Developing a sensor-based mobile application for in-home frailty assessment: a qualitative study.


Journal

BMC geriatrics
ISSN: 1471-2318
Titre abrégé: BMC Geriatr
Pays: England
ID NLM: 100968548

Informations de publication

Date de publication:
04 02 2021
Historique:
received: 05 06 2020
accepted: 20 01 2021
entrez: 5 2 2021
pubmed: 6 2 2021
medline: 27 4 2021
Statut: epublish

Résumé

Frailty syndrome disproportionately affects older people, including 15% of non-nursing home population, and is known to be a strong predictor of poor health outcomes. There is a growing interest in incorporating frailty assessment into research and clinical practice, which may provide an opportunity to improve in home frailty assessment and improve doctor patient communication. We conducted focus groups discussions to solicit input from older adult care recipients (non-frail, pre-frail, and frail), their informal caregivers, and medical providers about their preferences to tailor a mobile app to measure frailty in the home using sensor based technologies. Focus groups were recorded, transcribed, and analyzed thematically. We identified three major themes: 1) perspectives of frailty; 2) perceptions of home based sensors; and 3) data management concerns. These relate to the participants' insight, attitudes and concerns about having sensor-based technology to measure frailty in the home. Our qualitative findings indicate that knowing frailty status is important and useful and would allow older adults to remain independent longer. Participants also noted concerns with data management and the hope that this technology would not replace in-person visits with their healthcare provider. This study found that study participants of each frailty status expressed high interest and acceptance of sensor-based technologies. Based on the qualitative findings of this study, sensor-based technologies show promise for frailty assessment of older adults with care needs. The main concerns identified related to the volume of data collected and strategies for responsible and secure transfer, reporting, and distillation of data into useful and timely care information. Sensor-based technologies should be piloted for feasibility and utility. This will inform the larger goal of helping older adults to maintain independence while tracking potential health declines, especially among the most vulnerable, for early detection and intervention.

Sections du résumé

BACKGROUND
Frailty syndrome disproportionately affects older people, including 15% of non-nursing home population, and is known to be a strong predictor of poor health outcomes. There is a growing interest in incorporating frailty assessment into research and clinical practice, which may provide an opportunity to improve in home frailty assessment and improve doctor patient communication.
METHODS
We conducted focus groups discussions to solicit input from older adult care recipients (non-frail, pre-frail, and frail), their informal caregivers, and medical providers about their preferences to tailor a mobile app to measure frailty in the home using sensor based technologies. Focus groups were recorded, transcribed, and analyzed thematically.
RESULTS
We identified three major themes: 1) perspectives of frailty; 2) perceptions of home based sensors; and 3) data management concerns. These relate to the participants' insight, attitudes and concerns about having sensor-based technology to measure frailty in the home. Our qualitative findings indicate that knowing frailty status is important and useful and would allow older adults to remain independent longer. Participants also noted concerns with data management and the hope that this technology would not replace in-person visits with their healthcare provider.
CONCLUSIONS
This study found that study participants of each frailty status expressed high interest and acceptance of sensor-based technologies. Based on the qualitative findings of this study, sensor-based technologies show promise for frailty assessment of older adults with care needs. The main concerns identified related to the volume of data collected and strategies for responsible and secure transfer, reporting, and distillation of data into useful and timely care information. Sensor-based technologies should be piloted for feasibility and utility. This will inform the larger goal of helping older adults to maintain independence while tracking potential health declines, especially among the most vulnerable, for early detection and intervention.

Identifiants

pubmed: 33541276
doi: 10.1186/s12877-021-02041-z
pii: 10.1186/s12877-021-02041-z
pmc: PMC7863502
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

101

Subventions

Organisme : NIA NIH HHS
ID : P30 AG021334
Pays : United States
Organisme : The Johns Hopkins Claude D. Pepper Older Americans Independence Center
ID : P30AG021334

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Auteurs

Marcela D Blinka (MD)

Center on Aging and Health, Johns Hopkins University, 2024 E. Monument Street, Suite 2-700, Baltimore, MD, 21205, USA. mblinka1@jhmi.edu.
Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. mblinka1@jhmi.edu.

Brian Buta (B)

Center on Aging and Health, Johns Hopkins University, 2024 E. Monument Street, Suite 2-700, Baltimore, MD, 21205, USA.
Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Kevin D Bader (KD)

The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.

Casey Hanley (C)

The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.

Nancy L Schoenborn (NL)

Center on Aging and Health, Johns Hopkins University, 2024 E. Monument Street, Suite 2-700, Baltimore, MD, 21205, USA.
Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Matthew McNabney (M)

Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Qian-Li Xue (QL)

Center on Aging and Health, Johns Hopkins University, 2024 E. Monument Street, Suite 2-700, Baltimore, MD, 21205, USA. qxue1@jhu.edu.
Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. qxue1@jhu.edu.

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Classifications MeSH