Objective: To complete a cost-minimization analysis (CMA) of the cost of sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) in the management of early-stage breast cancer (ESBC) in a hypothetical Ontario hospital setting. Methods: Decision-analysis modeling, with a decision-tree and Markov states, was used to estimate hospital costs for the two treatment options. The model was populated with data from the literature and costs from the Ontario Case Costing Initiative, a publicly accessible, government-sponsored, costing database. Model variability and parameter uncertainty were quantified by probabilistic sensitivity analysis (PSA). Results: The SLNB treatment algorithm was cost-minimizing compared to the ALND-only treatment option. The costs of treating postoperative complications did not contribute to the incremental average cost. Conclusion: A treatment algorithm that involves SLNB as the initial axillary-staging procedure in the setting of ESBC offers a cost-savings over the ALND-only option. This result is generalizable to all Ontario hospitals.

Objective: To complete a cost-minimization analysis (CMA) of the cost of sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) in the management of early-stage breast cancer (ESBC) in a hypothetical Ontario hospital setting. Methods: Decision-analysis modeling, with a decision-tree and Markov states, was used to estimate hospital costs for the two treatment options. The model was populated with data from the literature and costs from the Ontario Case Costing Initiative, a publicly accessible, government-sponsored, costing database. Model variability and parameter uncertainty were quantified by probabilistic sensitivity analysis (PSA). Results: The SLNB treatment algorithm was cost-minimizing compared to the ALND-only treatment option. The costs of treating postoperative complications did not contribute to the incremental average cost. Conclusion: A treatment algorithm that involves SLNB as the initial axillary-staging procedure in the setting of ESBC offers a cost-savings over the ALND-only option. This result is generalizable to all Ontario hospitals.

The present work addresses the thermodynamic optimization of small binary-cycle geothermal power plants. The optimization process and entropy generation minimization analysis were performed to minimize the overall exergy loss of the power plant, and the irreversibilities associated with heat transfer and fluid friction caused by the system components. The effect of the geothermal resource temperature to impact on the cycle power output was studied, and it was found that the maximum cycle power output increases exponentially with the geothermal resource temperature. In addition, an optimal turbine inlet temperature was determined, and observed to increase almost linearly with the increase in the geothermal heat source. Furthermore, a coaxial geothermal heat exchanger was modeled and sized for minimum pumping power and maximum extracted heat energy. The geofluid circulation flow rate was also optimized, subject to a nearly linear increase in geothermal gradient. In both limits of the fully turbulent and laminar fully-developed flows, a nearly identical diameter ratio of the coaxial pipes was determined irrespective of the flow regime, whereas the optimal geofluid mass flow rate increased exponentially with the Reynolds number. SeveORCs were observed to yield maximum cycle power output. The addition of an IHE and/or an Oral organic Rankine Cycles were also considered as part of the study. The basic types of the FOH improved significantly the effectiveness of the conversion of the available geothermal energy into useful work, and increased the thermal efficiency of the geothermal power plant. Therefore, the regenerative ORCs were preferred for high-grade geothermal heat. In addition, a performance analysis of several organic fluids was conducted under saturation temperature and subcritical pressure operating conditions of the turbine. Organic fluids with higher boiling point temperature, such as n-pentane, were recommended for the basic type of ORCs, whereas those with lower vapour specific heat capacity, such as butane, were more suitable for the regenerative ORCs. / Dissertation (MEng)--University of Pretoria, 2013. / Mechanical and Aeronautical Engineering / unrestricted

Au Canada, le cancer du poumon est la cause principale de décès relié au cancer. À l’imagerie médicale, le cancer du poumon peut prendre la forme d’un nodule pulmonaire. La prise en charge menant au diagnostic définitif d’un nodule pulmonaire peut s’avérer complexe. La recherche en oncoprotéomique a permis le développement de nouveaux tests diagnostiques non-invasifs en cancer du poumon. Ceux-ci ont pour objectif d’évaluer le risque de malignité d’un nodule pour guider la prise en charge menant au diagnostic. Toutefois, l’impact économique de tels tests demeure inconnu. L’objectif de ce projet était de mesurer, en milieu de pratique réelle, l’utilisation des ressources en soins de santé pour l’investigation de nodules pulmonaires puis, de développer un modèle générique permettant d’évaluer l’impact économique au Québec des nouveaux tests protéomiques pour l’investigation de ces nodules. Tout d’abord, une revue de dossiers patients a été effectuée dans trois centres hospitaliers du Québec afin de mesurer les ressources en soins de santé et les coûts associés à l’investigation de nodules pulmonaires entre 0,8 et 3,0 cm. Par la suite, une analyse de minimisation de coûts a été effectuée à partir d’un modèle générique développé dans le cadre de ce projet. Ce modèle visait à comparer l’approche courante d’investigation à celle intégrant un test protéomique fictif afin de déterminer l’approche la moins dispendieuse. La revue de dossiers patients a permis de déterminer qu’au Québec, le coût moyen d’investigation d’un nodule pulmonaire est de 7 354$. Selon les résultats de l’analyse, si le coût du test protéomique est fixé en-deçà de 3 228,70$, l’approche intégrant celui-ci serait moins dispendieuse que l’approche courante. La présente analyse suggère que l’utilisation d’un test diagnostique protéomique non-invasif en début d’investigation pour un nodule de 0,8 à 3,0 cm, permettrait d’engendrer des économies pour le système de santé au Québec. / In Canada, lung cancer is the leading cause of death among cancer patients. Imaging technologies, such as computed tomography, allows the detection of potential lung cancers in the form of pulmonary nodules. The clinical pathway leading to the definitive diagnostic of a pulmonary nodule can be complex. Research in oncoproteomics has led to the development of novel noninvasive diagnostic tests in lung cancer. These tests aim to evaluate the risk of malignancy of a nodule in order to guide the clinical pathway leading to a diagnostic. However, the economic impact of such tests remains unknown. The objective of this project was to measure, in a real-life setting, health care resource utilization for the investigation of pulmonary nodules and then, develop a generic model to assess the economic impact in the province of Quebec of new proteomic tests for the investigation of these nodules. Firstly, a medical chart review was performed in three hospitals in Quebec to measure health care resource utilization for the investigation of pulmonary nodules of 0,8 to 3,0 cm. Then, a cost minimization analysis was performed by using a generic model developed for this project. This model compared the usual care to the approach integrating a fictive proteomic test in order to identify the less expensive approach. As per the medical chart review, the average cost for the investigation of a pulmonary nodule was $7,354. According to the results of the analysis, if the cost of the test is below $3,228.70, the approach integrating a proteomic test would be less expensive then the current approach. This study tends to demonstrate that the use of a noninvasive proteomic diagnostic test at the beginning of the investigation of a pulmonary nodule from 0,8 to 3,0 cm could generate savings for the health care system in Quebec.