Research and Mentorship in Medical Decision Making in Diabetes

 描述（由申请人提供）：随着可用降糖药数量的增加，以及我们了解到如何根据患者的临床特征、遗传特征、治疗偏好和社会环境对风险因素目标和治疗进行个性化，糖尿病护理中的医疗决策变得越来越复杂。为了加强糖尿病医疗决策的培训和研究，芝加哥大学医学副教授埃尔伯特黄博士提交了这份K24提案。芝加哥大学是一个理想的环境，因为它的完善的糖尿病研究计划和社会科学的显着优势。该计划的总体目标是：1）扩大糖尿病流行病学和药物流行病学的研究，以考虑风险因素控制和治疗随时间和临床亚组的影响; 2）制定决策支持干预措施，使医生和患者能够利用从糖尿病，老年病，遗传学和心理学中获得的知识，以更好地定制治疗。该计划的学员将有机会获得全国代表性的数据库，糖尿病并发症（1型，2型，单基因糖尿病，老年病）的计算机模拟模型，和基于网络的决策支持工具。拟议的研究检查了糖尿病医疗决策的三个新维度，即：1）随着时间的推移，医疗决策的重复性; 2）患者社交网络对护理和结果的作用; 3）随着时间的推移，个性化糖尿病护理的决策支持工具的开发。当前的第一个项目是利用退伍军人健康管理局的纵向数据（2003-2011年）对2型糖尿病患者（约900，000）进行降糖治疗动态模式的比较有效性研究。该研究的目的是描述和分类药物选择和血糖控制的纵向模式，并使用结构建模方法评估与这些治疗模式相关的结局风险。目前的第二个项目是国家社会生活，健康和老龄化项目（NSHAP），这是一项具有全国代表性的老年人纵向研究，现在进入第三波，旨在研究社会因素（例如，亲密关系、社会网络特征）影响与糖尿病相关的护理和结果。在新的研究中，黄博士将开发一种新的基于网络的老年糖尿病决策支持工具，旨在鼓励个性化的血糖和血压目标选择。其目的是：1）更新糖尿病模拟模型，以纳入糖尿病相关证据的变化; 2）修改工具的输出，以反映血糖和血压目标的新共识小组建议; 3）创建一个针对西班牙语拉丁美洲人的支持工具版本。这个K24奖项将使黄博士能够在糖尿病的医疗决策方面创建一个导师计划，并在新的方向上扩展他的研究组合，这将指导不同人群的个性化护理。 患有糖尿病

 DESCRIPTION (provided by applicant): Medical decisions in diabetes care are becoming more complex as the number of available glucose lowering agents has expanded and as we learn how risk factor targets and treatments may need to be individualized based on a patient's clinical characteristics, genetic profiles, treatment preferences, and social circumstances. To strengthen training and research in medical decision making in diabetes, Dr. Elbert Huang, Associate Professor of Medicine at the University of Chicago, is submitting this K24 proposal. The University of Chicago is an ideal environment for this program because of its well-established diabetes research programs and significant strengths in the social sciences. The overall goals of the program are: 1) to expand research in the epidemiology and pharmaco-epidemiology of diabetes to consider the effects of risk factor control and treatments over time and across clinical subgroups; and 2) to develop decision support interventions that can allow physicians and patients to harness knowledge gained from diabetes, geriatrics, genetics, and psychology to better tailor treatments. Trainees of the program will have access to nationally representative data repositories, computer simulation models of diabetes complications (type 1, type 2, monogenic diabetes, geriatrics), and web-based decision support tools. The proposed studies examine three new dimensions of medical decision making in diabetes, namely: 1) the recurrent nature of medical decisions over time; 2) the role of social networks of patients on care and outcomes; 3) and the development of decision support tools for personalizing diabetes care over time. The first current project is a study of the comparative effectiveness of dynamic patterns of glucose lowering therapies utilizing longitudinal data (2003-2011) from the Veterans Health Administration for patients with type 2 diabetes (~900,000). The aims of the study are to describe and classify longitudinal patterns of medication choices and glucose control and to evaluate the risks of outcomes associated with these treatment patterns, using structural modeling methods. The second current project is the National Social Life, Health and Aging Project (NSHAP), a nationally-representative longitudinal study of older adults, now entering Wave 3, designed to examine mechanisms by which social factors (e.g., intimate relationships, social network characteristics) affect care and outcomes related to diabetes. In new research, Dr. Huang will develop a new web-based geriatric diabetes decision support tool that is designed to encourage individualization of glucose and blood pressure target selection. The aims are to: 1) update a diabetes simulation model in order to incorporate changes in evidence regarding diabetes; 2) revise the output of the tool to reflect new consensus panel recommendations for glucose and blood pressure targets; and 3) create a version of the support tool tailored to Spanish-speaking Latinos. This K24 award will allow Dr. Huang to create a mentorship program in medical decision making in diabetes and expand his research portfolio in new directions that will guide individualization of care for diverse populations of patients living with diabetes.