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Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial.

ABSTRACT: BACKGROUND:Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital. METHODS:In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA, USA. Eligible participants were adults aged 18 years or older who were in hospital with stage 1 or greater acute kidney injury as defined by Kidney Disease Improving Global Outcomes creatinine-based criteria. Exclusion criteria were initial hospital creatinine 4·0 mg/dL (to convert to ?mol/L, multiply by 88·4) or greater, fewer than two creatinine values measured, inability to determine the covering provider, admission to hospice or the observation unit, previous randomisation, or end-stage renal disease. Patients were randomly assigned (1:1) via a computer-generated sequence to receive an acute kidney injury alert (a text-based alert sent to the covering provider and unit pharmacist indicating new acute kidney injury) or usual care, stratified by medical versus surgical admission and intensive care unit versus non-intensive care unit location in blocks of 4-8 participants. The primary outcome was a composite of relative maximum change in creatinine, dialysis, and death at 7 days after randomisation. All analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01862419. FINDINGS:Between Sept 17, 2013, and April 14, 2014, 23,664 patients were screened. 1201 eligible participants were assigned to the acute kidney injury alert group and 1192 were assigned to the usual care group. Composite relative maximum change in creatinine, dialysis, and death at 7 days did not differ between the alert group and the usual care group (p=0·88), or within any of the four randomisation strata (all p>0·05). At 7 days after randomisation, median maximum relative change in creatinine concentrations was 0·0% (IQR 0·0-18·4) in the alert group and 0·6% (0·0-17·5) in the usual care group (p=0·81); 87 (7·2%) patients in the alert group and 70 (5·9%) patients in usual care group had received dialysis (odds ratio 1·25 [95% CI 0·90-1·74]; p=0·18); and 71 (5·9%) patients in the alert group and 61 (5·1%) patients in the usual care group had died (1·16 [0·81-1·68]; p=0·40). INTERPRETATION:An electronic alert system for acute kidney injury did not improve clinical outcomes among patients in hospital. FUNDING:Penn Center for Healthcare Improvement and Patient Safety.

SUBMITTER: Wilson FP

PROVIDER: S-EPMC4475457 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial.

Wilson F Perry FP Shashaty Michael M Testani Jeffrey J Aqeel Iram I Borovskiy Yuliya Y Ellenberg Susan S SS Feldman Harold I HI Fernandez Hilda H Gitelman Yevgeniy Y Lin Jennie J Negoianu Dan D Parikh Chirag R CR Reese Peter P PP Urbani Richard R Fuchs Barry B

Lancet (London, England) 20150226 9981

<h4>Background</h4>Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital.<h4>Methods</h4>In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA ...[more]

PMID: 25726515

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Project description:IntroductionAcute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack of strong evidence of their benefits. We designed a multicentre, randomised, controlled trial to evaluate the effectiveness of AKI alerts. Our aim is to highlight several challenges faced in the design of this trial, which uses electronic screening, enrolment, randomisation, intervention and data collection.Methods and analysisThe design and implementation of an electronic alert system for AKI was a reiterative process involving several challenges and limitations set by the confines of the electronic medical record system. The trial will electronically identify and randomise 6030 adults with AKI at six hospitals over a 1.5-2 year period to usual care versus an electronic alert containing an AKI-specific order set. Our primary outcome will be a composite of AKI progression, inpatient dialysis and inpatient death within 14 days of randomisation. During a 1-month pilot in the medical intensive care unit of Yale New Haven Hospital, we have demonstrated feasibility of automating enrolment and data collection. Feedback from providers exposed to the alerts was used to continually improve alert clarity, user friendliness and alert specificity through refined inclusion and exclusion criteria.Ethics and disseminationThis study has been approved by the appropriate ethics committees for each of our study sites. Our study qualified for a waiver of informed consent as it presents no more than minimal risk and cannot be feasibly conducted in the absence of a waiver. We are committed to open dissemination of our data through clinicaltrials.gov and submission of results to the NIH data sharing repository. Results of our trial will be submitted for publication in a peer-reviewed journal.Trial registration numberNCT02753751; Pre-results.

