Prediction Analytics to Guide Prevention of Kidney Disease Among U.S. Veterans
The goal the study is to develop a data-driven approach to reduce the incidence and progression of kidney disease among Veterans in the U.S. The study will carry out predictive analytics (using traditional statistical and machine learning tools) and geospatial analyses, to identify high risk individuals as well as those with identifiable kidney disease, and the geographic areas they live in, to better understand risk and progression factors for kidney disease. This work will set the stage for enabling targeted population health interventions to prevent kidney disease as well as slow progression of kidney disease among U.S. veterans.
Principal Investigator: Rajiv Saran at U-M Medical School
Co-investigator: Tiffany Veinot
The amount of the award is $750,000 for the project period. The contract is funded by the Department of Veterans Affairs Center for Innovation (VACI).