A 2019 awarded grant under the Robert Wood Johnson Foundation’s Health Data for Action program, managed by AcademyHealth.
The goal of this study is to help providers better understand different patterns of weight gain based on a trajectory of observations, which may in turn inform efforts to allocate limited resources to the patient sub-groups that may benefit most. The researchers will use data from athenahealth and computational phenotyping to examine how combinations of comorbidities and medications may trigger obesity. First, the researchers will develop a dynamic pattern-mining model to identify trends/patterns of weight gain that are most likely to be associated with diabetes. In the second part of the study, the researchers will identify combinations of medications and clinical conditions that may trigger obesity and Alzheimer’s disease. Deliverables will include a project work plan and final narrative report. The researchers will also produce paper(s) suitable for publication and present findings at national research meetings and to other stakeholder audiences as appropriate, including policymakers at the federal, state, and local levels and other key stakeholders, as part of the deliverables for this grant.
Dr. Jiang is a Christopher Sarofim family associate professor, CPRIT Scholar in Cancer Research, and center di... Read Bio
Dr. Yejin Kim is an assistant professor in the School of Biomedical Informatics (SBMI) at The University of Te... Read Bio
Grant: #76781
Grantee Institution: The University of Texas Health Science Center at Houston
Grant Period: 9/15/19 – 9/14/20