Dataset Information

Understanding Electronic AKI Alerts: Characterization by Definitional Rules.

ABSTRACT: Introduction:Automated acute kidney injury (AKI) electronic alerts are based on comparing creatinine with historic results. Methods:We report the significance of AKI defined by 3 "rules" differing in the time period from which the baseline creatinine is obtained, and AKI with creatinine within the normal range. Results:A total of 47,090 incident episodes of AKI occurred between November 2013 and April 2016. Rule 1 (>26 ?mol/l increase in creatinine within 48 hours) accounted for 9.6%. Rule 2 (?50% increase in creatinine within previous 7 days) and rule 3 (?50% creatinine increase from the median value of results within the last 8-365 days) accounted for 27.3% and 63.1%, respectively. Hospital-acquired AKI was predominantly identified by rules 1 and 2 (71.7%), and community-acquired AKI (86.3%) by rule 3. Stages 2 and 3 were detected by rules 2 and 3. Ninety-day mortality was higher in AKI rule 2 (32.4%) than rule 1 (28.3%, P < 0.001) and rule 3 (26.6%, P < 0.001). Nonrecovery of renal function (90 days) was lower for rule 1 (7.9%) than rule 2 (22.4%, P < 0.001) and rule 3 (16.5%, P < 0.001). We found that 19.2% of AKI occurred with creatinine values within normal range, in which mortality was lower than that in AKI detected by a creatinine value outside the reference range (22.6% vs. 29.6%, P < 0.001). Discussion:Rule 1 could only be invoked for stage 1 alerts and was associated with acute on chronic kidney disease acquired in hospital. Rule 2 was also associated with hospital-acquired AKI and had the highest mortality and nonrecovery. Rule 3 was the commonest cause of an alert and was associated with community-acquired AKI.

SUBMITTER: Holmes J

PROVIDER: S-EPMC5678680 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Understanding Electronic AKI Alerts: Characterization by Definitional Rules.

Holmes Jennifer J Roberts Gethin G Meran Soma S Williams John D JD Phillips Aled O AO

Kidney international reports 20161209 3

<h4>Introduction</h4>Automated acute kidney injury (AKI) electronic alerts are based on comparing creatinine with historic results.<h4>Methods</h4>We report the significance of AKI defined by 3 "rules" differing in the time period from which the baseline creatinine is obtained, and AKI with creatinine within the normal range.<h4>Results</h4>A total of 47,090 incident episodes of AKI occurred between November 2013 and April 2016. Rule 1 (>26 μmol/l increase in creatinine within 48 hours) accounte ...[more]

PMID: 29142963

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Project description:ObjectiveTo determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury.DesignDouble blinded, multicenter, parallel, randomized controlled trial.SettingSix 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.Participants6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria.InterventionsAn 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 measuresA 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.Results6030 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.ConclusionsAlerts 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 registrationClinicalTrials.gov NCT02753751.

Project description:Background and objectivesElectronic alerts for heterogenous conditions such as AKI may not provide benefit for all eligible patients and can lead to alert fatigue, suggesting that personalized alert targeting may be useful. Uplift-based alert targeting may be superior to purely prognostic-targeting of interventions because uplift models assess marginal treatment effect rather than likelihood of outcome.Design, setting, participants, & measurementsThis is a secondary analysis of a clinical trial of 2278 adult patients with AKI randomized to an automated, electronic alert system versus usual care. We used three uplift algorithms and one purely prognostic algorithm, trained in 70% of the data, and evaluated the effect of targeting alerts to patients with higher scores in the held-out 30% of the data. The performance of the targeting strategy was assessed as the interaction between the model prediction of likelihood to benefit from alerts and randomization status. The outcome of interest was maximum relative change in creatinine from the time of randomization to 3 days after randomization.ResultsThe three uplift score algorithms all gave rise to a significant interaction term, suggesting that a strategy of targeting individuals with higher uplift scores would lead to a beneficial effect of AKI alerting, in contrast to the null effect seen in the overall study. The prognostic model did not successfully stratify patients with regards to benefit of the intervention. Among individuals in the high uplift group, alerting was associated with a median reduction in change in creatinine of -5.3% (P=0.03). In the low uplift group, alerting was associated with a median increase in change in creatinine of +5.3% (P=0.005). Older individuals, women, and those with a lower randomization creatinine were more likely to receive high uplift scores, suggesting that alerts may benefit those with more slowly developing AKI.ConclusionsUplift modeling, which accounts for treatment effect, can successfully target electronic alerts for AKI to those most likely to benefit, whereas purely prognostic targeting cannot.

Project description:BACKGROUND:Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. METHODS AND FINDINGS:A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014-16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981-1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858-0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560-0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. CONCLUSIONS:In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness. TRIAL REGISTRATION:Clinicaltrials.org NCT03047382.

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Understanding Electronic AKI Alerts: Characterization by Definitional Rules.

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Understanding Electronic AKI Alerts: Characterization by Definitional Rules.

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