Applications for Detection of Acute Kidney Injury Using Electronic Medical Records and Clinical Information Systems: Workgroup Statements from the 15th ADQI Consensus Conference. Issue 1 (26th February 2016)

• Record Type: Journal Article
• Authors: James, Matthew T.; Hobson, Charles E.; Darmon, Michael; Mohan, Sumit; Hudson, Darren; Goldstein, Stuart L.; Ronco, Claudio; Kellum, John A.; Bagshaw, Sean M.
• Is Part Of: Canadian journal of kidney health and disease =. Volume 3:Issue 1(2016)
• Publication Date: 2016-02-26
• Subjects: Acute kidney injury -- Detection -- Clinical informatics -- Clinical decision support; Kidneys -- Diseases -- Periodicals; Nephrology -- Periodicals; Dialysis -- Periodicals; Kidneys -- Transplantation -- Periodicals; Kidney Diseases -- Periodicals; Nephrology -- Periodicals; Dialysis -- Periodicals; Kidney Transplantation -- Periodicals; Dialysis; Kidneys -- Diseases; Kidneys -- Transplantation; Nephrology; Periodicals; Electronic journals; 616.61005
• DOI: 10.1186/s40697-016-0100-2
• Languages: English
• ISSNs: 2054-3581

Abstract

Electronic medical records and clinical information systems are increasingly used in hospitals and can be leveraged to improve recognition and care for acute kidney injury. This Acute Dialysis Quality Initiative (ADQI) workgroup was convened to develop consensus around principles for the design of automated AKI detection systems to produce real-time AKI alerts using electronic systems. AKI alerts were recognized by the workgroup as an opportunity to prompt earlier clinical evaluation, further testing and ultimately intervention, rather than as a diagnostic label. Workgroup members agreed with designing AKI alert systems to align with the existing KDIGO classification system, but recommended future work to further refine the appropriateness of AKI alerts and to link these alerts to actionable recommendations for AKI care. The consensus statements developed in this review can be used as a roadmap for development of future electronic applications for automated detection and reporting of AKI.