Best international health practice requires that all people benefit equally from health care services regardless of their socio-economic status and that healthcare payments be based on ability to pay. Although recent household surveys in Malawi show progress in a number of health indicators population averages, many inequalities in health outcomes still exist or are widening among households stratified by socioeconomic and geographical location variables. Inequalities in out-of-pocket expenditures (OOPEs) for healthcare and how they influence utilization of healthcare services are of particular interest to policy makers as they ultimately affect overall health of households. The rationale for this study is that analysis of inequities in healthcare between socioeconomic groups can help to unmask intra-group and between groups' inequities hidden in national population averages. The study's three main papers examined equity in households' out-of-pocket healthcare payments and utilization of medical care. The study adopted the widely used economic frameworks and techniques developed by O'Donnell et al (2008) for analyzing health equity using household data. These economic frameworks focus on the notion of equal treatment for equal need and that payment for healthcare should be according to ability to pay. The Malawi Integrated Household Survey 2(2005) (MIHS2) was the main dataset used in the analysis. The MIHS2 is currently the only dataset that presents inequalities in healthcare expenditures at the household level in Malawi. However, the MIHS2 report does not examine the extent to which these inequalities are inequities. It is in this context that the first study focused on assessing, first, the progressivity of OOPEs for healthcare and second, the redistributive effect of OOPEs for healthcare as a source of finance in the Malawi health system. The progressivity results indicate that OOPEs for healthcare are relatively regressive in Malawi with the poor shouldering the highest financial burden relative to their ability to pay. The study found no evidence of redistributive effect of OOPEs on income inequalities in Malawi. The second study focused on linking OOPEs to use of healthcare using the recommended two-part model (Probit and OLS). The concentration indices were decomposed into contributing factors after standardizing for health need factors, which include age, sex, self-assessed health, chronic illness and disabilities. Probability of use of healthcare and OOPEs were both found to be concentrated among the non-poor while the poor who have higher health need have less use of healthcare. The last study assessed the socioeconomic factors associated with horizontal equity in use of medical facilities and predicted use using logistic regression. General medical facilities use was found to be more concentrated among the non-poor despite the poor having a higher health need. The results showed no significant inequalities in use of public medical facilities and self-treatment between the poor and the non-poor. Overall, inequalities in healthcare utilization and out-of-pocket healthcare expenditures in Malawi are mainly influenced by socioeconomic factors, which are non-need factors than health need factors. Inequalities due to non-need factors suggest presence of inequities, which are avoidable and unjust. This study can help policy makers have a better understanding of the possible effects of OOPEs and help in explaining the factors contributing to inequities in medical care utilization in Malawi. Such information is necessary so that highest priority should be given to the health problems or challenges disproportionately affecting households with varying levels of socioeconomic privilege. / Graduation date: 2012

There is a growing interest in the impact of waiting for surgery, a common experience for many Canadians. Pain and psychological symptoms prior to surgical management are frequently problems for women with gynaecological conditions, however minimal research was found to investigate pain and psychological symptoms in these women prior to surgery. Also pain is recognized to increase healthcare utilization, but this has not been previously examined in this population. The objectives of this research project were to examine levels of pain, psychological factors associated with pain and frequency of healthcare utilization due to pain in a population of women waiting for gynaecological surgery, predominantly undergoing hysterectomies. Four hundred and twenty nine women in a tertiary care centre in southeastern Ontario were included in the study. Anxiety was measured using the State Trait Anxiety Inventory (STAI), depression with the Centre for Epidemiologic Studies Depression Scale (CES-D), somatization using the Seven Symptom Screening Test (SSST) and catastrophizing was measured using an abbreviated coping strategies questionnaire (CSQ). Pain was assessed using the Brief Pain Inventory (BPI). Women also reported on their healthcare utilization for pain over the past 12 months. The length of wait was obtained from hospital waiting data. Results showed a moderate to severe pain intensity score occurred in 30.5% of women and a moderate to severe interference score in 31.5%. Being younger, married, employed and with high trait anxiety were factors associated with higher rates of healthcare utilization. High levels of depression, somatization and catastrophizing were associated with higher pain intensity and interference scores. This study supports the need for preoperative assessment of physical and psychological symptoms in women waiting for gynaecological surgery. Improving patients’ health prior to surgery will potentially reduce their healthcare demands on a financially constrained healthcare service. / Thesis (Master, Nursing) -- Queen's University, 2009-09-25 12:31:28.298

No description available.

Advances in surgical technique and medical management have led to fundamental changes in surgical care allowing for a paradigm shift from inpatient to outpatient surgery. Enhanced recovery pathways have moved surgical recovery from inpatient to outpatient settings requiring informal caregiver support. The purpose of this study was to determine the prevalence of caregiver burden in this patient population and to explore whether caregiver burden contributes to preventable use of emergency room services. The conceptual framework supporting this retrospective cross-sectional study was Andersen's behavioral model of health services utilization. Data collected from 28 urologic patient/caregiver pairs were analyzed using descriptive statistics and linear and logistic regression. Findings indicated measurable caregiver burden in 2 of the 5 Caregiver Reaction Assessment (CRA) subscales: impact on schedule and impact on health. Findings also indicated a measurable protective effect of high socioeconomic status of caregivers and the CRA subscale of impact on finances, and a possible protective effect of caregiver self-esteem as measured by the CRA subscale and emergency room utilization within the first 30 days after enhanced recovery surgery. Social change implications include improving the surgical experience of patients and caregivers and enhancing the use of health care resources.

