Theses and Dissertations from UMD
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Item DIET, FOOD SECURITY, SOCIAL RELATIONSHIPS AND DEPRESSIVE SYMPTOMS IN HOMEBOUND OLDER ADULTS IN THE UNITED STATES AND THEIR IMPACT ON HEALTHCARE UTILIZATION(2020) Ashour, Fayrouz A.; Sahyoun, Nadine R; Nutrition; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Homebound older adults may be at increased risk for malnutrition and social isolation, posing a potential threat to them aging in their communities and increasing healthcare cost. The Nutrition Service Program under Older Americans Act (OAANSP) was established to support older adults aging in place by delivering meals and providing nutrition-related services. Aims: 1) Examine diet quality of home-delivered meal (HDM) recipients; 2) examine direct and indirect associations between social relationships, depressive symptoms, food insecurity (FI) and diet quality; and 3) examine direct and indirect associations between social relationships, FI, diet quality and hospitalization. Methods: Data obtained from OAANSP Outcomes Evaluation study included: 1) client outcomes survey, 2) two 24-hour dietary recalls, and 3) Medicare healthcare utilization data. Dietary recalls examined diet quality by calculating 1) population-level mean HEI scores; and 2) usual vegetable and protein intakes. Diet quantity was compared to Dietary Guidelines for Americans 2010 (DGA), and structural equation modeling was used to examine direct and indirect relationships. Results: HDM recipients and controls have high prevalence of FI, 22.4% and 16.5%, respectively. HDM recipients who did not receive a meal on day of dietary recall (no-meal recipients) had significantly poorer diet quality than HDM recipients who received a meal (meal recipients) that day and control group. Quality of overall diet for meal recipients, no-meal recipients and controls did not meet recommendations for several food groups/nutrients. Compared to DGA, HDM and complementary foods were low in whole grains, dairy, fiber, and surpassed upper limit of consumption for saturated fats, refined grains, sodium and added sugar. High FI was associated with greater depressive symptoms and lower usual vegetable intake in control group. High FI was associated with lower usual protein intake in HDM recipients and controls. Both groups were at high risk for protein insufficiency, which was associated with greater hospitalization in the control group. Conclusions: HDM recipients and controls have high prevalence of FI, poor diet quality, and insufficient protein intake. Increasing funding for OAANSP can allow program expansion and improvement of HDM. Validated tools to examine social relationships and additional contributors to FI are neededItem RACIAL AND ETHNIC DIFFERENCES IN ACCESSING TIMELY CANCER SCREENING AND TREATMENT SERVICES: A QUANTITATIVE ANALYSIS(2013) King, Christopher Jerome; Thomas, Stephen B.; Chen, Jie; Health Services Administration; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This research is organized into three integrated studies that explored differences in screening and treatment services across the cancer care continuum by race and ethnicity. The Andersen Behavioral Model of Health Services Use and the Five Dimensions of Access were used as conceptual frameworks. In the first study (Chapter 2), data from the Medical Expenditure Panel Survey were used to examine breast and cervical cancer screening rates before and during the Great Recession (2007-2009). The interaction terms of recession and race and ethnicity were controlled to examine whether minorities exhibited different utilization patterns under economic shock compared to Whites. In Chapter 3, data from the National Health Interview Survey (NHIS) from 2006-2010 were used to identify adult cancer survivors and adults without a history of cancer. Multivariate logistic regressions were applied to examine the prevalence of cost, organizational and transportation barriers between survivors and the general population. The likelihood of experiencing barriers was explored by race and ethnicity. In Chapter 4, differences in the likelihood of experiencing access barriers among survivors by race and ethnicity was explored. Data were merged from the 2000-2011 (NHIS) to identify adult cancer survivors who reported cost, organizational and transportation barriers. Logistic regressions were applied to determine the likelihood of reporting each type of barrier, while controlling for demographic and socioeconomic variables. The Fairlie decomposition technique was applied to identify contributing factors that explained differences in accessing care based by race and ethnicity. Overall, results of the investigations demonstrate that: (1) breast and cervical screening rates declined most among White women during the recession period, while rates increased among Hispanic women during the same period; (2) minority cancer survivors were significantly more likely to experience access-to-care barriers than Whites; and (3) insurance, comorbidity, perceived health and nativity were leading factors that contributed to racial and ethnic differences in timely receipt of cancer screening and treatment services. As provisions of the Affordable Care Act take effect, findings provide insight into practices, policies, and future research that will help achieve Healthy People 2020 screening objectives and reduce racial and ethnic disparities in accessing timely cancer care.Item QUALITY OF PAST EXPERIENCES WITH HEALTHCARE PROVIDERS, LEVEL OF SELF-EFFICACY, AND DEGREE OF TRUST IN PROVIDERS AS DETERMINANTS OF PROVIDER AVOIDANCE: TESTING THE MODERATING EFFECTS OF RACE AND GENDER(2012) McDowell, April; Epstein, Norman B; Family Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A critical component in the prevention and treatment of illness and disease is individuals' timely and consistent consultation with healthcare providers. The purpose of the current study was to examine factors influencing individuals' avoidance of healthcare providers in a national sample of insured U.S. adults who potentially have access to healthcare but may not use it. Inadequate access to healthcare as a function of disparities (e.g., lack of health insurance) has increasingly received attention. However, there has been a lack of attention to factors that interfere with use of healthcare among individuals who potentially have access based on insurance coverage. Those individuals are at risk of negative health outcomes when they avoid medical consultation for serious health symptoms. Consequently, the present study examined factors influencing healthcare avoidance among individuals who have health insurance. A secondary analysis was conducted with a publically available data set, the 2007 Health Information National Trends Survey (NCI, 2009). The study examined the extent to which health self-efficacy, quality of past interactions that an individual has had with healthcare providers (HCPs), and trust in HCPs to take care of one's health needs predicted current avoidance of HCPs. The study also examined individuals' levels of trust in HCPs as a potential mediator of the relationship between the quality of interactions with HCPs