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Multi-parameter vital sign database to assist in alarm optimization for general care units

Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fati...

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Autores principales: Welch, James, Kanter, Benjamin, Skora, Brooke, McCombie, Scott, Henry, Isaac, McCombie, Devin, Kennedy, Rosemary, Soller, Babs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5081381/
https://www.ncbi.nlm.nih.gov/pubmed/26439830
http://dx.doi.org/10.1007/s10877-015-9790-8
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author Welch, James
Kanter, Benjamin
Skora, Brooke
McCombie, Scott
Henry, Isaac
McCombie, Devin
Kennedy, Rosemary
Soller, Babs
author_facet Welch, James
Kanter, Benjamin
Skora, Brooke
McCombie, Scott
Henry, Isaac
McCombie, Devin
Kennedy, Rosemary
Soller, Babs
author_sort Welch, James
collection PubMed
description Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fatigue. The objective of this study was the development of a methodology to help care teams optimize alarm settings. An on-body wireless monitoring system was used to continually assess heart rate, respiratory rate, SpO(2) and noninvasive blood pressure in the general ward of ten hospitals between April 1, 2014 and January 19, 2015. These data, 94,575 h for 3430 patients are contained in a large database, accessible with cloud computing tools. Simulation scenarios assessed the total alarm rate as a function of threshold and annunciation delay (s). The total alarm rate of ten alarms/patient/day predicted from the cloud-hosted database was the same as the total alarm rate for a 10 day evaluation (1550 h for 36 patients) in an independent hospital. Plots of vital sign distributions in the cloud-hosted database were similar to other large databases published by different authors. The cloud-hosted database can be used to run simulations for various alarm thresholds and annunciation delays to predict the total alarm burden experienced by nursing staff. This methodology might, in the future, be used to help reduce alarm fatigue without sacrificing the ability to continually monitor all vital signs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10877-015-9790-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-50813812016-11-10 Multi-parameter vital sign database to assist in alarm optimization for general care units Welch, James Kanter, Benjamin Skora, Brooke McCombie, Scott Henry, Isaac McCombie, Devin Kennedy, Rosemary Soller, Babs J Clin Monit Comput Original Research Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fatigue. The objective of this study was the development of a methodology to help care teams optimize alarm settings. An on-body wireless monitoring system was used to continually assess heart rate, respiratory rate, SpO(2) and noninvasive blood pressure in the general ward of ten hospitals between April 1, 2014 and January 19, 2015. These data, 94,575 h for 3430 patients are contained in a large database, accessible with cloud computing tools. Simulation scenarios assessed the total alarm rate as a function of threshold and annunciation delay (s). The total alarm rate of ten alarms/patient/day predicted from the cloud-hosted database was the same as the total alarm rate for a 10 day evaluation (1550 h for 36 patients) in an independent hospital. Plots of vital sign distributions in the cloud-hosted database were similar to other large databases published by different authors. The cloud-hosted database can be used to run simulations for various alarm thresholds and annunciation delays to predict the total alarm burden experienced by nursing staff. This methodology might, in the future, be used to help reduce alarm fatigue without sacrificing the ability to continually monitor all vital signs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10877-015-9790-8) contains supplementary material, which is available to authorized users. Springer Netherlands 2015-10-06 2016 /pmc/articles/PMC5081381/ /pubmed/26439830 http://dx.doi.org/10.1007/s10877-015-9790-8 Text en © The Author(s) 2015 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.
spellingShingle Original Research
Welch, James
Kanter, Benjamin
Skora, Brooke
McCombie, Scott
Henry, Isaac
McCombie, Devin
Kennedy, Rosemary
Soller, Babs
Multi-parameter vital sign database to assist in alarm optimization for general care units
title Multi-parameter vital sign database to assist in alarm optimization for general care units
title_full Multi-parameter vital sign database to assist in alarm optimization for general care units
title_fullStr Multi-parameter vital sign database to assist in alarm optimization for general care units
title_full_unstemmed Multi-parameter vital sign database to assist in alarm optimization for general care units
title_short Multi-parameter vital sign database to assist in alarm optimization for general care units
title_sort multi-parameter vital sign database to assist in alarm optimization for general care units
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5081381/
https://www.ncbi.nlm.nih.gov/pubmed/26439830
http://dx.doi.org/10.1007/s10877-015-9790-8
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