Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15th ADQI Consensus Conference

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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.

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Les dossiers médicaux électroniques et les systèmes de renseignements cliniques sont de plus en plus utilisés dans les hôpitaux. Ces éléments pourraient être mis à profit pour faciliter le dépistage de l’insuffisance rénale aigüe (IRA) et améliorer les soins offerts aux patients qui en souffrent. Lors de la dernière réunion du Acute Dialysis Quality Initiative (ADQI), un groupe de travail s’est réuni pour établir un consensus autour de principes régissant la constitution d’un système automatisé de détection de l’IRA. Un système qui permettrait de produire des alertes en temps réel pour dépister les cas d’IRA (alertes IRA). Le groupe de travail a reconnu que de telles alertes représenteraient des opportunités de procéder à une évaluation clinique ou un dépistage précoce de la maladie et donc, à des interventions plus rapides, plutôt que de ne constituer qu’un indicateur diagnostique. Les membres du groupe de travail se sont entendus pour que le système d’alertes IRA soit développé en se basant sur la classification établie par le KIDGO. Ils ont toutefois recommandé que des travaux ultérieurs soient effectués pour raffiner les alertes et pour que celles-ci soient suivies de recommandations applicables et assorties d’un plan concret de soins à offrir aux patients. Les déclarations consensuelles présentées dans ce compte-rendu pourraient constituer le plan de développement pour la mise au point d’applications électroniques permettant la détection et le signalement de cas d’IRA de façon automatisée.

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The online version of this article (doi:10.1186/s40697-016-0100-2) contains supplementary material, which is available to authorized users.

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Most cited references 33

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Diagnosis, epidemiology and outcomes of acute kidney injury.

K. Liu, Sushrut S Waikar, Glenn Chertow (2008)

Acute kidney injury is an increasingly common and potentially catastrophic complication in hospitalized patients. Early observational studies from the 1980s and 1990s established the general epidemiologic features of acute kidney injury: the incidence, prognostic significance, and predisposing medical and surgical conditions. Recent multicenter observational cohorts and administrative databases have enhanced our understanding of the overall disease burden of acute kidney injury and trends in its epidemiology. An increasing number of clinical studies focusing on specific types of acute kidney injury (e.g., in the setting of intravenous contrast, sepsis, and major surgery) have provided further details into this heterogeneous syndrome. Despite our sophisticated understanding of the epidemiology and pathobiology of acute kidney injury, current prevention strategies are inadequate and current treatment options outside of renal replacement therapy are nonexistent. This failure to innovate may be due in part to a diagnostic approach that has stagnated for decades and continues to rely on markers of glomerular filtration (blood urea nitrogen and creatinine) that are neither sensitive nor specific. There has been increasing interest in the identification and validation of novel biomarkers of acute kidney injury that may permit earlier and more accurate diagnosis. This review summarizes the major epidemiologic studies of acute kidney injury and efforts to modernize the approach to its diagnosis.

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Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients

Etienne Macedo, Josée Bouchard, Sharon H Soroko … (2010)

Introduction Serum creatinine concentration (sCr) is the marker used for diagnosing and staging acute kidney injury (AKI) in the RIFLE and AKIN classification systems, but is influenced by several factors including its volume of distribution. We evaluated the effect of fluid accumulation on sCr to estimate severity of AKI. Methods In 253 patients recruited from a prospective observational study of critically-ill patients with AKI, we calculated cumulative fluid balance and computed a fluid-adjusted sCr concentration reflecting the effect of volume of distribution during the development phase of AKI. The time to reach a relative 50% increase from the reference sCr using the crude and adjusted sCr was compared. We defined late recognition to estimate severity of AKI when this time interval to reach 50% relative increase between the crude and adjusted sCr exceeded 24 hours. Results The median cumulative fluid balance increased from 2.7 liters on day 2 to 6.5 liters on day 7. The difference between adjusted and crude sCr was significantly higher at each time point and progressively increased from a median difference of 0.09 mg/dL to 0.65 mg/dL after six days. Sixty-four (25%) patients met criteria for a late recognition to estimate severity progression of AKI. This group of patients had a lower urine output and a higher daily and cumulative fluid balance during the development phase of AKI. They were more likely to need dialysis but showed no difference in mortality compared to patients who did not meet the criteria for late recognition of severity progression. Conclusions In critically-ill patients, the dilution of sCr by fluid accumulation may lead to underestimation of the severity of AKI and increases the time required to identify a 50% relative increase in sCr. A simple formula to correct sCr for fluid balance can improve staging of AKI and provide a better parameter for earlier recognition of severity progression.

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Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials.

Anwesha N Fernandes, Brian Hemens, G. Der Sahakian … (2012)

To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Meta-regression analysis of randomised controlled trials. A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. "Effective" systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party.

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Author and article information

Contributors

Matthew T. James: mjames@ucalgary.ca

Journal

Journal ID (nlm-ta): Can J Kidney Health Dis

Journal ID (iso-abbrev): Can J Kidney Health Dis

Title: Canadian Journal of Kidney Health and Disease

Publisher: BioMed Central (London )

ISSN (Electronic): 2054-3581

Publication date (Electronic): 26 February 2016

Publication date PMC-release: 26 February 2016

Publication date Collection: 2016

Volume: 3

Electronic Location Identifier: 9

Affiliations

[ ]Departments of Medicine and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Canada

[ ]Department of Health Services Research, Management and Policy, University of Florida, Gainesville, Florida

[ ]Department of Intensive Care Medicine, Saint-Etienne University Hospital, Saint-Priest-En-Jarez, France

[ ]Department of Medicine, Division of Nephrology, Columbia University Medical Center, New York, NY USA

[ ]Division of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada

[ ]Department of Nephrology, Dialysis and Transplantation, International Renal Research Institute of Vicenza, San Bortolo Hospital, Vicenza, Italy

[ ]Department of Pediatrics, Division of Pediatric Nephrology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH USA

[ ]Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA USA

Article

Publisher ID: 100

DOI: 10.1186/s40697-016-0100-2

PMC ID: 4768328

PubMed ID: 26925245

SO-VID: 834a2834-5b5c-41ec-9384-7abd48db4a54

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 19 October 2015

Date accepted : 5 January 2016

Funding

Funded by: Acute Dialysis Quality Initiative (ADQI)

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Keywords: acute kidney injury,detection,clinical informatics,clinical decision support

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Keywords: acute kidney injury, detection, clinical informatics, clinical decision support

Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15 ^th ADQI Consensus Conference

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Most cited references 33

Diagnosis, epidemiology and outcomes of acute kidney injury.

Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients

Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials.

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Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15 th ADQI Consensus Conference

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Electronic supplementary material

Karger: Nephrology

Diagnosis, epidemiology and outcomes of acute kidney injury.

Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients

Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials.

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Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15 ^th ADQI Consensus Conference