Utilizing electronic health records to predict acute kidney injury risk and outcomes: Workgroup statements from the 15th ADQI Consensus Conference

Canadian Journal of Kidney Health and Disease

Volumn 3, Issue 1, 2016, Pages

  Sutherland, Scott M ^a   Chawla, Lakhmir S ^b   Kane Gill, Sandra L ^c   Hsu, Raymond K ^d   Kramer, Andrew A ^e   Goldstein, Stuart L ^f   Kellum, John A ^c   Ronco, Claudio ^g   Bagshaw, Sean M ^h  

^a STANFORD UNIVERSITY   (United States)

^b GEORGE WASHINGTON UNIVERSITY MEDICAL CENTER   (United States)

^c UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e Prescient Healthcare Consulting   (United States)

^f CINCINNATI CHILDREN'S HOSPITAL MEDICAL CENTER   (United States)

^g SAN BORTOLO HOSPITAL   (Italy)

^h UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Acute kidney injury; Big data; Electronic health record; Electronic medical record; Prediction; Predictive analytics

Indexed keywords

CREATINE KINASE; CREATININE; DIPEPTIDYL CARBOXYPEPTIDASE INHIBITOR; DIURETIC AGENT; FUROSEMIDE; HYPERTENSIVE FACTOR; INOTROPIC AGENT; METHAMPHETAMINE; NONSTEROID ANTIINFLAMMATORY AGENT;

ACUTE KIDNEY FAILURE; CLINICAL ASSESSMENT; DISEASE CLASSIFICATION; ELECTRONIC HEALTH RECORD; GLOMERULUS FILTRATION RATE; HEMODIALYSIS; HUMAN; PREDICTION; PRIORITY JOURNAL; RENAL REPLACEMENT THERAPY; REVIEW; RISK ASSESSMENT;

EID: 84997703642     PISSN: None     EISSN: 20543581     Source Type: Journal    
DOI: 10.1186/s40697-016-0099-4     Document Type: Review

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