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Shared decision-making about breast reconstruction : a decision analysis approach

An ongoing objective in healthcare is the development of tools to improve patient decision-making and surgical outcomes for patients with breast cancer that have undergone or plan to undergo breast reconstruction. In keeping with the bioethical concept of autonomy, these decision models are patient-oriented and expansive, covering a range of different patient decision-makers. In pursuit of these goals, this dissertation contributes to the development of a prototype shared decision support system that will guide patients with breast cancer and their physicians in making decisions about breast reconstruction.
This dissertation applies principles in decision analysis to breast reconstruction decision-making. In this dissertation, we examine three important areas of decision-making: (1) the options available to decision-makers, (2) the validity of probabilistic information assessed from reconstructive surgeons, and (3) the feasibility of applying multiattribute utility theory. In addition, it discusses the influences of breast aesthetics and proposes a measure for quantifying such influences. The dissertation concludes with a fictional case study that demonstrates the integration of the findings and application of decision analysis in patient-oriented shared breast reconstruction decision-making.
Through the implementation of decision analysis principles, cognitive biases and emotion may be attenuated, clearing the decision-maker’s judgment, and ostensibly leading to good decisions. While good decisions cannot guarantee good outcomes at the individual level, they can be expected to improve outcomes for patients with breast cancer as a whole. And regardless of the outcome, good decisions yield clarity of action and grant the decision-maker a measure of peace in an otherwise uncertain world. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/22976
Date29 January 2014
CreatorsSun, Clement Sung-Jay
Source SetsUniversity of Texas
Languageen_US
Detected LanguageEnglish
Formatapplication/pdf

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