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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>

Pharmaceuticals have become, arguably, one of the fastest changing forms of health care. Advancements in pharmaceuticals are constantly bringing better treatments to illnesses previously untreatable. These advancements, however, come with a hefty price tag: In many countries they also represent the fastest growing source of health care expenditures. Innovative drugs often come to the market with high prices, and the prices of existing drugs can creep up if they are not reined in. These high prices can threaten patient access to the pharmaceuticals they need. Fortunately, there is a lot public policy can do, if it is designed to interact well with clinical, economic, and commercial factors, to safeguard this access. This thesis contains three studies on the effects of public policy on the price-accessibility of pharmaceuticals. Its objectives are as follows: 1) To develop the definitions of a fair pricing of pharmaceuticals in terms of price-accessibility, 2) to present two case studies where public policy changes pharmaceutical prices and affects their utilization, and 3) discuss the significance of these case study policies on access to these drugs. This thesis contributes to the existing body of literature by developing new theoretical models about what constitutes fair pricing of pharmaceuticals and about the relationships between the main parties responsible for making pharmaceuticals accessible to the people who need them. A new evaluation of the policy that delisted high-strength opioids from public formularies in Ontario is also presented with new regression models that allow the analysis of the effects of the policy across sociodemographic categories. Finally, this thesis also contains the first empirical analysis of OHIP plus, the policy that extended the public drug benefits to all individuals under 25 years of age; in this case, with the focus on oral chemotherapy drugs for cancer. / Dissertation / Doctor of Philosophy (PhD) / The rising prices of some pharmaceuticals have made them inaccessible to patients and their families, who must make big financial sacrifices to afford the drugs they need. This thesis contains three studies on the impact of ethical pricing and public policy on the accessibility of pharmaceuticals. Its objectives are to develop definitions of fair pricing in terms of access, to analyze two public policies that sought to change the utilization of pharmaceuticals by changing the price people pay for them, and to elaborate on what these policies mean for the accessibility of these drugs. This thesis’ contributions to the literature include novel theoretical models about pharmaceutical pricing and new evaluations of the effects, by sociodemographic category, of a policy designed to combat the ongoing opioids epidemic in Ontario, Canada, and the effects of OHIP plus on the emerging use of expensive oral-delivery cancer drugs in the same province.

Associations between the experience of traumatic events and illness behaviors such as health complaints and healthcare use are reported in recent studies. Posttraumatic Stress Disorder (PTSD) symptoms and diagnosis have been found to mediate this trauma-illness relationship. Differences in health behaviors have additionally been noted in the literature, with trauma victims engaging in more negative health behaviors, which may subsequently affect illness status. Further, illness behaviors such as somatic complaints and healthcare utilization are influenced by modeling and reinforcement of such behaviors. The current study sought to evaluate the contributions of negative health behaviors, illness-related learning history, and PTSD symptoms on trauma victims' health complaints, functional health status, and utilization of healthcare services. The final sample included 298 undergraduate students at a large southeastern university. Participants provided information about their trauma histories, health behaviors, illness-related learning history and current illness behaviors on group-administered self-report questionnaires. Consent to obtain utilization information from the university health center was also obtained. Hierarchical regression analyses were used to assess the additive contributions of the predictor variables. The results indicated that health complaints, functional health status, and utilization behavior are each influenced by trauma history, with more illness behavior associated with greater trauma severity. In addition, health behaviors, illness-related learning history and PTSD symptoms all contribute to the prediction of health complaints and functional health status. Utilization behavior, however, was predicted only by trauma history and learning history. Further, the different types of learning history (modeling, reinforcement, priming) appear to affect different illness behaviors. Implications of the study are discussed. / Ph. D.

