For aging populations age 65 years and older, lack of social engagement, or social isolation, is a public health issue that can have serious health implications. The ability to engage socially can decrease with aging populations due to many factors, such as health status and mobility. As social engagement decreases, the potential for serious diseases, such as dementia, increases. Limited social connections and engagement can be linked to healthcare utilization through increased rates of re-hospitalization as well as potentially decreased ability to and increased need to regularly access physician services. The aim of this research is to expand on the existing body of work in the area of care access and social isolation among aging populations, to examine the relationship between physician office visits and social activity and what differences may exist between those who live in urban and non-urban settings. A cross-sectional analysis was conducted using data from the Fall 2019 Medicare Current Beneficiary Survey (MCBS). The number of physician office visits participants have annually was the variable of primary interest. Physician visits were categorized dichotomously into moderate or no use and high use. Individuals with 11 or more visits were considered to be high utilizers within this data set and those with 10 visits or less as low. The key independent variables in this analysis are social activities and geography of the respondent. Social activities are defined has having social limitations, from respondents indicating limited activities most or all of the time in the past month, or low limitations, indication of some or no limitation of activities within the past month. Metropolitan Statistical Area (MSA) was used to categorize respondents as residing in an urban or rural community. The study population included 11,670 individuals over the age of 65. Approximately 15% of respondents were categorized as high health service utilizers and 85% were low or average. Only 7% of respondents were noted as having high levels of restrictions on social activities. The majority (81%) of respondents were classified as residing in a metro area compared to 19% residing in non-metro areas. High restrictions on social activities were associated with higher numbers of physician visits Approximately 10.6% of individuals with high social restrictions were also categorized as having higher numbers of physician visits compared to 6.6% among those with low social restrictions (OR=1.667; 95%CI: 1.47-1.89). No associations between geography and physician visits were noted. This study found a relationship between restricted social engagement and higher utilization of physician services. These findings were not consistent when adjusting for additional covariates of interest. Because poor general health can play a large part in both the ability to engage socially and high utilization of physician visits in aging populations, these findings underscore the importance of enhancing community services and opportunities for social engagement as health policy tools for improving health and quality of life for aging individuals.

Indiana University-Purdue University Indianapolis (IUPUI) / Poor oral health is associated with pain, decreased chewing function, negative social perceptions, and reduced quality of life. Low-income adults disproportionally have worse oral health and use dental services at lower rates than higher-income adults. This disparity is associated with individual demographic and socioeconomic factors, cost and coverage barriers, as well as the supply and location of dental providers. Although the full causal pathway remains elusive, evidence suggests an association with poor oral health and an exacerbation of chronic diseases symptoms. Thus, adequate provision of dental care has important population health implications. Despite this importance, dental care use among low-income adults is particularly underexplored. Furthermore, existing research lacks robust methodological designs to mitigate bias from unobserved confounders. Dental coverage for low-income adults through Medicaid is emerging as a way to provide services to this population. However, given state budget constraints, comprehensive public dental benefits are uncommon or at risk of being cut. Therefore, it is important to quantify the individual and economic value of dental care use among adult Medicaid enrollees. This dissertation examines factors and outcomes associated with dental care use among Medicaid-enrolled adults in Indiana. This dissertation includes three studies 1) a pooled cross-sectional analysis that measures the association of individual and community level factors with dental care use, 2) a repeated measures study with individual fixed effects to examine whether receipt of preventive dental care is associated with fewer subsequent non-preventive dental visits and lower total annual dental expenditures, and 3) an empirical study that utilizes an instrumental variable estimation method to examine the effect of preventive dental visits on medical and pharmacy expenditures. Overall, this dissertation attempts to understand the correlates of dental care use, the effectiveness of preventive dental care, and the association between preventive dental care and medical expenditures.

