Challenges, Strengths and Opportunities Related to Implementing Comprehensive Evidence-Based Guidelines on Breast Cancer Survivorship Care by Primary Care Physicians and Nurse Practitioners in Southeastern Ontario

Background Many breast cancer survivors continue to have a broad range of physical and psychosocial problems after breast cancer treatment. As cancer centres move forward with earlier discharge of stable breast cancer survivors to primary care follow-up it is important that comprehensive evidence-based breast cancer survivorship care is implemented to effectively address these needs. Research suggests primary care providers are willing to provide breast cancer survivorship care but many lack the knowledge and confidence to provide evidence-based care. Purpose The overall purpose of this thesis was to determine the challenges, strengths and opportunities related to implementing comprehensive evidence-based breast cancer survivorship guidelines by primary care physicians and nurse practitioners in southeastern Ontario. Methods This mixed-methods research was conducted in three phases: (1) synthesis and appraisal of clinical practice guidelines relevant to provision of breast cancer survivorship care within the primary care practice setting; (2) a brief quantitative survey of primary care providers to determine actual practices related to provision of evidence-based breast cancer survivorship care; and (3) individual interviews with primary care providers about the challenges, strengths and opportunities related to provision of comprehensive evidence-based breast cancer survivorship care. Results and Conclusions In the first phase, a comprehensive clinical practice framework was created to guide provision of breast cancer survivorship care and consisted of a one-page checklist outlining breast cancer survivorship issues relevant to primary care, a three-page summary of key recommendations, and a one-page list of guideline sources. The second phase identified several knowledge and practice gaps, and it was determined that guideline implementation rates were higher for recommendations related to prevention and surveillance aspects of survivorship care and lowest related to screening for and management of long-term effects. The third phase identified three major challenges to providing breast cancer survivorship care: inconsistent educational preparation, provider anxieties, and primary care burden; and three major strengths or opportunities to facilitate implementation of survivorship care guidelines: tools and technology, empowering survivors, and optimizing nursing roles. A better understanding of these challenges, strengths and opportunities will inform development of targeted knowledge translation interventions to provide support and education to primary care providers.

An exploration of students’ perceptions and attitudes towards creativity in engineering education

Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2016-09-29 17:45:16.051

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.