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Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals
BACKGROUND: The Ambient Intelligent Geriatric Management (AmbIGeM) system augments best practice and involves a novel wearable sensor (accelerometer and gyroscope) worn by patients where the data captured by the sensor are interpreted by algorithms to trigger alerts on clinician handheld mobile devi...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751806/ https://www.ncbi.nlm.nih.gov/pubmed/34153102 http://dx.doi.org/10.1093/gerona/glab174 |
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author | Visvanathan, Renuka Ranasinghe, Damith C Lange, Kylie Wilson, Anne Dollard, Joanne Boyle, Eileen Jones, Katherine Chesser, Michael Ingram, Katharine Hoskins, Stephen Pham, Clarabelle Karnon, Jonathan Hill, Keith D |
author_facet | Visvanathan, Renuka Ranasinghe, Damith C Lange, Kylie Wilson, Anne Dollard, Joanne Boyle, Eileen Jones, Katherine Chesser, Michael Ingram, Katharine Hoskins, Stephen Pham, Clarabelle Karnon, Jonathan Hill, Keith D |
author_sort | Visvanathan, Renuka |
collection | PubMed |
description | BACKGROUND: The Ambient Intelligent Geriatric Management (AmbIGeM) system augments best practice and involves a novel wearable sensor (accelerometer and gyroscope) worn by patients where the data captured by the sensor are interpreted by algorithms to trigger alerts on clinician handheld mobile devices when risk movements are detected. METHODS: A 3-cluster stepped-wedge pragmatic trial investigating the effect on the primary outcome of falls rate and secondary outcome of injurious fall and proportion of fallers. Three wards across 2 states were included. Patients aged ≥65 years were eligible. Patients requiring palliative care were excluded. The trial was registered with the Australia and New Zealand Clinical Trials registry, number 12617000981325. RESULTS: A total of 4924 older patients were admitted to the study wards with 1076 excluded and 3240 (1995 control, 1245 intervention) enrolled. The median proportion of study duration with valid readings per patient was 49% ((interquartile range [IQR] 25%-67%)). There was no significant difference between intervention and control relating to the falls rate (adjusted rate ratio = 1.41, 95% confidence interval [0.85, 2.34]; p = .192), proportion of fallers (odds ratio = 1.54, 95% confidence interval [0.91, 2.61]; p = .105), and injurious falls rate (adjusted rate ratio = 0.90, 95% confidence interval [0.38, 2.14]; p = .807). In a post hoc analysis, falls and injurious falls rate were reduced in the Geriatric Evaluation and Management Unit wards when the intervention period was compared to the control period. CONCLUSIONS: The AmbIGeM system did not reduce the rate of falls, rate of injurious falls, or proportion of fallers. There remains a case for further exploration and refinement of this technology given the post hoc analysis findings with the Geriatric Evaluation and Management Unit wards. Clinical Trials Registration Number: 12617000981325 |
format | Online Article Text |
id | pubmed-8751806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-87518062022-01-12 Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals Visvanathan, Renuka Ranasinghe, Damith C Lange, Kylie Wilson, Anne Dollard, Joanne Boyle, Eileen Jones, Katherine Chesser, Michael Ingram, Katharine Hoskins, Stephen Pham, Clarabelle Karnon, Jonathan Hill, Keith D J Gerontol A Biol Sci Med Sci THE JOURNAL OF GERONTOLOGY: Medical Sciences BACKGROUND: The Ambient Intelligent Geriatric Management (AmbIGeM) system augments best practice and involves a novel wearable sensor (accelerometer and gyroscope) worn by patients where the data captured by the sensor are interpreted by algorithms to trigger alerts on clinician handheld mobile devices when risk movements are detected. METHODS: A 3-cluster stepped-wedge pragmatic trial investigating the effect on the primary outcome of falls rate and secondary outcome of injurious fall and proportion of fallers. Three wards across 2 states were included. Patients aged ≥65 years were eligible. Patients requiring palliative care were excluded. The trial was registered with the Australia and New Zealand Clinical Trials registry, number 12617000981325. RESULTS: A total of 4924 older patients were admitted to the study wards with 1076 excluded and 3240 (1995 control, 1245 intervention) enrolled. The median proportion of study duration with valid readings per patient was 49% ((interquartile range [IQR] 25%-67%)). There was no significant difference between intervention and control relating to the falls rate (adjusted rate ratio = 1.41, 95% confidence interval [0.85, 2.34]; p = .192), proportion of fallers (odds ratio = 1.54, 95% confidence interval [0.91, 2.61]; p = .105), and injurious falls rate (adjusted rate ratio = 0.90, 95% confidence interval [0.38, 2.14]; p = .807). In a post hoc analysis, falls and injurious falls rate were reduced in the Geriatric Evaluation and Management Unit wards when the intervention period was compared to the control period. CONCLUSIONS: The AmbIGeM system did not reduce the rate of falls, rate of injurious falls, or proportion of fallers. There remains a case for further exploration and refinement of this technology given the post hoc analysis findings with the Geriatric Evaluation and Management Unit wards. Clinical Trials Registration Number: 12617000981325 Oxford University Press 2021-06-21 /pmc/articles/PMC8751806/ /pubmed/34153102 http://dx.doi.org/10.1093/gerona/glab174 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | THE JOURNAL OF GERONTOLOGY: Medical Sciences Visvanathan, Renuka Ranasinghe, Damith C Lange, Kylie Wilson, Anne Dollard, Joanne Boyle, Eileen Jones, Katherine Chesser, Michael Ingram, Katharine Hoskins, Stephen Pham, Clarabelle Karnon, Jonathan Hill, Keith D Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title | Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title_full | Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title_fullStr | Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title_full_unstemmed | Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title_short | Effectiveness of the Wearable Sensor-based Ambient Intelligent Geriatric Management (AmbIGeM) System in Preventing Falls in Older People in Hospitals |
title_sort | effectiveness of the wearable sensor-based ambient intelligent geriatric management (ambigem) system in preventing falls in older people in hospitals |
topic | THE JOURNAL OF GERONTOLOGY: Medical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751806/ https://www.ncbi.nlm.nih.gov/pubmed/34153102 http://dx.doi.org/10.1093/gerona/glab174 |
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