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A community virtual ward model to support older persons with complex health care and social care needs

Overview of attention for article published in Clinical Interventions in Aging, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#29 of 1,269)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
53 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
31 Mendeley
Title
A community virtual ward model to support older persons with complex health care and social care needs
Published in
Clinical Interventions in Aging, June 2017
DOI 10.2147/cia.s130876
Pubmed ID
Authors

C Lewis, Z Moore, F Doyle, A Martin, D Patton, LE Nugent

Abstract

Globally the older population is increasing rapidly. As a result there is an increase in frail older persons living within the community, with increased risks of a hospital admission and higher mortality and morbidity rates. Due to complexity of care, health care professionals face challenges in providing effective case management and avoiding unplanned admissions to hospital. A community virtual ward (CVW) model was developed to assist health care professionals to support older persons at home during periods of illness and/or functional decline. A quantitative observational study was conducted to examine if a CVW model of care reduced unplanned hospital admissions and emergency department (ED) presentations in 54 patients over a 12-month period. The sign-rank test examined matched data on bed days, ED presentations, and unplanned hospital admissions pre- and post-CVW implementation. Other risk factors for admission to hospital were examined using the Mann-Whitney test pre-and post-CVW admission, including falls, living alone, and cognition. Correlations between hospital admission avoidances and unplanned hospital admissions and ED presentations were tested using Spearman's ρ test. There was a reduction in ED presentations post-CVW admission (P<0.001), and median unscheduled admissions were reduced (P=0.001). Those living alone had a lower number of ED presentations (median 0.5, interquartile range 0-1) prior to admission in comparison to those living with a caregiver, with no differences observed during admission to CVW. For those who experienced a fall during CVW admission, the odds ratio (OR) of requiring long-term care doubled for each extra fall (OR =2.24, 95% CI 1.11 to 4.52, P=0.025). Reduced cognition was associated with an increased risk of ED presentations (ρ=0.292, P<0.05) but not associated with increased risks of unplanned hospital admissions (ρ=0.09, P=0.546). There were no significant correlations seen between admission avoidance and the number of unplanned hospital admissions or ED presentations. Through an integrated approach to care, a CVW model in the care of older persons can reduce ED presentations and unplanned hospital admissions.

Twitter Demographics

The data shown below were collected from the profiles of 53 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 8 26%
Student > Bachelor 4 13%
Student > Ph. D. Student 4 13%
Student > Postgraduate 3 10%
Student > Master 3 10%
Other 9 29%
Readers by discipline Count As %
Unspecified 8 26%
Medicine and Dentistry 7 23%
Nursing and Health Professions 7 23%
Agricultural and Biological Sciences 2 6%
Psychology 1 3%
Other 6 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 41. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 January 2018.
All research outputs
#355,500
of 12,368,612 outputs
Outputs from Clinical Interventions in Aging
#29
of 1,269 outputs
Outputs of similar age
#15,898
of 267,018 outputs
Outputs of similar age from Clinical Interventions in Aging
#3
of 40 outputs
Altmetric has tracked 12,368,612 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,269 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,018 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.