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Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals

OBJECTIVES: This study aimed to evaluate the effectiveness of using 1 to 4 mobile or fixed automated video monitoring systems (AVMSs) to decrease the risk of unattended bed exits (UBEs) as antecedents to unassisted falls among patients at high risk for falls and fall-related injuries in 15 small rur...

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Autores principales: Jones, Katherine J., Haynatzki, Gleb, Sabalka, Lucas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612902/
https://www.ncbi.nlm.nih.gov/pubmed/33009181
http://dx.doi.org/10.1097/PTS.0000000000000789
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author Jones, Katherine J.
Haynatzki, Gleb
Sabalka, Lucas
author_facet Jones, Katherine J.
Haynatzki, Gleb
Sabalka, Lucas
author_sort Jones, Katherine J.
collection PubMed
description OBJECTIVES: This study aimed to evaluate the effectiveness of using 1 to 4 mobile or fixed automated video monitoring systems (AVMSs) to decrease the risk of unattended bed exits (UBEs) as antecedents to unassisted falls among patients at high risk for falls and fall-related injuries in 15 small rural hospitals. METHODS: We compared UBE rates and fall rates during baseline (5 months in which patient movement was recorded but nurses did not receive alerts) and intervention phases (2 months in which nurses received alerts). We determined lead time (seconds elapsed from the first alert because of patient movement until 3 seconds after an UBE) during baseline and positive predictive value and sensitivity during intervention. RESULTS: Age and fall risk were negatively associated with the baseline patient rate of UBEs/day. From baseline to intervention: in 9 hospitals primarily using mobile systems, UBEs/day decreased from 0.84 to 0.09 (89%); in 5 hospitals primarily using fixed systems, UBEs/day increased from 0.43 to 3.18 (649%) as patients at low risk for falls were observed safely exiting the bed; and among 13 hospitals with complete data, total falls/1000 admissions decreased from 8.83 to 5.53 (37%), and injurious falls/1000 admissions decreased from 2.52 to 0.55 (78%). The median lead time of the AVMS was 28.5 seconds, positive predictive value was nearly 60%, and sensitivity was 97.4%. CONCLUSIONS: Use of relatively few AVMSs may allow nurses to adaptively manage UBEs as antecedents to unassisted falls and fall-related injuries in small rural hospitals. Additional research is needed in larger hospitals to better understand the effectiveness of AVMSs.
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spelling pubmed-86129022021-11-29 Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals Jones, Katherine J. Haynatzki, Gleb Sabalka, Lucas J Patient Saf Original Studies OBJECTIVES: This study aimed to evaluate the effectiveness of using 1 to 4 mobile or fixed automated video monitoring systems (AVMSs) to decrease the risk of unattended bed exits (UBEs) as antecedents to unassisted falls among patients at high risk for falls and fall-related injuries in 15 small rural hospitals. METHODS: We compared UBE rates and fall rates during baseline (5 months in which patient movement was recorded but nurses did not receive alerts) and intervention phases (2 months in which nurses received alerts). We determined lead time (seconds elapsed from the first alert because of patient movement until 3 seconds after an UBE) during baseline and positive predictive value and sensitivity during intervention. RESULTS: Age and fall risk were negatively associated with the baseline patient rate of UBEs/day. From baseline to intervention: in 9 hospitals primarily using mobile systems, UBEs/day decreased from 0.84 to 0.09 (89%); in 5 hospitals primarily using fixed systems, UBEs/day increased from 0.43 to 3.18 (649%) as patients at low risk for falls were observed safely exiting the bed; and among 13 hospitals with complete data, total falls/1000 admissions decreased from 8.83 to 5.53 (37%), and injurious falls/1000 admissions decreased from 2.52 to 0.55 (78%). The median lead time of the AVMS was 28.5 seconds, positive predictive value was nearly 60%, and sensitivity was 97.4%. CONCLUSIONS: Use of relatively few AVMSs may allow nurses to adaptively manage UBEs as antecedents to unassisted falls and fall-related injuries in small rural hospitals. Additional research is needed in larger hospitals to better understand the effectiveness of AVMSs. Lippincott Williams & Wilkins 2021-12 2020-10-01 /pmc/articles/PMC8612902/ /pubmed/33009181 http://dx.doi.org/10.1097/PTS.0000000000000789 Text en Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/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) (https://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 Original Studies
Jones, Katherine J.
Haynatzki, Gleb
Sabalka, Lucas
Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title_full Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title_fullStr Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title_full_unstemmed Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title_short Evaluation of Automated Video Monitoring to Decrease the Risk of Unattended Bed Exits in Small Rural Hospitals
title_sort evaluation of automated video monitoring to decrease the risk of unattended bed exits in small rural hospitals
topic Original Studies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8612902/
https://www.ncbi.nlm.nih.gov/pubmed/33009181
http://dx.doi.org/10.1097/PTS.0000000000000789
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