No description available.

In recent years, there has been increased focus on rural and Appalachian health because of disparate chronic health outcomes when compared to the rest of the US. Appalachia, a subsection of the US, has even worse health outcomes related to chronic diseases. Although Appalachia is its own unique region, there is significant overlap with rural areas in terms of shared cultural characteristics (e.g., strong sense of community, distrust in outsiders, lack of trust in traditional medicine, and strong Christian religious affiliations and faith in God), limited access to healthcare services, and disparate health outcomes. The research presented in this dissertation is significant because it provides insight into and compares healthcare utilization rates in women in Appalachia and surrounding areas. Study 1: In addition to racial discrimination, Black Appalachian women often face other obstacles involving other types of negative interpersonal experiences when seeking healthcare. Despite these known disparities, Black women are frequently underrepresented in Appalachian health research. This study investigated healthcare experiences for sixteen Black Appalachian women using semi-structured interviews to identify and subsequently address ways to eliminate barriers to care. Interview questions utilized the theory of intersectionality and the Social Ecological Model to create a framework to describe the complexity of healthcare utilization and barriers to care while providing context into each participant's background and lived experience. Interview questions explored four topics: 1) barriers to medical care; 2) social support; 3) ideal and actual healthcare experiences; and 4) desired changes to improve quality of care. We used an inductive analysis process to create a robust thematic coding schema, organizing responses into 60 total themes and 141 codes, and reported the most frequent. Our results explore the ways in which one's intersectional identity as a Black Appalachian woman affects interpersonal interactions and experiences when engaging with the healthcare system. Participants frequently reported barriers related to scheduling conflicts and delays, experiences with rushed appointments and inhospitable providers and support staff, and desires for accurate collection of medical information. Participant responses often emphasized difficulties with the organization of the medical system, revealing specific areas for future intervention to improve quality of care for Black Appalachian women. Study 2: Use of the emergency department (ED) for low acuity conditions (e.g., back pain, dental pain, sore throat) and primary care places an additional strain on ED staff and resources, while increasing waiting and treatment times for high acuity patients. Factors such as race, gender, and insurance type have a strong association with the likelihood of a patient using the ED for a low acuity concern. Women are more likely to utilize healthcare services, which also holds true in the context of the ED. Using a sample of adult women from Virginia, West Virginia, Tennessee, North Carolina, and Kentucky, I investigated which demographic factors, age, race, geographic location (metro, nonmetro, rural), employment, and insurance coverage, affect a patient's likelihood to visit the ED for a low acuity condition within a southwestern Virginia hospital system. Log-binomial regression was used to estimate unadjusted and adjusted prevalence ratios of acuity level by race, age, rurality level, employment, and insurance type with corresponding 95% CIs. Our sample included 28,222 female patients who visited the ED between January 1, 2021 and September 30, 2022. Low acuity visits accounted for 15.9% (n=4,485) of visits during the timeframe. In summary, our results suggest that older age and location in non-metro area are the most salient factors contributing to a higher likelihood of low acuity ED visits among women. Race, a primary variable of interest, did not have the relationship to acuity that was expected based on previous literature; Black women patients were less likely to have a low acuity visit than white women patients. During our study period, overall number of visits remained steady, while there was an increase in proportion of low acuity visits. Further research is needed into the underlying causes to more definitively explain this increase. / Doctor of Philosophy / In recent years, there has been increased focus on rural and Appalachian health because of disparate chronic health outcomes when compared to the rest of the US. Appalachia, a subsection of the US, has even worse health outcomes related to chronic diseases. Although Appalachia is its own unique region, there is significant overlap with rural areas in terms of shared cultural characteristics (e.g. strong sense of community, distrust in outsiders, lack of trust in traditional medicine, and strong Christian religious affiliations and faith in God), limited access to healthcare services, and disparate health outcomes. Black/African Americans are another population with higher rates of chronic disease and poorer health outcomes compared to their white and Latinx peers. The combination of poorer health outcomes and higher rates of chronic disease negatively impacts life expectancy and quality of life. One driving factor in these poor health outcomes across all of these groups is low rates of healthcare utilization, whether due to decreased access (as is the case for many rural populations), or other as of yet unidentified challenges. Although literature exists about rural health outcomes, Appalachian health outcomes, and health outcomes focusing on Black women, there is very limited literature that examines the intersectional impact of these characteristics on health. Health disparity research in this region does not currently stratify differences in outcomes by both race and gender, which prevents a detailed analysis of the full extent of the gap in health outcomes. This research presented in this dissertation is significant because it provides insight into and compares healthcare utilization rates in women in Appalachia and surrounding areas across the lifespan. Knowing the contextual factors influencing healthcare seeking behaviors and utilization is the first step to designing effective interventions that improve women's access to care. Interventions need to be intentionally designed to consider, and ultimately, shift medical care and community attitudes to decrease health disparities in Appalachia. To successfully decrease health disparities, it is necessary to consider all of a patient's identities or characteristics. The same contextual factors that affect their healthcare utilization can also impact their care experience.

