Cargando…
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...
Autores principales: | , , , , , , , |
---|---|
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 |
_version_ | 1782462879690129408 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5081381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT welchjames multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT kanterbenjamin multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT skorabrooke multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT mccombiescott multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT henryisaac multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT mccombiedevin multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT kennedyrosemary multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits AT sollerbabs multiparametervitalsigndatabasetoassistinalarmoptimizationforgeneralcareunits |