and the degree to which individuals avoid HCPs, as well as patient race/ethnicity and gender as potential moderators of the relationship between quality of interactions with HCPs and trust in HCPs. Control variables included age, education, and income. Results provided support for the expected relationships between health self-efficacy, quality of interactions with HCPs, and trust in HCPs, and HCP avoidance. Furthermore, results revealed that trust in HCPs is a significant mediator between quality of interactions with HCPs and HCP avoidance. However, results did not provide support for race/ethnicity and gender as clinically significant moderators between quality of interactions with HCPs and trust in HCPs. Findings provide useful information about factors that influence individuals' avoidance of HCPs, thereby identifying targets for reducing this problematic public health phenomenon. Implications for theory, research, practice, and policy are presented.Item Social Preferences Among Clinicians in Tanzania: Evidence from the Lab and the Field(2011) Brock, J. Michelle; Leonard, Kenneth L.; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Health worker effort can have a dramatic influence on patient outcomes. This is especially true in developing countries, where poor overall quality of healthcare systems is the norm. There is evidence, however, that despite low levels of education and experience, clinicians in Tanzania underperform relative to their ability (Leonard and Masatu, 2005). Understanding clinicians' intrinsic motivations may help us identify nonmonetary incentives for improving quality of care. To this end, this dissertation considers how risk, pride and social information impact altruism among Tanzanian clinicians. In Chapter 4, we study how risky environments impact social preferences. With experimental evidence from games with risky outcomes, we establish that social preferences of players who give in standard dictator games are best described by consideration of equating ex ante chances to win rather than of ex post payoffs. The more money decision-makers transfer in the dictator game, the more likely they are to equalize payoff chances under risk. Risk to the recipient does, however, generally decrease the transferred amount. Also, while some people behave generously regardless of the attributes of others, pride and knowledge about the recipient characteristics may also motivate altruistic behavior. In Chapter 5, we explore the role of social information and pride in determining pro-social behavior among clinicians in Tanzania. We find that making someone feel proud increases the number of "fair" allocations (50/50 giving) and that those who do not respond to decreased partner anonymity are less responsive to induced pride. Chapter 6 combines laboratory data on social preferences and field data on clinicians' workplace effort. This study is unique in that we observe the same subjects from the laboratory in a field setting, where pro-social behavior has large welfare impacts. We use modified dictator games to define subjects as fair types, social information responsive types and pride responsive types and test how those characteristics are correlated with effort in the workplace. We find that clinicians responsive to both pride and social information provide higher than average effort in the workplace. These results are suggestive of Ellingsen and Johannesson's (2008) theory of social preferences wherein social identity and esteem interact to motivate altruism.Item Prioritizing Patients: Stochastic Dynamic Programming for Surgery Scheduling and Mass Casualty Incident Triage(2011) Herring, William L.; Herrmann, Jeffrey W; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The research presented in this dissertation contributes to the growing literature on applications of operations research models to problems in healthcare through the development and analysis of mathematical models for two fundamental problems facing nearly all hospitals: the single-day surgery scheduling problem and planning for triage in the event of a mass casualty incident. Both of these problems can be understood as sequential decision-making processes aimed at prioritizing between different classes of patients under significant uncertainty and are modeled using stochastic dynamic programming. Our study of the single-day surgery scheduling problem represents the first model to capture the sequential nature of the operating room (OR) manager's decisions during the transition between the generality of cyclical block schedules (which allocate OR time to surgical specialties) and the specificity of schedules for a particular day (which assign individual patients to specific ORs). A case study of the scheduling system at the University of Maryland Medical Center highlights the importance of the decision to release unused blocks of OR time and use them to schedule cases from the surgical request queue (RQ). Our results indicate that high quality block release and RQ decisions can be made using threshold-based policies that preserve a specific amount of OR time for late-arriving demand from the specialties on the block schedule. The development of mass casualty incident (MCI) response plans has become a priority for hospitals, and especially emergency departments and trauma centers, in recent years. Central to all MCI response plans is the triage process, which sorts casualties into different categories in order to facilitate the identification and prioritization of those who should receive immediate treatment. Our research relates MCI triage to the problem of scheduling impatient jobs in a clearing system and extends earlier research by incorporating the important trauma principle that patients' long-term (post-treatment) survival probabilities deteriorate the longer they wait for treatment. Our results indicate that the consideration of deteriorating survival probabilities during MCI triage decisions, in addition to previously studied patient characteristics and overall patient volume, increases the total number of expected survivors.Item A DATA ANALYTICAL FRAMEWORK FOR IMPROVING REAL-TIME, DECISION SUPPORT SYSTEMS IN HEALTHCARE(2010) Yahav, Inbal; Shmeuli, Galit; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to differentiate between models that are based on known baseline behavior and those based on a baseline with missing information. We apply and illustrate the framework in the context of two important healthcare contexts: biosurveillance and kidney allocation. In the biosurveillance context, we address the problem of early detection of disease outbreaks. We discuss integer programming-based univariate monitoring and statistical and operations research-based multivariate monitoring approaches. We assess method performance on authentic biosurveillance data. In the kidney allocation context, we present a two-phase model that combines an integer programming-based learning phase and a data-analytical based real-time phase. We examine and evaluate our method on the current Organ Procurement and Transplantation Network (OPTN) waiting list. In both contexts, we show that our framework produces significant improvements over existing methods.