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The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study

Intensive care units (ICU) are often overflooded with alarms from monitoring devices which constitutes a hazard to both staff and patients. To date, the suggested solutions to excessive monitoring alarms have remained on a research level. We aimed to identify patient characteristics that affect the...

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Autores principales: Sinno, Zeena-Carola, Shay, Denys, Kruppa, Jochen, Klopfenstein, Sophie A.I., Giesa, Niklas, Flint, Anne Rike, Herren, Patrick, Scheibe, Franziska, Spies, Claudia, Hinrichs, Carl, Winter, Axel, Balzer, Felix, Poncette, Akira-Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758124/
https://www.ncbi.nlm.nih.gov/pubmed/36526892
http://dx.doi.org/10.1038/s41598-022-26261-4
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author Sinno, Zeena-Carola
Shay, Denys
Kruppa, Jochen
Klopfenstein, Sophie A.I.
Giesa, Niklas
Flint, Anne Rike
Herren, Patrick
Scheibe, Franziska
Spies, Claudia
Hinrichs, Carl
Winter, Axel
Balzer, Felix
Poncette, Akira-Sebastian
author_facet Sinno, Zeena-Carola
Shay, Denys
Kruppa, Jochen
Klopfenstein, Sophie A.I.
Giesa, Niklas
Flint, Anne Rike
Herren, Patrick
Scheibe, Franziska
Spies, Claudia
Hinrichs, Carl
Winter, Axel
Balzer, Felix
Poncette, Akira-Sebastian
author_sort Sinno, Zeena-Carola
collection PubMed
description Intensive care units (ICU) are often overflooded with alarms from monitoring devices which constitutes a hazard to both staff and patients. To date, the suggested solutions to excessive monitoring alarms have remained on a research level. We aimed to identify patient characteristics that affect the ICU alarm rate with the goal of proposing a straightforward solution that can easily be implemented in ICUs. Alarm logs from eight adult ICUs of a tertiary care university-hospital in Berlin, Germany were retrospectively collected between September 2019 and March 2021. Adult patients admitted to the ICU with at least 24 h of continuous alarm logs were included in the study. The sum of alarms per patient per day was calculated. The median was 119. A total of 26,890 observations from 3205 patients were included. 23 variables were extracted from patients' electronic health records (EHR) and a multivariable logistic regression was performed to evaluate the association of patient characteristics and alarm rates. Invasive blood pressure monitoring (adjusted odds ratio (aOR) 4.68, 95%CI 4.15–5.29, p < 0.001), invasive mechanical ventilation (aOR 1.24, 95%CI 1.16–1.32, p < 0.001), heart failure (aOR 1.26, 95%CI 1.19–1.35, p < 0.001), chronic renal failure (aOR 1.18, 95%CI 1.10–1.27, p < 0.001), hypertension (aOR 1.19, 95%CI 1.13–1.26, p < 0.001), high RASS (aOR 1.22, 95%CI 1.18–1.25, p < 0.001) and scheduled surgical admission (aOR 1.22, 95%CI 1.13–1.32, p < 0.001) were significantly associated with a high alarm rate. Our study suggests that patient-specific alarm management should be integrated in the clinical routine of ICUs. To reduce the overall alarm load, particular attention regarding alarm management should be paid to patients with invasive blood pressure monitoring, invasive mechanical ventilation, heart failure, chronic renal failure, hypertension, high RASS or scheduled surgical admission since they are more likely to have a high contribution to noise pollution, alarm fatigue and hence compromised patient safety in ICUs.
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spelling pubmed-97581242022-12-18 The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study Sinno, Zeena-Carola Shay, Denys Kruppa, Jochen Klopfenstein, Sophie A.I. Giesa, Niklas Flint, Anne Rike Herren, Patrick Scheibe, Franziska Spies, Claudia Hinrichs, Carl Winter, Axel Balzer, Felix Poncette, Akira-Sebastian Sci Rep Article Intensive care units (ICU) are often overflooded with alarms from monitoring devices which constitutes a hazard to both staff and patients. To date, the suggested solutions to excessive monitoring alarms have remained on a research level. We aimed to identify patient characteristics that affect the ICU alarm rate with the goal of proposing a straightforward solution that can easily be implemented in ICUs. Alarm logs from eight adult ICUs of a tertiary care university-hospital in Berlin, Germany were retrospectively collected between September 2019 and March 2021. Adult patients admitted to the ICU with at least 24 h of continuous alarm logs were included in the study. The sum of alarms per patient per day was calculated. The median was 119. A total of 26,890 observations from 3205 patients were included. 23 variables were extracted from patients' electronic health records (EHR) and a multivariable logistic regression was performed to evaluate the association of patient characteristics and alarm rates. Invasive blood pressure monitoring (adjusted odds ratio (aOR) 4.68, 95%CI 4.15–5.29, p < 0.001), invasive mechanical ventilation (aOR 1.24, 95%CI 1.16–1.32, p < 0.001), heart failure (aOR 1.26, 95%CI 1.19–1.35, p < 0.001), chronic renal failure (aOR 1.18, 95%CI 1.10–1.27, p < 0.001), hypertension (aOR 1.19, 95%CI 1.13–1.26, p < 0.001), high RASS (aOR 1.22, 95%CI 1.18–1.25, p < 0.001) and scheduled surgical admission (aOR 1.22, 95%CI 1.13–1.32, p < 0.001) were significantly associated with a high alarm rate. Our study suggests that patient-specific alarm management should be integrated in the clinical routine of ICUs. To reduce the overall alarm load, particular attention regarding alarm management should be paid to patients with invasive blood pressure monitoring, invasive mechanical ventilation, heart failure, chronic renal failure, hypertension, high RASS or scheduled surgical admission since they are more likely to have a high contribution to noise pollution, alarm fatigue and hence compromised patient safety in ICUs. Nature Publishing Group UK 2022-12-16 /pmc/articles/PMC9758124/ /pubmed/36526892 http://dx.doi.org/10.1038/s41598-022-26261-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sinno, Zeena-Carola
Shay, Denys
Kruppa, Jochen
Klopfenstein, Sophie A.I.
Giesa, Niklas
Flint, Anne Rike
Herren, Patrick
Scheibe, Franziska
Spies, Claudia
Hinrichs, Carl
Winter, Axel
Balzer, Felix
Poncette, Akira-Sebastian
The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title_full The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title_fullStr The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title_full_unstemmed The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title_short The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
title_sort influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758124/
https://www.ncbi.nlm.nih.gov/pubmed/36526892
http://dx.doi.org/10.1038/s41598-022-26261-4
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