Living safer and longer at home: the TIHM story
Living safer and longer at home: the TIHM story
This paper will present fndings and key lessons learnt from a UK randomised controlled trial that tested clinical (e.g. hospital admissions,quality of life, well being of people with dementia and their carers) and cost efectiveness of a complex combinatorial domiciliary Internet of Things(IoT) intervention developed with, and for, people with mild to moderate dementia. Its goal was to support people remaining at home, out of hospital and residential care. Technology Integrated Health Management(TIHM) for Dementia is one of seven NHS Test Bed innovations developed and funded by NHS England and Innovate UK to evaluate how cutting edge IoT technology can be used to improve the lives of those living with dementia.People with dementia and their carers were recruited to provide a sample of 204 dyads (intervention: 101 dyads; and control: 103 dyads). Real-time clinical and environmental data were collected over a 6-month period using technology devices and sensors installed in participants’ homes.Information was relayed daily to a dashboard-alert system (the ‘integrated view’), which was monitored 24 hours a day by the trained TIHM team.Alzheimer’s Society Dementia Navigators also provided support at homefor non-emergency episodes. Machine-learning algorithms provided actionable information and alerts (e.g. related to wandering, UTIs,hypertensive/hypotensive episodes; dehydration) that were managed in a collaboration between the monitoring team and participant dyad.The paper will present a synthesis of evaluation fndings (including clinical and cost efectiveness, user acceptance, clinical decision making and disease management practices). It will discuss the potential for developing a refned TIHM system supported by assistive technologies and machine-learning algorithms for early detection of personalised symptom change; declining health status; and for the deployment of preventative, rather than responsive, interventions to improve quality of dementia care.
60-61
Chrysanthaki, Theopisti
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Ream, Emma
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Parsons, Catherine
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Kieran, Egan
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Bridget, Jones
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Klepacz, Naomi
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Mark, Joy
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Gage, Heather
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Jordan, Jake
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Maguire, Roma
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Nilforooshan, Ramin
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Kenny, Mark
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Barnaghi, Payam
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Dixon, Julian
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Rostill, Helen
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31 October 2018
Chrysanthaki, Theopisti
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Ream, Emma
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Parsons, Catherine
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Kieran, Egan
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Bridget, Jones
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Klepacz, Naomi
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Mark, Joy
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Gage, Heather
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Jordan, Jake
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Maguire, Roma
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Nilforooshan, Ramin
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Kenny, Mark
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Barnaghi, Payam
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Dixon, Julian
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Rostill, Helen
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Chrysanthaki, Theopisti, Ream, Emma, Parsons, Catherine, Kieran, Egan, Bridget, Jones, Klepacz, Naomi, Mark, Joy, Gage, Heather, Jordan, Jake, Maguire, Roma, Nilforooshan, Ramin, Kenny, Mark, Barnaghi, Payam, Dixon, Julian and Rostill, Helen
(2018)
Living safer and longer at home: the TIHM story.
The 28th Alzheimer Europe Conference (#28AEC): “Making dementia a European priority”, , Barcelona, Spain.
29 - 31 Oct 2018.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
This paper will present fndings and key lessons learnt from a UK randomised controlled trial that tested clinical (e.g. hospital admissions,quality of life, well being of people with dementia and their carers) and cost efectiveness of a complex combinatorial domiciliary Internet of Things(IoT) intervention developed with, and for, people with mild to moderate dementia. Its goal was to support people remaining at home, out of hospital and residential care. Technology Integrated Health Management(TIHM) for Dementia is one of seven NHS Test Bed innovations developed and funded by NHS England and Innovate UK to evaluate how cutting edge IoT technology can be used to improve the lives of those living with dementia.People with dementia and their carers were recruited to provide a sample of 204 dyads (intervention: 101 dyads; and control: 103 dyads). Real-time clinical and environmental data were collected over a 6-month period using technology devices and sensors installed in participants’ homes.Information was relayed daily to a dashboard-alert system (the ‘integrated view’), which was monitored 24 hours a day by the trained TIHM team.Alzheimer’s Society Dementia Navigators also provided support at homefor non-emergency episodes. Machine-learning algorithms provided actionable information and alerts (e.g. related to wandering, UTIs,hypertensive/hypotensive episodes; dehydration) that were managed in a collaboration between the monitoring team and participant dyad.The paper will present a synthesis of evaluation fndings (including clinical and cost efectiveness, user acceptance, clinical decision making and disease management practices). It will discuss the potential for developing a refned TIHM system supported by assistive technologies and machine-learning algorithms for early detection of personalised symptom change; declining health status; and for the deployment of preventative, rather than responsive, interventions to improve quality of dementia care.
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Published date: 31 October 2018
Venue - Dates:
The 28th Alzheimer Europe Conference (#28AEC): “Making dementia a European priority”, , Barcelona, Spain, 2018-10-29 - 2018-10-31
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Local EPrints ID: 483625
URI: http://eprints.soton.ac.uk/id/eprint/483625
PURE UUID: 2a761f9d-68d4-44ff-a5d7-91090564ccde
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Date deposited: 02 Nov 2023 17:55
Last modified: 18 Mar 2024 04:07
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Contributors
Author:
Theopisti Chrysanthaki
Author:
Emma Ream
Author:
Catherine Parsons
Author:
Egan Kieran
Author:
Jones Bridget
Author:
Naomi Klepacz
Author:
Joy Mark
Author:
Heather Gage
Author:
Jake Jordan
Author:
Roma Maguire
Author:
Ramin Nilforooshan
Author:
Mark Kenny
Author:
Payam Barnaghi
Author:
Julian Dixon
Author:
Helen Rostill
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