Ovarian cancer is the fifth leading cause of all cancer deaths in women and the most lethal gynecologic cancer in the United States. During metastasis, cancer cells exfoliate from the primary tumor and aggregate to form spheroids, enhancing their survival within the peritoneal cavity during dissemination to a secondary outgrowth site. The inability of removal of these aggregates by traditional surgical interventions may contribute to the high recurrence and mortality rate of ovarian cancer diagnosed at late stages. Obesity, particularly abdominal obesity, has been shown to increase ovarian cancer risk and decrease survival. The recruitment of stromal vascular fraction (SVF) present in adipose tissue represents a growth and proliferation advantage to ovarian tumors, and endogenous sphingolipids like sphingosine-1-phosphate are increased in ovarian cancer patients. These conditions, combined with the physiological conditions within malignant ascites (hypoxia and low glucose), represent a physiological environment that can impact the metabolic responses of ovarian cancer spheroids. Here, we investigated the metabolic adaptations of serous ovarian cancer cells across the metastatic cycle and in conditions that mimic those of the peritoneal cavity and malignant ascites. We first investigated the different in metabolic responses between adherent monolayers and 3D spheroids. We confirmed that spheroids have a reduced metabolic rate and drug response that is affected by the incorporation of obese SVF into aggregates. To investigate these changes in the next stages of the metastatic cycle, we used time trials to observe how adherence of spheroids to a secondary site changes metabolic response and substrate utilization in physiological conditions. Adhesion of spheroids showed changes in energy metabolism and substrate utilization, switching from mainly glutamine oxidation to glucose oxidation that could support successful outgrowth. Spheroids also were resilient to culture conditions, even non-permissive conditions such as those found in the peritoneal cavity. Finally, we utilized human malignant ascites from ovarian cancer patients as a further investigation into conditions that imitate in vivo characteristics that could affect spheroid metabolism. Exposure to malignant ascites reduced spheroid viability as well as basal respiration and ATP synthesis. However, spare respiratory capacity was increased, and human spheroids changed their substrate utilization in response to ascites. Taken together, these studies provide an identification of metabolic switches across different stages of ovarian cancer metastasis that contribute to their survival, which represents an emerging target for prevention and treatment for individuals with ovarian cancer. / Doctor of Philosophy / Ovarian cancer is the deadliest reproductive cancer in women, and most women who are diagnosed will die from the disease because of its high recurrence rate and because it is typically detected at late stages. When ovarian cancer metastasizes, cells or cell clusters from the original tumor aggregate together to form balls of cells called spheroids, which move through the abdominal cavity to other sites to grow additional tumors. These spheroids are thought to contribute to recurrence of this cancer, since they cannot be removed by surgery. As these spheroids move through the abdominal cavity, they are exposed to an environment that has a low amount of oxygen and glucose. These spheroids may also be exposed to bioactive lipids and cells from the adipose tissue called stromal vascular fraction, both of which are related to obesity and may help cancer spheroids survive. The survival of these spheroids is in part related to how their metabolism functions, which may help them make energy and the building blocks needed to continue growing and form successful secondary tumors. Identifying how these spheroids change their metabolism at different points during the disease may help identify points that can be targeted to prevent changes in metabolism that could support their growth. This dissertation identified metabolic changes that occur in spheroids, in conditions that are similar to those spheroids would be exposed to in an abdominal cavity. First, we compared single layers of cells to spheroids and found that spheroids had a lower metabolic rate and lower drug response, which may help them survive in the abdominal cavity. Next, we allowed the spheroids to lay down and grow out, like they would when they found a new location during metastasis, to see how their metabolism changed and what substances they used to make energy in conditions that mimicked the abdominal cavity. As spheroids adhered, they changed their energy metabolism and switched the substances they used to make energy, all while continuing to survive and grow out even in conditions that were not supportive. These switches could help them grow out and successfully metastasize. Lastly, we used ascites fluid from human ovarian cancer patients and treated spheroids with this to see how their metabolism changed in response. While some aspects of metabolism and survival was reduced, their ability to increase their metabolism when stressed increased and human spheroids used nutrients to make energy differently. Overall, we show that across the stages of metastasis, ovarian cancer spheroids can change their metabolism in response to their environment. Identifying these metabolic switches helps us understand how successful metastasis happens, and can inform future targets to slow or prevent metastasis, prolonging the life of women who have been diagnosed with ovarian cancer.

Three studies were conducted to evaluate a method for estimating grass and legume fractions in extrusa samples from esophageally-fistulated animals, based on different concentrations of neutral detergent fiber (NDF), Ca and lignin in grasses and legumes. In experiment 1, NDF, Ca and lignin concentrations were measured in mixtures of six combinations of red clover-orchardgrass and alfalfa-tall fescue (100:0; 80:20; 60:40; 40:60; 20:80; 0:100). The R² values were .90, .80 and .22 for Ca, NDF and lignin, respectively. In experiment 2, fresh tall fescue and red clover were collected during 8 d, mixed in the same proportions as in experiment 1, and each fraction was fed to esophageally-fistulated steers. Extrusa samples were collected without loss of saliva. Regression equations developed were y= 1.08 - .008x (R²= .91) for Ca and y= 50.9 + .22x (R²= .74) for NDF, where x represents % grass. In experiment 3, two esophageally-fistulated steers were allowed to graze in 20 4 X 4 m² plots of red clover and tall fescue after fasting overnight. The grass/legume proportions of the extrusas and the grab samples were extrapolated from slopes. The botanical composition of grab samples differed (P<.001) from that of extrusas for both components and for both animals. Extrapolation from NDF values tended to overestimate the proportion of grass in extrusa samples and underestimate it in grab samples. Calcium was not affected by salivation and mastication and was more reliable than NDF. Lignin was not an accurate predictor. / M.S.

Experiments were conducted to study the chemical changes and microanatomical characteristics associated with maturity, rate and extent of DM digestion, behavior and extent of tissue digestion and mode of microbial attack during simulated ruminal digestion. Barley and millet plants were collected at four different stages of development: vegetative, boot, heading and mature. Berseem was harvested at three different stages of development: vegetative, bud and full bloom. For the first three stages of grasses and legumes, the plants were separated into three botanical fractions: leaf blades (leaflets), leaf sheaths (petioles) and stems. Grasses were harvested at mature stage and barley seeds were separated by thresher and millet seed by hand cutting the head. Straws were chopped in a hammer mill through a 2.5 cm screen and treated: 1) no added water (control), 40% added water, 2) alone or with 3) urea, 4) NH₄OH and 5) H₂O₂ at pH 11.5. Grasses showed higher (P<.05) cell wall constituents, xylose, p-coumaric and ferulic acid and lower (P<.05) IVDMD values for stems and leaf sheaths than leaf blades. Legume showed higher (P<.05) values for cell wall constituents and xylose for stems, compared to petioles and leaflets. At advanced maturity, scanning electron microscopy (SEM) showed increased lignification and decreased tissue digestion for leaf sheaths and stems, compared to leaf blades. Lignification was higher in millet leaf sheaths than barley leaf sheaths. Within berseem plant parts, petioles showed better digestion than leaflets and stems. The contents of ADF, cellulose and lignin were increased (P<.05) and hemicellulose was decreased (P<.05) in alkaline H₂O₂-treated straws, compared to untreated, NH₃- and urea-treated straw. Total phenolic acids were decreased (P<.05) in treated, compared to untreated straw. In vitro DM digestibility was increased (P<.05) for all chemical treatments, with larger (P<.05) increase for NH₃ treatment than alkaline H₂O₂ treatment. / Ph. D.