A simple electronic alert for acute kidney injury

Abstract

Background: Acute kidney injury (AKI) is frequently under-recognized and contributes to poor outcomes. Electronic alerts (e-alerts) to highlight AKI based on changes in serum creatinine may facilitate earlier recognition and treatment, and sophisticated algorithms for AKI detection have been proposed or implemented elsewhere. However, many laboratories currently lack the resources or capability to replicate these systems. Methods: A real-time automated delta check e-alert flags a 50% increase in creatinine to a concentration of >50 mmol/L from the most recent result within a 90-day period and automatically adds the comment '?AKI -creatinine increase >50% from previous' with a link to local AKI guidelines. In addition, creatinine results >300 mmol/L are retrospectively reviewed and phoned if AKI is suspected. For each alert over a 12-day period we manually reviewed previous and subsequent creatinine results to determine baseline creatinine and stage AKI according to Acute Kidney Injury Network (AKIN) criteria. Results: From 11,930 creatinine requests, 63 of 90 (70%) delta check e-alerts were due to AKI, identifying 61 episodes of AKI. Thirty four of 54 (63%) creatinine results >300 mmol/L were due to AKI, identifying a further 10 episodes of AKI. The positive predictive value (PPV) for AKI of a delta check e-alert was greater when the trigger creatinine was >100 mmol/L (PPV 89%) or when the absolute change in creatinine was >50 mmol/L (PPV 93%). Conclusion:This study demonstrates that a simple automated delta check can detect and flag AKI in real time, continuously, at little extra cost and without manual input. KeywordsRenal disease, creatinine, laboratory methods, AKIN, delta check Accepted: 17th April 2014 IntroductionAcute kidney injury (AKI) is a sudden decline in renal function, generally occurring over hours or days. AKI is increasingly recognized as a common and serious complication of many hospital admissions and is associated with poor outcomes such as increased mortality, 1 chronic kidney disease (CKD) progression, 2 prolonged hospital stay and increased healthcare costs. Furthermore, there is evidence that AKI is frequently under-recognized; delays in recognizing and treating AKI were a major criticism in a 2009 National Confidential Enquiry into Patient Outcomes and Death report into the care of patients who died with a primary diagnosis of AKI. 4 Electronic alerts (e-alerts) to highlight possible AKI to the requesting clinician or renal team based on changes in serum creatinine are one strategy to facilitate earlier recognition and treatment of AKI. This approach has been backed by a 2012 UK Consensus Conference on AKI management hosted by the Royal College of Physicians

Identification of Major Adverse Kidney Events Within the Electronic Health Record

“…Manual chart review by two physicians is a well-recognized reference standard for kidney injury outcomes, and the 91 % agreement between the two initial reviewers in our study was similar to that observed in previous AKI studies [28, 31]. Including all ICU admissions allowed examination of performance characteristics over a wide spectrum of underlying illness, including patients with CKD (for whom risk of AKI is high but assessment of baseline creatinine may be challenging) and patients receiving RRT prior to admission (who remain at risk for the in-hospital mortality component of MAKE).…”

Overestimation of 25-hydroxyvitamin D3 by increased ionisation efficiency of 3-epi-25-hydroxyvitamin D3 in LC–MS/MS methods not separating both metabolites as determined by an LC–MS/MS method for separate quantification of 25-hydroxyvitamin D3, 3-epi-25-hydroxyvitamin D3 and 25-hydroxyvitamin D2 in human serum

“…APCI and APPI), or with other instrumentation or chromatographic conditions. Recently, an article has been published leading to a similar conclusion of overestimation of the 3-epi-25(OH)D 3 concentration from increased ionisation using ESI-LC-MS/MS [24]. These authors showed that signal enhancement was dependent on mobile phase composition, with increasing signal enhancement at higher methanol concentrations.…”

Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patients

“…For instance, when the patient was using a SSRI and the sodium level was 129 mmol/l, only marginally low, the CDSS would alert the physician while during the grand round this sodium level might have been noticed but did not immediately alarm the physicians. Perhaps a fixed cut-off value is not always significant, but a percentage change in a certain value may be more useful in clinical practice, [23]. On the down-side, relying solely on percent changes of laboratory values may only detect events at a late stage.…”