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Interventions to optimise prescribing for older people in care homes

Overview of attention for article published in Cochrane database of systematic reviews, February 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
67 tweeters
facebook
6 Facebook pages
wikipedia
1 Wikipedia page

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
111 Mendeley
citeulike
1 CiteULike
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Title
Interventions to optimise prescribing for older people in care homes
Published in
Cochrane database of systematic reviews, February 2016
DOI 10.1002/14651858.cd009095.pub3
Pubmed ID
Authors

David P Alldred, Mary-Claire Kennedy, Carmel Hughes, Timothy F Chen, Paul Miller

Abstract

There is a substantial body of evidence that prescribing for care home residents is suboptimal and requires improvement. Consequently, there is a need to identify effective interventions to optimise prescribing and resident outcomes in this context. This is an update of a previously published review (Alldred 2013). The objective of the review was to determine the effect of interventions to optimise overall prescribing for older people living in care homes. For this update, we searched the Cochrane Central Register of Controlled Trials (CENTRAL) (including the Cochrane Effective Practice and Organisation of Care (EPOC) Specialised Register), MEDLINE, EMBASE and CINAHL to May 2015. We also searched clinical trial registries for relevant studies. We included randomised controlled trials evaluating interventions aimed at optimising prescribing for older people (aged 65 years or older) living in institutionalised care facilities. Studies were included if they measured one or more of the following primary outcomes: adverse drug events; hospital admissions; mortality; or secondary outcomes, quality of life (using validated instrument); medication-related problems; medication appropriateness (using validated instrument); medicine costs. Two authors independently screened titles and abstracts, assessed studies for eligibility, assessed risk of bias and extracted data. We presented a narrative summary of results. The 12 included studies involved 10,953 residents in 355 (range 1 to 85) care homes in ten countries. Nine studies were cluster-randomised controlled trials and three studies were patient-randomised controlled trials. The interventions evaluated were diverse and often multifaceted. Medication review was a component of ten studies. Four studies involved multidisciplinary case-conferencing, five studies involved an educational element for health and care professionals and one study evaluated the use of clinical decision support technology. We did not combine the results in a meta-analysis due to heterogeneity across studies. Interventions to optimise prescribing may lead to fewer days in hospital (one study out of eight; low certainty evidence), a slower decline in health-related quality of life (one study out of two; low certainty evidence), the identification and resolution of medication-related problems (seven studies; low certainty evidence), and may lead to improved medication appropriateness (five studies out of five studies; low certainty evidence). We are uncertain whether the intervention improves/reduces medicine costs (five studies; very low certainty evidence) and it may make little or no difference on adverse drug events (two studies; low certainty evidence) or mortality (six studies; low certainty evidence). The risk of bias across studies was heterogeneous. We could not draw robust conclusions from the evidence due to variability in design, interventions, outcomes and results. The interventions implemented in the studies in this review led to the identification and resolution of medication-related problems and improvements in medication appropriateness, however evidence of a consistent effect on resident-related outcomes was not found. There is a need for high-quality cluster-randomised controlled trials testing clinical decision support systems and multidisciplinary interventions that measure well-defined, important resident-related outcomes.

Twitter Demographics

The data shown below were collected from the profiles of 67 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 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Ireland 1 <1%
Canada 1 <1%
Unknown 108 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 20%
Researcher 22 20%
Student > Ph. D. Student 13 12%
Unspecified 11 10%
Student > Doctoral Student 11 10%
Other 32 29%
Readers by discipline Count As %
Medicine and Dentistry 30 27%
Pharmacology, Toxicology and Pharmaceutical Science 23 21%
Nursing and Health Professions 21 19%
Unspecified 14 13%
Social Sciences 8 7%
Other 15 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 01 October 2018.
All research outputs
#338,267
of 12,531,547 outputs
Outputs from Cochrane database of systematic reviews
#1,054
of 10,345 outputs
Outputs of similar age
#13,046
of 335,210 outputs
Outputs of similar age from Cochrane database of systematic reviews
#34
of 186 outputs
Altmetric has tracked 12,531,547 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 10,345 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.2. This one has done well, scoring higher than 89% 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 335,210 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 96% of its contemporaries.
We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.