Research and Mentorship in Medical Decision Making in Diabetes

糖尿病医疗决策的研究和指导

• 批准号: 9324997
• 负责人: ELBERT S. HUANG
• 金额: $ 17.69万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9324997
• 关键词: Address; Affect; Aging; Architecture; Award; Behavior; Benefits and Risks; Biological Markers; Blood Pressure; Caring; Characteristics; Chicago; Choices and Control; Clinical; Comparative Study; Complex; Complications of Diabetes Mellitus; Computer Simulation; Consensus; Data; Data Collection; Databases; Decision Making; Development; Diabetes Mellitus; Dimensions; Disease; Elderly; Environment; Epidemiology; Event; Frequencies; Genetic; Geriatrics; Glucose; Goals; Health; Health Care Costs; Heterogeneity; Hypoglycemia; Individual; Intervention; Knowledge; Latino; Learning; Life; Longitudinal Studies; Measures; Medical; Medicine; Mentorship; Methods; Mid-Career Clinical Scientist Award (K24); Monitor; Nature; Non-Insulin-Dependent Diabetes Mellitus; Older Population; Online Systems; Outcome; Output; Patients; Pattern; Pharmaceutical Preparations; Pharmacoepidemiology; Physicians; Population Heterogeneity; Preparation; Protocols documentation; Psyche structure; Psychology; Quality of life; Recommendation; Recurrence; Regimen; Research; Research Personnel; Risk; Risk Factors; Role; Selection for Treatments; Self Care; Social Environment; Social Functioning; Social Network; Social Sciences; Structural Models; Subgroup; Time; Training; Universities; Update; Veterans; base; blood glucose regulation; care seeking; clinical practice; comparative effectiveness; design; diabetes control; follow-up; genetic profiling; glycemic control; health administration; impaired functional status; improved; individualized medicine; insight; mid-career faculty; models and simulation; mortality; next generation; novel; older patient; patient population; personalized care; personalized decision; preference; programs; public health relevance; social; support tools; tool

 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.