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Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset
The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation f...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9854741/ https://www.ncbi.nlm.nih.gov/pubmed/36671610 http://dx.doi.org/10.3390/bioengineering10010037 |
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author | Zahradka, Nicole Geoghan, Sophie Watson, Hope Goldberg, Eli Wolfberg, Adam Wilkes, Matt |
author_facet | Zahradka, Nicole Geoghan, Sophie Watson, Hope Goldberg, Eli Wolfberg, Adam Wilkes, Matt |
author_sort | Zahradka, Nicole |
collection | PubMed |
description | The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation frequency and alarm settings on alarms in a real-world dataset. Vital signs were collected from 76 patients admitted to healthcare at home programs using the Current Health (CH) platform; its wearable continuously measured respiratory rate (RR), pulse rate (PR), and oxygen saturation (SpO(2)). Total alarms, alarm rate, patient rate, and detection time were calculated for three alarm rulesets to detect changes in SpO(2), PR, and RR under four vital sign observation frequencies and four window sizes for the alarm algorithms’ median filter. Total alarms ranged from 65 to 3113. The alarm rate and early detection increased with the observation frequency for all alarm rulesets. Median filter windows reduced alarms triggered by normal fluctuations in vital signs without compromising the granularity of time between assessments. Frequent assessments enabled with continuous monitoring support early intervention but need to pair with settings that balance sensitivity, specificity, clinical risk, and provider capacity to respond when a patient is home to minimize clinician burden. |
format | Online Article Text |
id | pubmed-9854741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98547412023-01-21 Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset Zahradka, Nicole Geoghan, Sophie Watson, Hope Goldberg, Eli Wolfberg, Adam Wilkes, Matt Bioengineering (Basel) Article The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation frequency and alarm settings on alarms in a real-world dataset. Vital signs were collected from 76 patients admitted to healthcare at home programs using the Current Health (CH) platform; its wearable continuously measured respiratory rate (RR), pulse rate (PR), and oxygen saturation (SpO(2)). Total alarms, alarm rate, patient rate, and detection time were calculated for three alarm rulesets to detect changes in SpO(2), PR, and RR under four vital sign observation frequencies and four window sizes for the alarm algorithms’ median filter. Total alarms ranged from 65 to 3113. The alarm rate and early detection increased with the observation frequency for all alarm rulesets. Median filter windows reduced alarms triggered by normal fluctuations in vital signs without compromising the granularity of time between assessments. Frequent assessments enabled with continuous monitoring support early intervention but need to pair with settings that balance sensitivity, specificity, clinical risk, and provider capacity to respond when a patient is home to minimize clinician burden. MDPI 2022-12-28 /pmc/articles/PMC9854741/ /pubmed/36671610 http://dx.doi.org/10.3390/bioengineering10010037 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zahradka, Nicole Geoghan, Sophie Watson, Hope Goldberg, Eli Wolfberg, Adam Wilkes, Matt Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title | Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title_full | Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title_fullStr | Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title_full_unstemmed | Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title_short | Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset |
title_sort | assessment of remote vital sign monitoring and alarms in a real-world healthcare at home dataset |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9854741/ https://www.ncbi.nlm.nih.gov/pubmed/36671610 http://dx.doi.org/10.3390/bioengineering10010037 |
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