Evidence map›Paper›PMID 33439144›Full record

ArticleJournal of medical Internet research2021

Application of In-Home Monitoring Data to Transition Decisions in Continuing Care Retirement Communities: Usability Study.

Katherine Wild, Nicole Sharma, Nora Mattek, Jason Karlawish, Thomas Riley, Jeffrey Kaye

Registry-linked trialAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02566239 (Ambient Independence Measures for Guiding Care Transitions), which is not on this map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02566239 nacompletednot on this map

Ambient Independence Measures for Guiding Care Transitions

TypeinterventionalSponsorOregon Health and Science UniversityRan2014 to 2019Enrolled96ConditionsAgingArmsShare activity data with care team
3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Katherine Wild *Department of Neurology, Oregon Center for Aging and Technology, Oregon Health and Science University, Portland, OR, United States.ORCID 0000-0002-6749-9729
Nicole SharmaDepartment of Neurology, Oregon Center for Aging and Technology, Oregon Health and Science University, Portland, OR, United States.ORCID 0000-0003-2794-3271
Nora MattekDepartment of Neurology, Oregon Center for Aging and Technology, Oregon Health and Science University, Portland, OR, United States.ORCID 0000-0003-2623-1969
Jason KarlawishDepartment of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-6880-2865
Thomas RileyDepartment of Neurology, Oregon Center for Aging and Technology, Oregon Health and Science University, Portland, OR, United States.ORCID 0000-0001-8662-4428
Jeffrey KayeDepartment of Neurology, Oregon Center for Aging and Technology, Oregon Health and Science University, Portland, OR, United States.ORCID 0000-0002-9971-3478

Funding

Research Education ComponentP30AG066518 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI Zachary Beattie · 2020 to 2026
$28.6M
NIA NIH HHS P30 AG066518
6 · The paper itself

Abstract

backgroundContinuous in-home monitoring of older adults can provide rich and sensitive data capturing subtle behavioral and cognitive changes. Our previous work has identified multiple metrics that describe meaningful trends in daily activities over time. The continuous, multidomain nature of this technology may also serve to inform caregivers of the need for higher levels of care to maintain the health and safety of at-risk older adults. Accordingly, care decisions can be based on objective, systematically assessed real-time data.

objectiveThis study deployed a suite of in-home monitoring technologies to detect changing levels of care needs in residents of independent living units in 7 retirement communities and to assess the efficacy of computer-based tools in informing decisions regarding care transitions.

methodsContinuous activity data were presented via an interactive, web-based tool to the staff identified in each facility who were involved in decisions regarding transitions in care among residents. Comparisons were planned between outcomes for residents whose data were shared and those whose data were not made available to the staff. Staff use of the data dashboard was monitored throughout the study, and exit interviews with the staff were conducted to explicate staff interaction with the data platform. Residents were sent weekly self-report questionnaires to document any health- or care-related changes.

resultsDuring the study period, 30 of the 95 residents (32%) reported at least one incidence of new or increased provision of care; 6 residents made a permanent move to a higher level of care within their communities. Despite initial enthusiasm and an iterative process of refinement of measures and modes of data presentation based on staff input, actual inspection and therefore the use of resident data were well below expectation. In total, 11 of the 25 staff participants (44%) logged in to the activity dashboard throughout the study. Survey data and in-depth interviews provided insight into the mismatch between intended and actual use.

conclusionsMost continuous in-home monitoring technology acceptance models focus on perceived usefulness and ease of use and equate the intent to use technology with actual use. Our experience suggests otherwise. We found that multiple intervening variables exist between perceived usefulness, intent to use, and actual use. Ethical, institutional, and social factors are considered in their roles as determinants of use.

Indexed as

AgedFemaleHome Care ServicesHousing for the ElderlyHumansMaleRetirementSurveys and Questionnairescare transitionremote sensing technologytechnology

Identifiers

PMID33439144
PMCPMC7840292

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.