ArticleApplied clinical informatics2014
Development and performance of electronic acute kidney injury triggers to identify pediatric patients at risk for nephrotoxic medication-associated harm.
Article in Applied clinical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review.Paediatric drugs · 2024Pooled it
- External Validation, Recalibration, and Extension of a Prediction Model of Early Acute Kidney Injury in Critically Ill Children Using Multicenter Data.Critical care explorations · 2026Article
- A multi-center collaborative highlights the differences in nephrotoxic medication exposure and associated AKI in pediatric bone marrow transplant, oncology, and pulmonary service lines.Pediatric nephrology (Berlin, Germany) · 2026Article
- Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup.Nature reviews. Nephrology · 2023Review
- Alerting to acute kidney injury - Challenges, benefits, and strategies.Practical laboratory medicine · 2022Article
- Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury.BMC medical informatics and decision making · 2020Article
- Clinical Decision Support System with Renal Dose Adjustment Did Not Improve Subsequent Renal and Hepatic Function among Inpatients: The Japan Adverse Drug Event Study.Applied clinical informatics · 2020Article
- Current Status of Novel Biomarkers for the Diagnosis of Acute Kidney Injury: A Historical Perspective.Journal of intensive care medicine · 2020Article
- Impact of acute kidney injury and nephrotoxic exposure on hospital length of stay.Pediatric nephrology (Berlin, Germany) · 2020Article
- Data Challenges With Real-Time Safety Event Detection And Clinical Decision Support.Journal of medical Internet research · 2019Article
- eResearch in acute kidney injury: a primer for electronic health record research.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2019Review
- Safety Lapses Prior to Initiation of Hemodialysis for Acute Kidney Injury in Hospitalized Patients: A Patient Safety Initiative.Journal of clinical medicine · 2018Article
- Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review.International journal of molecular sciences · 2017Review
- Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics.Journal of the American Medical Informatics Association : JAMIA · 2017Review
- Drug-associated acute kidney injury: who's at risk?Pediatric nephrology (Berlin, Germany) · 2017Review
- Leveraging Food and Drug Administration Adverse Event Reports for the Automated Monitoring of Electronic Health Records in a Pediatric Hospital.Biomedical informatics insights · 2017Article
- Nephrotoxicities.F1000Research · 2017Review
- Previous aminoglycoside use and acute kidney injury risk in non-critically ill children.Pediatric nephrology (Berlin, Germany) · 2017Article
- Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference.Canadian journal of kidney health and disease · 2016Review
- Acute kidney injury in the era of big data: the 15(th) Consensus Conference of the Acute Dialysis Quality Initiative (ADQI).Canadian journal of kidney health and disease · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundNephrotoxic medication-associated acute kidney injury (NTMx-AKI) is a costly clinical phenomenon and more common than previously recognized. Prior efforts to use technology to identify AKI have focused on detection after renal injury has occurred.
objectivesDescribe an approach and provide a technical framework for the creation of risk-stratifying AKI triggers and the development of an application to manage the AKI trigger data. Report the performance characteristics of those triggers and the refinement process and on the challenges of implementation.
methodsInitial manual trigger screening guided design of an automated electronic trigger report. A web-based application was designed to alleviate inefficiency and serve as a user interface and central workspace for the project. Performance of the NTMx exposure trigger reports from September 2011 to September 2013 were evaluated using sensitivity (SN), specificity (SP), positive and negative predictive values (PPV, NPV).
resultsAutomated reports were created to replace manual screening for NTMx-AKI. The initial performance of the NTMx exposure triggers for SN, SP, PPV, and NPV all were ≥0.78, and increased over the study, with all four measures reaching ≥0.95 consistently. A web-based application was implemented that simplifies data entry and couriering from the reports, expedites results viewing, and interfaces with an automated data visualization tool. Sociotechnical challenges were logged and reported.
conclusionWe have built a risk-stratifying system based on electronic triggers that detects patients at-risk for NTMx-AKI before injury occurs. The performance of the NTMx-exposed reports has neared 100% through iterative optimization. The complexity of the trigger logic and clinical workflows surrounding NTMx-AKI led to a challenging implementation, but one that has been successful from technical, clinical, and quality improvement standpoints. This report summarizes the construction of a trigger-based application, the performance of the triggers, and the challenges uncovered during the design, build, and implementation of the system.
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