Electronic Health Record-Enabled Big-Data Approaches to Nephrotoxin-Associated Acute Kidney Injury Risk Prediction

2018 ◽  
Vol 38 (8) ◽  
pp. 804-812 ◽  
Author(s):  
Scott M. Sutherland
Keyword(s):  
Acute Kidney Injury ◽  
Big Data ◽  
Electronic Health Record ◽  
Risk Prediction ◽  
Injury Risk ◽  
Kidney Injury ◽  
Health Record ◽  
Electronic Health

scholarly journals eResearch in acute kidney injury: a primer for electronic health record research

2018 ◽  
Vol 34 (3) ◽  
pp. 401-407 ◽  
Author(s):  
Emily L Joyce ◽  
Dilhari R DeAlmeida ◽  
Dana Y Fuhrman ◽  
Priyanka Priyanka ◽  
John A Kellum
Keyword(s):  
Acute Kidney Injury ◽  
Electronic Health Record ◽  
Kidney Injury ◽  
Health Record ◽  
Electronic Health

scholarly journals Electronic health record-based predictive models for acute kidney injury screening in pediatric inpatients

2017 ◽  
Vol 82 (3) ◽  
pp. 465-473 ◽  
Author(s):  
Li Wang ◽  
Tracy L McGregor ◽  
Deborah P Jones ◽  
Brian C Bridges ◽  
Geoffrey M Fleming ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Electronic Health Record ◽  
Predictive Models ◽  
Kidney Injury ◽  
Health Record ◽  
Electronic Health ◽  
Injury Screening

Electronic Health Record Identification of Nephrotoxin Exposure and Associated Acute Kidney Injury

PEDIATRICS ◽  
2013 ◽  
Vol 132 (3) ◽  
pp. e756-e767 ◽  
Author(s):  
S. L. Goldstein ◽  
E. Kirkendall ◽  
H. Nguyen ◽  
J. K. Schaffzin ◽  
J. Bucuvalas ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Electronic Health Record ◽  
Kidney Injury ◽  
Health Record ◽  
Electronic Health

scholarly journals Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial

BMJ ◽  
2021 ◽  
pp. m4786
Author(s):  
F Perry Wilson ◽  
Melissa Martin ◽  
Yu Yamamoto ◽  
Caitlin Partridge ◽  
Erica Moreira ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Relative Risk ◽  
Confidence Interval ◽  
Electronic Health Record ◽  
Usual Care ◽  
Primary Outcome ◽  
Kidney Injury ◽  
Health Record ◽  
Care Practices ◽  
Electronic Health

Abstract Objective To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury. Design Double blinded, multicenter, parallel, randomized controlled trial. Setting Six hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers. Participants 6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria. Interventions An electronic health record based “pop-up” alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient’s medical record. Main outcome measures A composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each hospital and frequency of various care practices for acute kidney injury. Results 6030 patients were randomized over 22 months. The primary outcome occurred in 653 (21.3%) of 3059 patients with an alert and in 622 (20.9%) of 2971 patients receiving usual care (relative risk 1.02, 95% confidence interval 0.93 to 1.13, P=0.67). Analysis by each hospital showed worse outcomes in the two non-teaching hospitals (n=765, 13%), where alerts were associated with a higher risk of the primary outcome (relative risk 1.49, 95% confidence interval 1.12 to 1.98, P=0.006). More deaths occurred at these centers (15.6% in the alert group v 8.6% in the usual care group, P=0.003). Certain acute kidney injury care practices were increased in the alert group but did not appear to mediate these outcomes. Conclusions Alerts did not reduce the risk of our primary outcome among patients in hospital with acute kidney injury. The heterogeneity of effect across clinical centers should lead to a re-evaluation of existing alerting systems for acute kidney injury. Trial registration ClinicalTrials.gov NCT02753751 .

scholarly journals Risk Prediction of Renal Failure for Chronic Disease Population Based on Electronic Health Record Big Data

2021 ◽  
Vol 25 ◽  
pp. 100234
Author(s):  
Yujie Yang ◽  
Ye Li ◽  
Runge Chen ◽  
Jing Zheng ◽  
Yunpeng Cai ◽  
...  
Keyword(s):  
Renal Failure ◽  
Big Data ◽  
Chronic Disease ◽  
Electronic Health Record ◽  
Risk Prediction ◽  
Population Based ◽  
Health Record ◽  
Electronic Health
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