Tiffany C.E. Veinot

Reducing Kidney Disease through Acute Kidney Injury Risk Prediction and Prevention

Research Project Description
Michael Heung, Rajiv Saran, David W. Hutton, Zhi He, Vahakn Bedig Shahinian, Karandeep Singh, Tiffany C.E. Veinot

Acute kidney injury (AKI) is a sudden decline in kidney function, often occurring in the setting of hospitalization. It occurs in up to 20% of hospitalized adults ? millions of Americans annually ? and is recognized as one of the most significant contributors to chronic kidney disease (CKD) development and progression (Chawla et al, N Engl J Med 2014;371:58). Thus prevention of AKI has the potential to significantly reduce the overall burden of kidney disease. Furthermore, AKI is associated with hospital mortality rates approaching 25%; mortality exceeds 50% when dialysis is required.

Our proposal aims to a) develop a high fidelity AKI risk prediction tool for hospitalized Veterans that can be administered shortly after admission; b) develop a decision support tool for management of patients identified as being at risk for AKI; and c) implement these tools in a pilot cohort of VA facilities. The ultimate goal of our study is to reduce the burden of kidney disease by decreasing one of its most important precipitants: AKI. As we will leverage VA health data and data analytic approaches for this proposal, it will also secondarily target Topic 0002: Data Science Advances to Improve Health Care of People with Kidney Disease.

Funding:
Veterans Affairs, Department of
(36C10B18C2766)

Funding Period: 9/30/2018 to 9/29/2019

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