Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15 ADQI Consensus Conference

Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15 ADQI Consensus Conference

The data contained within the electronic health record (EHR) is “big” from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI...

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Bibliographic Details
Main Authors: Scott M. Sutherland, Lakhmir S. Chawla, Sandra L. Kane-Gill, Raymond K. Hsu, Andrew A. Kramer, Stuart L. Goldstein, John A. Kellum, Claudio Ronco, Sean M. Bagshaw
Format: Article
Language:English
Published: SAGE Publishing 2016-02-01
Series:Canadian Journal of Kidney Health and Disease
Online Access:https://doi.org/10.1186/s40697-016-0099-4

Internet

https://doi.org/10.1186/s40697-016-0099-4

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