Project description:BackgroundEngaging, interactive, and automated virtual reality (VR) treatments might help solve the unmet needs of individuals with mental health disorders. We tested the efficacy of an automated cognitive intervention for fear of heights guided by an avatar virtual coach (animated using motion and voice capture of an actor) in VR and delivered with the latest consumer equipment.MethodsWe did a randomised trial of automated VR versus usual care. We recruited adults aged older than 18 years with a fear of heights by radio advertisements in Oxfordshire, UK. We diagnosed fear of heights if participants scored more than 29 on the Heights Interpretation Questionnaire (HIQ). We randomly allocated participants by computer in a 1:1 ratio to either automated VR delivered in roughly six 30-min sessions administered about two to three times a week over a 2-week period (intervention group) or to usual care (control group). Randomisation was stratified by severity of fear of heights. The research team, who were unaware of the random allocation, administered three fear-of-height assessments, at baseline (0 weeks), at the end of treatment (2 weeks), and at follow-up (4 weeks). The primary outcome measure was HIQ score (range 16-80, with higher scores indicating greater severity). This trial is registered with the ISRCTN registry, number ISRCTN11898283.FindingsBetween Nov 25, 2017, and Feb 27, 2018, 100 individuals were enrolled and underwent randomisation, of whom 49 were assigned to the VR treatment group and 51 to the control group. All participants completed the 4-week follow-up. The mean total treatment time in VR was 124·43 min (SD 34·23). Compared with participants in the control group, the VR treatment reduced fear of heights at the end of treatment (mean change score -24·5 [SD 13·1] in the VR group vs -1·2 [7·3] in the control group; adjusted difference -24·0, 95% CI -27·7 to -20·3; Cohen's d=2·0; p<0·0001). The benefit was maintained at follow-up (mean change score -25·1 [SD 13·9] in the VR group vs -1·5 [7·8] in the control group; adjusted difference -24·3, 95% CI -27·9 to -20·6; Cohen's d=2·0; p<0·0001). The number needed to treat to at least halve the fear of heights was 1·3. No adverse events were reported.InterpretationPsychological therapy delivered automatically by a VR coach can produce large clinical benefits. Evidence-based VR treatments have the potential to greatly increase treatment provision for mental health disorders.FundingOxford VR, and the National Institute of Health Research Oxford Health Biomedical Research Centre.

Project description:IntroductionMany patients with psychosis experience everyday social situations as anxiety-provoking. The fears can arise, for example, from paranoia, hallucinations, social anxiety or negative-self beliefs. The fears lead patients to withdraw from activities, and this isolation leads to a cycle of worsening physical and mental health. Breaking this cycle requires highly active treatment directly in the troubling situations so that patients learn that they can safely and confidently enter them. However patients with psychosis seldom receive such life-changing interventions. To solve this problem we have developed an automated psychological treatment delivered in virtual reality (VR). It allows patients to experience computer simulations of the situations that they find anxiety-provoking. A virtual coach guides patients, using cognitive techniques, in how to overcome their fears. Patients are willing to enter VR simulations of anxiety-provoking situations because they know the simulations are not real, but the learning made transfers to the real world.Methods and analysis432 patients with psychosis and anxious avoidance of social situations will be recruited from National Health Service (NHS) secondary care services. In the gameChange trial, they will be randomised (1:1) to the six-session VR cognitive treatment added to treatment as usual or treatment as usual alone. Assessments will be conducted at 0, 6 (post-treatment) and 26 weeks by a researcher blind to allocation. The primary outcome is avoidance and distress in real-life situations, using a behavioural assessment task, at 6?weeks. The secondary outcomes are psychiatric symptoms, activity levels and quality of life. All main analyses will be intention-to-treat. Moderation and mediation will be tested. An economic evaluation will be conducted.Ethics and disseminationThe trial has received ethical approval from the NHS South Central - Oxford B Research Ethics Committee (19/SC/0075). A key output will be a high-quality automated VR treatment for patients to overcome anxious avoidance of social situations.Trial registration numberISRCTN17308399.

