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.
Medical decisions in diabetes are becoming more complex as we learn to individualize targets and treatments based on clinical characteristics, genetic profiles, treatment preferences, and social circumstances. This award will allow Dr. Elbert Huang to devote 50% of his time to training the next generation of researchers in medical decision making in diabetes and expand his research in epidemiology, pharmacoepidemiology, and decision support interventions. Improving the quality of medical decision making in diabetes has the great potential to improve the quality of life of patients living with the disease.
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