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Using in-Home Monitoring Technology ...
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Yefimova, Maria.
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Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults./
Author:
Yefimova, Maria.
Description:
129 p.
Notes:
Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Contained By:
Dissertation Abstracts International77-10B(E).
Subject:
Nursing. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10118815
ISBN:
9781339801445
Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.
Yefimova, Maria.
Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.
- 129 p.
Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Thesis (Ph.D.)--University of California, Los Angeles, 2016.
The boom of in-home monitoring technology offers unprecedented information about an individual's interaction with the environment. A variety of low cost sensors can continuously and unobtrusively collect information about activities in the living space. Capturing early changes in the daily routines of vulnerable older adults residing in these "smart homes" may allow clinicians to predict and prevent negative health consequences through timely intervention. However, the current state of science is hampered by the lack of theoretically driven approaches to analyze sensor data in relation to clinically meaningful health outcomes. The aims of the study are 1) to characterize an older adult's daily routine, as captured with smart home sensors, 2) to assess if deviations from it are indicative of changes in their health trajectory, such as falls, ER visits or unplanned hospitalizations, and 3) identify between person factors that affect the characteristics of the daily routine. It used previously collected data from 10 residents of TigerPlace, a unique retirement facility that evaluates health technology affiliated with University of Missouri, Columbia. Older adults live in apartments equipped with network of motion, depth and bed sensors that unobtrusively collect information about daily activity of its resident. Thirty months of continuous sensor data were analyzed in the context of bi-annual clinical assessments and nursing notes extracted from the electronic health record. A retrospective multiple case study approach is guided by the conceptual model developed for this study that is grounded in nursing and gerontological literature. Changes in the temporality and frequency of daily activity were found for common geriatric symptoms, such as urinary symptoms and confusion. Seasonal and weekly effect was evident across participants in the duration of time spent in various areas of the apartment. Participants varied in their baseline daily routines, but for the majority of symptoms there were prodromal changes in at home activity that was detected with sensors. As the cost of technology adoption decreases, nurses can use these innovative tools to coordinate care and intervene early to prevent or mitigate the functional decline associated with vulnerable older adults.
ISBN: 9781339801445Subjects--Topical Terms:
528444
Nursing.
Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.
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Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.
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Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
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Thesis (Ph.D.)--University of California, Los Angeles, 2016.
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The boom of in-home monitoring technology offers unprecedented information about an individual's interaction with the environment. A variety of low cost sensors can continuously and unobtrusively collect information about activities in the living space. Capturing early changes in the daily routines of vulnerable older adults residing in these "smart homes" may allow clinicians to predict and prevent negative health consequences through timely intervention. However, the current state of science is hampered by the lack of theoretically driven approaches to analyze sensor data in relation to clinically meaningful health outcomes. The aims of the study are 1) to characterize an older adult's daily routine, as captured with smart home sensors, 2) to assess if deviations from it are indicative of changes in their health trajectory, such as falls, ER visits or unplanned hospitalizations, and 3) identify between person factors that affect the characteristics of the daily routine. It used previously collected data from 10 residents of TigerPlace, a unique retirement facility that evaluates health technology affiliated with University of Missouri, Columbia. Older adults live in apartments equipped with network of motion, depth and bed sensors that unobtrusively collect information about daily activity of its resident. Thirty months of continuous sensor data were analyzed in the context of bi-annual clinical assessments and nursing notes extracted from the electronic health record. A retrospective multiple case study approach is guided by the conceptual model developed for this study that is grounded in nursing and gerontological literature. Changes in the temporality and frequency of daily activity were found for common geriatric symptoms, such as urinary symptoms and confusion. Seasonal and weekly effect was evident across participants in the duration of time spent in various areas of the apartment. Participants varied in their baseline daily routines, but for the majority of symptoms there were prodromal changes in at home activity that was detected with sensors. As the cost of technology adoption decreases, nurses can use these innovative tools to coordinate care and intervene early to prevent or mitigate the functional decline associated with vulnerable older adults.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10118815
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