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:Persecutory delusions are a major psychiatric problem and are associated with a wide range of adverse outcomes. Our theoretical model views these delusions as unfounded threat beliefs which persist due to defence behaviours (e.g. avoidance) that prevent disconfirmatory evidence being processed. The treatment implications are that patients need to (1) go into feared situations and (2) not use defence behaviours. This enables relearning of safety and hence paranoia diminution. However, this is very difficult for patients due to their severe anxiety. A solution is to use virtual reality (VR) social situations, which are graded in difficulty and which patients find much easier to enter. We have now automated the provision of cognitive therapy within VR using an avatar coach, so that a therapist is not required and the treatment is scalable. In the THRIVE trial, the automated VR cognitive treatment will be tested against a VR control condition. It will contribute to our wider programme of work developing VR for patients with psychosis. METHODS:Patients with persistent persecutory delusions in the context of non-affective psychosis will be randomised (1:1) to the automated VR cognitive treatment or VR mental relaxation (control condition). Each VR treatment will comprise approximately four sessions of 30 min. Standard care will remain as usual in both groups. Assessments will be carried out at 0, 2, 4 (post treatment), 8, 16, and 24?weeks by a researcher blind to treatment allocation. The primary outcome is degree of conviction in the persecutory delusion (primary endpoint 4?weeks). Effect sizes will be re-established by an interim analysis of 30 patients. If the interim effect size suggests that the treatment is worth pursuing (d?>?0.1), then the trial will go on to test 90 patients in total. Secondary outcomes include real world distress, activity levels, suicidal ideation, and quality of life. Mediation will also be tested. All main analyses will follow the intention-to-treat principle. The trial is funded by the Medical Research Council Developmental Pathway Funding Scheme. DISCUSSION:The trial will provide the first test of automated cognitive therapy within VR for patients with psychosis. The treatment is potentially highly scalable for treatment services. TRIAL REGISTRATION:ISRCTN, ISRCTN12497310 . Registered on 14 August 2018.

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:BackgroundAcute kidney injury is common in hospitalized patients, increases morbidity and mortality, and is under-recognized. To improve provider recognition, we previously developed an electronic alert system for acute kidney injury. To test the hypothesis that this electronic acute kidney injury alert could improve patient outcome, we designed a randomized controlled trial to test the effectiveness of this alert in hospitalized patients. The study design presented several methodologic, ethical, and statistical challenges.PurposeTo highlight the challenges faced and the solutions employed in the design and implementation of a clinical trial to determine whether the provision of an early electronic alert for acute kidney injury would improve outcomes in hospitalized patients. Challenges included how to randomize the delivery of the alert system and the ethical framework for waiving informed consent. Other methodologic challenges included the selection and statistical evaluation of our study outcome, a ranked-composite of a continuous covariate (creatinine) and two dichotomous outcomes (dialysis and death), and the use of the medical record as a source of trial data.MethodsWe have designed a randomized trial to assess the effectiveness of an electronic alert system for acute kidney injury. With broad inclusion criteria, and a waiver of informed consent, we enroll and randomize virtually every patient with acute kidney injury in our hospital.ResultsAs of 31 March 2014, we have enrolled 2373 patients of 2400 targeted. Pre-alert data demonstrated a strong association between severity of acute kidney injury and inpatient mortality with a range of 6.4% in those with mild, stage 1 acute kidney injury, to 29% among those with stage 3 acute kidney injury (p < 0.001). We judged that informed consent would undermine the scientific validity of the study and present harms that are out of proportion to the very low risk intervention.ConclusionOur study demonstrates the feasibility of designing an ethical randomized controlled trial of an early electronic alert for acute kidney injury without obtaining informed consent from individual participants. Our study outcome may serve as a model for other studies of acute kidney injury, insofar as our paradigm accounts for the effect that early death and dialysis have on assessment of acute kidney injury severity as defined by maximum achieved serum creatinine.

Dataset Information

Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial.

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Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial.

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