No description available.

In this thesis we provide statistical and model-based data mining methods for pattern detection with applications to biomedical and healthcare data sets. In particular, we examine applications in costly acute or chronic disease management. In Chapter II, we consider nuclear magnetic resonance experiments in which we seek to locate and demix smooth, yet highly localized components in a noisy two-dimensional signal. By using wavelet-based methods we are able to separate components from the noisy background, as well as from other neighboring components. In Chapter III, we pilot methods for identifying profiles of patient utilization of the healthcare system from large, highly-sensitive, patient-level data. We combine model-based data mining methods with clustering analysis in order to extract longitudinal utilization profiles. We transform these profiles into simple visual displays that can inform policy decisions and quantify the potential cost savings of interventions that improve adherence to recommended care guidelines. In Chapter IV, we propose new methods integrating survival analysis models and clustering analysis to profile patient-level utilization behaviors while controlling for variations in the population’s demographic and healthcare characteristics and explaining variations in utilization due to different state-based Medicaid programs, as well as access and urbanicity measures.

The inmate population is increasing, aging and generally in poorer health than the non-incarcerated population. Providing healthcare to inmates is constitutionally mandated, and expensive. Little published research exists to assist corrections health policy makers strategically plan for future inmate healthcare needs. This research provides an extensive description of the healthcare utilization patterns of a sample of 577 male and female inmates incarcerated at state-operated prisons in Kentucky during the period January 1, 2007, to December 31, 2007 and who have at least one of the chronic conditions of diabetes, hypertension or hyperlipidemia. The primary outcome measures were a count of the number of encounters documented in the inmate‟s electronic health record by 1) medical doctors and advanced registered nurse practitioners (medical care utilization) and 2) psychiatrists and psychologists (mental healthcare utilization), and 3) a dichotomous variable indicating if the inmate had received care from a health provider located outside the prison. The explanatory variables included demographic variables, health status variables, health risk factors, sentence-related variables, facility characteristics, inmate to corrections and medical staff ratios and quality of care indicators. Differences in healthcare utilization between various groups of inmates were tested using Pearson‟s chi-squared test for categorical variables and Student t-test for continuous variables. In the bivariate analysis increasing age, being female, having comorbidities, having a diagnosis of mental illness, being obese, not adhering to diet, exercise and medications, refusing or missing treatment, being at a facility with more corrections or medical staff and having better quality of care were all associated with greater healthcare utilization. Negative binomial regression was used to analyze the count outcomes, and multivariate logistic regression analysis was used to analyze the dichotomous outcome. Regression analysis revealed that the number of problems an inmate had recorded in their electronic health record and increasing age were the two greatest predictors of within facility and secondary healthcare utilization. Carrying out case management and disease management for inmates with comorbidities may have benefits for Departments of Corrections and inmates.

Healthcare utilizations are typically measured independently of each other; neglecting the interdependencies between services. An episode of care is suitable for measuring healthcare utilizations of patients with complex health conditions because it tracks all contacts throughout the healthcare system. The overall goal of this research was to construct an episode of care data system to study healthcare utilizations and costs of chronic obstructive pulmonary disease (COPD) exacerbations. To achieve this goal, four related studies were undertaken. The first study (Chapter 2) evaluated the agreement between emergency department (ED) data and hospital records for capturing transitions between the two care settings. Using the κ statistic as a measure of concordance, we found good agreement between the two data sources for intra-facility transfers; but only fair agreement for inter-facility transfers. The results show that linking multiple data sources would be important to identify all related healthcare utilization across care settings. The second study (Chapter 3) linked hospital data, ED data, physician billing claims, and outpatient drug records to construct an episode of care data system for COPD patients. Latent class analysis was used to identify COPD patient groups with distinct healthcare pathways. Pathways were associated with outcomes such as mortality and costs. A few individuals followed complex pathways and incurred high costs. Building on the previous study, the next one (Chapter 4) predicted whether high-cost patients in one episode also incurred high costs in subsequent episodes. Using logistic regression models, we found that patient information routinely collected in administrative health data could satisfactorily predict those who become persistent high users. The final study (Chapter 5) used a cross-validation approach to compare the performance of eight alternative linear regression models for predicting costs of episodes of COPD exacerbations. The results indicate that the robust regression model, a model not often considered for cost prediction, was among the best models for predicting episode-based costs. Overall, this research demonstrated how population-based administrative health databases could be linked to construct an episode of care data system for a chronic health condition. The resulting data system supported novel investigations of healthcare system-wide utilizations and costs. / May 2016