Open AccessAcute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support
Author(s) -
F. Perry Wilson,
Jason Greenberg
Publication year - 2018
Publication title -
the nephron journals/nephron journals
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.951
H-Index - 72
eISSN - 2235-3186
pISSN - 1660-8151
DOI - 10.1159/000492064
Subject(s) - medicine , acute kidney injury , kidney disease , intensive care medicine , dialysis , sequela , psychological intervention , creatinine , nephrology , emergency medicine , medical emergency , surgery , psychiatry
Broad adoption of electronic health record (EHR) systems has facilitated acute kidney injury (AKI) research in 2 ways. First, the detection of AKI based on changes in serum creatinine has largely replaced the sensitive but nonspecific administrative coding of AKI that predominated in earlier studies. Second, the ability to implement real-time AKI interventions such as alerts and best-practice advisories has emerged as a promising tool to fight against the harmful sequela of AKI, which include short-term adverse outcomes as well as progression to chronic kidney disease, dialysis, and death. In this review, we discuss the current state-of-the-art in EHR-based tools to predict imminent AKI, alert to the presence of AKI, and modify provider behaviors in the presence of AKI.