title: Optimal and early detection of acute kidney injury requires effective clinical decision support systems.
authors.affiliation: Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Handler
authors.affiliation: Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Sandra L
authors.initials: SL
authors.lastname: Kane-Gill
authors.affiliation: Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Kellum
mesh_terms: D058186:Acute Kidney Injury / Q000175:diagnosis*; D056902:Clinical Alarms; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D008297:Male
keywords: acute kidney injury; decision support systems; electronic medical record