2.7% (U. S) of the population had a valvular disease. The Centers for Disease Control and Prevention (CDC) also estimated that about 2500 Americans die yearly due to valvular disease. Several factors, such as the type of valvular disease, can affect the outcome of this disease. However, the hospital type, insurance status, and location of the patients may determine the quality of care and valvular disease outcome. Teaching hospitals are often in urban regions and house various well-grounded specialists as well as tools and equipment that may be a significant contributory factor to the outcome of Valvular heart disease. This study aims at determining the importance of quality of healthcare access in the outcome of valvular disease. At the bivariate analysis level, it was hypothesized that the type of hospital, location of patients, and age at diagnosis are significantly related to the outcome of valvular disease. At the multivariate level, it was hypothesized that after controlling for every other variable, the predictor variables were significantly related to the outcome of valvular disease. Data analysis was conducted on cross-2012 sectional National Inpatient Survey (NIS) data. The Core, severity, and hospital data were used for this analysis. Descriptive statistics and bivariate and multivariate logistic regressions were conducted to assess the association between the outcome of valvular disease and the type of hospital (teaching or non-teaching), patient location, age at diagnosis, insurance, income, and sex. All analysis was performed using the Statistical Analysis System (SAS). The results of the descriptive study showed about 2.9% of patients had comorbidity from valvular disease. Patients attending teaching hospitals had a 0.3% comorbidity present (P =.001). At the multivariate analysis level, patients at the teaching hospital were less likely to have comorbidity compared to individuals at non-teaching (AOR = 0.735; CI = 0.549, 0.970, P = 0.0303). Patients with public or no insurance were less likely to have a comorbidity of valvular disease as compared to patients with private insurance (AOR =0.596, AOR =0.288; CI = 0.393, 0.904 CI= 0.120, 0.692 P= 0.0149 P= 0.0054 respectively). Also, males were less likely to have valvular heart disease comorbidity as compared to females. All other variables not mentioned were not significant in the multivariate analysis. Accreditation programs can ensure that non-teaching hospitals have the necessary resources, equipment, and personnel to manage the valvular disease. Furthermore, providing incentives, such as financial support or performance-based incentives, can encourage non-teaching hospitals to invest in the necessary resources and personnel to manage valvular heart disease. We also recommend awareness campaigns and screening programs for patients in rural regions.

The purpose of this study was to investigate the relationship between health insurance status and diabetes management (in terms of medication adherence and physical activity levels) in Black adults based on socioeconomic factors. Data were harvested from the Sample Adult Questionnaires of the National Health Interview Survey (NHIS) between the years of 2010 and 2016. The survey questions that were collected included information about the participants' income, education level, insurance status, diabetes diagnosis, medication therapy and physical activity levels. This study employed the most recent version of the Statistical Package for Social Sciences (SPSS) software. The association between diabetes management and socioeconomic factors were analyzed using chi-square analysis. It was hypothesized that Black adults who were uninsured, lower income, and less-educated would report lower adherence to medication and lower physical activity participation when compared to their insured, higher income, and higher-educated counterparts. However, there was no statistically significant relationship between health insurance status and diabetes management in people of different socioeconomic status. Too few people met the weekly recommendations for moderate exercise thus chi-square outcomes for physical activity were invalid. This study will be beneficial for future research as it has provided more generalizable information on this topic due to the use of a national dataset. This study also highlighted the importance of adequate physical activity interventions for this population and can be used for further research on Black adults with diabetes.