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Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video

To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients. DESIGN: Prospective, observational study. SETTING: Medical ICU...

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Autores principales: Fazio, Sarina, Doroy, Amy, Da Marto, Natalie, Taylor, Sandra, Anderson, Nicholas, Young, Heather M., Adams, Jason Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188433/
https://www.ncbi.nlm.nih.gov/pubmed/32426733
http://dx.doi.org/10.1097/CCE.0000000000000091
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author Fazio, Sarina
Doroy, Amy
Da Marto, Natalie
Taylor, Sandra
Anderson, Nicholas
Young, Heather M.
Adams, Jason Y.
author_facet Fazio, Sarina
Doroy, Amy
Da Marto, Natalie
Taylor, Sandra
Anderson, Nicholas
Young, Heather M.
Adams, Jason Y.
author_sort Fazio, Sarina
collection PubMed
description To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients. DESIGN: Prospective, observational study. SETTING: Medical ICU at an academic hospital. PATIENTS: Adult ICU patients (n = 30) were each continuously monitored over a median of 24.4 hours, yielding 711.5 hours of video, electronic health record, and sensor data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Electronic health record documentation estimated ambulation (intraclass correlation coefficient, 0.89; 95% CI, 0.78–0.95), sitting out-of-bed (intraclass correlation coefficient, 0.85; 95% CI, 0.72–0.93), and turning events (intraclass correlation coefficient, 0.87; 95% CI, 0.75–0.94) with excellent agreement but underestimated the number of standing, transferring, and pregait activities performed per patient. The accelerometer-based sensor had excellent agreement with video annotation for estimating duration of time spent supine (intraclass correlation coefficient, 0.99; CI, 0.97–0.99) and sitting/standing upright (intraclass correlation coefficient, 0.92; CI, 0.82–0.96) but overestimated ambulation time. CONCLUSIONS: Our results show that electronic health record documentation and sensor-based technologies accurately capture distinct but complimentary metrics for ICU mobility measurement. Innovations in artifact detection, standardization of clinically relevant mobility definitions, and electronic health record documentation enhancements may enable further use of these technologies to drive critical care research and technology leveraged data-driven ICU models of care.
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spelling pubmed-71884332020-05-19 Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video Fazio, Sarina Doroy, Amy Da Marto, Natalie Taylor, Sandra Anderson, Nicholas Young, Heather M. Adams, Jason Y. Crit Care Explor Methodology To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients. DESIGN: Prospective, observational study. SETTING: Medical ICU at an academic hospital. PATIENTS: Adult ICU patients (n = 30) were each continuously monitored over a median of 24.4 hours, yielding 711.5 hours of video, electronic health record, and sensor data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Electronic health record documentation estimated ambulation (intraclass correlation coefficient, 0.89; 95% CI, 0.78–0.95), sitting out-of-bed (intraclass correlation coefficient, 0.85; 95% CI, 0.72–0.93), and turning events (intraclass correlation coefficient, 0.87; 95% CI, 0.75–0.94) with excellent agreement but underestimated the number of standing, transferring, and pregait activities performed per patient. The accelerometer-based sensor had excellent agreement with video annotation for estimating duration of time spent supine (intraclass correlation coefficient, 0.99; CI, 0.97–0.99) and sitting/standing upright (intraclass correlation coefficient, 0.92; CI, 0.82–0.96) but overestimated ambulation time. CONCLUSIONS: Our results show that electronic health record documentation and sensor-based technologies accurately capture distinct but complimentary metrics for ICU mobility measurement. Innovations in artifact detection, standardization of clinically relevant mobility definitions, and electronic health record documentation enhancements may enable further use of these technologies to drive critical care research and technology leveraged data-driven ICU models of care. Wolters Kluwer Health 2020-04-29 /pmc/articles/PMC7188433/ /pubmed/32426733 http://dx.doi.org/10.1097/CCE.0000000000000091 Text en Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Methodology
Fazio, Sarina
Doroy, Amy
Da Marto, Natalie
Taylor, Sandra
Anderson, Nicholas
Young, Heather M.
Adams, Jason Y.
Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title_full Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title_fullStr Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title_full_unstemmed Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title_short Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video
title_sort quantifying mobility in the icu: comparison of electronic health record documentation and accelerometer-based sensors to clinician-annotated video
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188433/
https://www.ncbi.nlm.nih.gov/pubmed/32426733
http://dx.doi.org/10.1097/CCE.0000000000000091
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