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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

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 a...

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Autores principales: James, Matthew T., Hobson, Charles E., Darmon, Michael, Mohan, Sumit, Hudson, Darren, Goldstein, Stuart L., Ronco, Claudio, Kellum, John A., Bagshaw, Sean M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768328/
https://www.ncbi.nlm.nih.gov/pubmed/26925245
http://dx.doi.org/10.1186/s40697-016-0100-2
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author James, Matthew T.
Hobson, Charles E.
Darmon, Michael
Mohan, Sumit
Hudson, Darren
Goldstein, Stuart L.
Ronco, Claudio
Kellum, John A.
Bagshaw, Sean M.
author_facet James, Matthew T.
Hobson, Charles E.
Darmon, Michael
Mohan, Sumit
Hudson, Darren
Goldstein, Stuart L.
Ronco, Claudio
Kellum, John A.
Bagshaw, Sean M.
author_sort James, Matthew T.
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: 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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spelling pubmed-47683282016-02-27 Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference James, Matthew T. Hobson, Charles E. Darmon, Michael Mohan, Sumit Hudson, Darren Goldstein, Stuart L. Ronco, Claudio Kellum, John A. Bagshaw, Sean M. Can J Kidney Health Dis Review 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40697-016-0100-2) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-26 /pmc/articles/PMC4768328/ /pubmed/26925245 http://dx.doi.org/10.1186/s40697-016-0100-2 Text en © James et al. 2016 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.
spellingShingle Review
James, Matthew T.
Hobson, Charles E.
Darmon, Michael
Mohan, Sumit
Hudson, Darren
Goldstein, Stuart L.
Ronco, Claudio
Kellum, John A.
Bagshaw, Sean M.
Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title_full Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title_fullStr Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title_full_unstemmed Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title_short Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference
title_sort applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) adqi consensus conference
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768328/
https://www.ncbi.nlm.nih.gov/pubmed/26925245
http://dx.doi.org/10.1186/s40697-016-0100-2
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