A Patient-Specific Decision Support Tool for Bariatric Surgery

描述(由申请人提供)： 背景资料。肥胖及与肥胖相关的疾病已被证明会大大降低生活质量和预期寿命。目前，减肥手术是唯一被证明可以持续减轻病态肥胖患者体重的治疗方法。然而，由于手术涉及的风险和不确定的结果，决定接受手术是一个困难的决定。目标。作为一名对决策分析感兴趣的结果研究人员，这项应用的具体目标是：a)扩大我在构建决策分析模型、决策科学和进行以患者为中心的研究方面的技能，以及b)使用这些技能来开发和测试交互式决策支持工具，该工具提供关于单个患者的手术风险和减肥手术的预期益处的定制信息。我的长期职业目标是为病态肥胖症患者开发和测试各种针对患者的决策支持工具。训练。为了我的职业发展，我计划选修决策科学方面的额外课程，重点是为模拟设计决策分析模型。我的导师团队由决策分析、肥胖和研究方法领域的领先专家组成：Mark H.Eockman，医学博士，医学硕士，Joel Tsevat，医学博士，公共卫生硕士，David D‘Alessio，医学博士，David Fischer，医学博士，David Arterburn，医学博士，公共卫生硕士，Richard Hornung，DrPH，Thomas Inge，医学博士，博士和Meg Zeller博士。研究设计。对于这项建议，我们将首先开发一个基于人群的决策分析模型，该模型检查两种策略：减肥手术和病态肥胖的自然病史。使用这个模型，我们将确定哪些患者的减肥手术决定是“千呼万唤”的。然后，该模型将成为开发特定于患者的模型的基础，该模型将作为我们决策支持工具的基础。使用随机对照试验，我们将评估患者在使用决策支持工具时对减肥手术的风险和好处、决策冲突、对决策过程的满意度和决策自我效能的理解，并与获得减肥手术一般信息的对照组进行比较。 关联性。在这个项目完成时，我们将开发和测试一个基于网络的交互式决策支持工具，供考虑减肥手术的病态肥胖患者使用。这将有助于患者在权衡病态肥胖的治疗选择时做出更明智的决定。

DESCRIPTION (provided by applicant): Background. Obesity and obesity-associated conditions have been shown to greatly decrease both quality of life and life expectancy. Currently, bariatric surgery is the only proven treatment for sustained weight loss in the morbidly obese patient. However the decision to undergo surgery is a difficult one because of the risks involved in surgery and the uncertain outcome. Objectives. As an outcomes researcher with an interest in decision analysis, the specific objectives of this application are to: a) broaden my skills in the construction of decision analytic models, the decision sciences, and the conduct of patient-oriented research and b) use these skills to develop and test an interactive decision support tool that provides tailored information about the individual patient's surgical risk and the expected benefit of bariatric surgery. My long- term career goal is to develop and test a variety of patient-specific decision support tools for patients with morbid obesity. Training. For my career development, I plan to take additional coursework in the decision sciences, focusing on the design of decision analytic models for simulations. My mentorship team is comprised of leading experts in the fields of decision analysis, obesity and research methodology: Mark H. Eckman, MD, MS, Joel Tsevat, MD, MPH, David D'Alessio, MD, David Fischer, MD, David Arterburn, MD, MPH, Richard Hornung, DrPH, Thomas Inge, MD, PhD, and Meg Zeller, PhD. Research Design. For this proposal, we will first develop a population based decision analytic model that examines two strategies: bariatric surgery versus the natural history of morbid obesity. Using this model we will identify those patients for whom the decision to have bariatric surgery is a "close call". This model will then be the basis for the development of a patient-specific model that will serve as the foundation for our decision support tool. Using a randomized controlled trial, we will assess patients' understanding of the risks and benefits of bariatric surgery, decisional conflict, satisfaction with the decision making process and decision self efficacy when using the decision support tool compared to a control group with access to generic information about bariatric surgery. Relevance. At the completion of this project, we will have developed and tested an interactive web-based decision support tool to be used by morbidly obese patients considering bariatric surgery. This will assist patients in making a more informed decision when weighing the treatment options for morbid obesity.