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<p dir="ltr">The electronic health record (EHR) documents the patient’s medical history, with information such as demographics, diagnostic history, procedures, laboratory tests, and observations made by healthcare providers. This source of information can help support preventive health care and management. The present thesis explores the potential for EHR-driven models to predict acute care utilization (ACU) which is defined as visits to an emergency department (ED) or inpatient hospitalization (IH). ACU care is often associated with significant costs compared to outpatient visits. Identifying patients at risk can improve the quality of care for patients and can reduce the need for these services making healthcare organizations more cost-effective. This is important for vulnerable patients including those suffering from schizophrenia and bipolar disorders. This study compares the ability of the MedBERT architecture, the MedBERT+ architecture and standard machine learning models to identify at risk patients. MedBERT is a deep learning language model which was trained on diagnosis codes to predict the patient’s at risk for certain disease conditions. MedBERT+, the architecture introduced in this study is also trained on diagnosis codes. However, it adds socio-demographic embeddings and targets a different outcome, namely ACU. MedBERT+ outperformed the original architecture, MedBERT, as well as XGB achieving an AUC of 0.71 for both bipolar and schizophrenia patients when predicting ED visits and an AUC of 0.72 for bipolar patients when predicting IH visits. For schizophrenia patients, the IH predictive model had an AUC of 0.66 requiring further improvements. One potential direction for future improvement is the encoding of the demographic variables. Preliminary results indicate that an appropriate encoding of the age of the patient increased the AUC of Bipolar ED models to up to 0.78.</p>

The number of persons who are not employed has increased in Sweden since the early 1990s. Unemployment has been found to influence health, especially when unemployment rates are low. The extent to which unemployment affects health when unemployment is high is less clear, and this needs to be further studied. To improve health in the population, the health care system should offer equal access to health care according to need. It is important to study whether the employment status hinders the fulfilment of this goal. This thesis is based on four papers: Paper I and II aimed at analysing self-rated health versus mortality risk in relation to employment status, during one period of low unemployment and one period of high unemployment. Paper III and IV assessed the use of medical health care services and unmet care needs among persons who were unemployed or otherwise not employed. The goal was to analyse what health problems lead people to either seek or abstain from seeking care, and what factors encumber or facilitate this process. The overall results indicate that being unemployed or outside the labour force was associated with an excess risk of poor self-rated health, symptoms of depression, mental and physical exhaustion and mortality. The differences in self-rated health between the unemployed and employed were larger when unemployment levels were high, than when they were low. More groups of the unemployed were also afflicted with poor health when unemployment was high. Thus, poor health among the unemployed seems to be a public health problem during high levels of unemployment. Lack of employment was related to abstaining from seeking care, despite perceiving a need for care, and this was related to psychological symptoms. To deal with the needs of the unemployed and others who are outside the labour force it would be useful to develop and implement interventions within the health care system. These should focus on psychological and psychosocial problems. Future research should analyse how to facilitate health-promoting interventions among persons who are not anchored in the labour market.

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Individuals with overweight/obesity have been found to exhibit more negative attitudes toward health care and disproportionate rates of health care delay and avoidance, compared to their healthy weight peers. The present study sought to examine potential mechanisms through which weight status influences health care utilization and attitudes. Six hundred and thirty-three students completed a questionnaire measuring weight status, perceived weight bias, patient-provider relationship, and health care utilization and attitudes. Although the majority of the paths in the proposed theoretical mediation model were supported by the present findings, there was no support for the anticipated link between perceived weight bias and the patient-provider relationship or weight-related embarrassment. Overall, these results corroborated previous findings in a novel sample, but did not provide evidence that perceived weight bias mediates the relationship between weight status and health care outcomes. Possible explanations for these findings are deliberated.

A model for health care utilization was applied to a sample of low income women. Demographic Predisposing, Psychosocial Predisposing, Illness Level, and Enabling indicators were examined separately for African American (n = 266), Anglo American (n = 200), and Mexican American (n = 210) women. Structural Equation Modeling revealed that for African American and Anglo American women, Illness Level, the only significant path to Utilization, had a mediating effect on Psychosocial Predisposing indicators. The model for Mexican Americans was the most complex with Enabling indicators affecting Illness Level and Utilization. Psychosocial Predisposing indicators were mediated by Illness Level and Enabling indicators which both directly affected Utilization. Implications of the results for future research are addressed.