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Multidisciplinary treatment for peripheral arterial occlusive disease and the role of eHealth and mHealth

Overview of attention for article published in Journal of Multidisciplinary Healthcare, October 2012
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Title
Multidisciplinary treatment for peripheral arterial occlusive disease and the role of eHealth and mHealth
Published in
Journal of Multidisciplinary Healthcare, October 2012
DOI 10.2147/jmdh.s35779
Pubmed ID
Authors

Hugo JP Fokkenrood, Gert-Jan Lauret, Marc RM Scheltinga, Cor Spreeuwenberg, Rob A de Bie, Joep AW Teijink

Abstract

Increasingly unaffordable health care costs are forcing care providers to develop economically viable and efficient health care plans. Currently, only a minority of all newly diagnosed peripheral arterial occlusive disease (PAOD) patients receive efficient and structured conservative treatment for their disease. The aim of this article is to introduce an innovative effective treatment model termed ClaudicatioNet. This concept was launched in The Netherlands as a means to combat treatment shortcomings and stimulate cohesion and collaboration between stakeholders. The overall goal of ClaudicatioNet is to stimulate quality and transparency of PAOD treatment by optimizing multidisciplinary health care chains on a national level. Improved quality is based on stimulating both a theoretical and practical knowledge base, while eHealth and mHealth technologies are used to create clear insights of provided care to enhance quality control management, in addition these technologies can be used to increase patient empowerment, thereby increasing efficacy of PAOD treatment. This online community consists of a web portal with public and personal information supplemented with a mobile application. By connecting to these tools, a social community is created where patients can meet and keep in touch with fellow patients, while useful information for supervising health care professionals is provided. The ClaudicatioNet concept will likely create more efficient and cost-effective PAOD treatment by improving the quality of supervised training programs, extending possibilities and stimulating patient empowerment by using eHealth and mHealth solutions. A free market principle is introduced by introducing transparency to provided care by using objective and subjective outcome parameters. Cost-effectiveness can be achieved using supervised training programs, which may substitute for or postpone expensive invasive vascular interventions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 1%
Unknown 79 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 20%
Researcher 12 15%
Student > Postgraduate 8 10%
Student > Doctoral Student 6 8%
Student > Bachelor 6 8%
Other 16 20%
Unknown 16 20%
Readers by discipline Count As %
Medicine and Dentistry 22 28%
Nursing and Health Professions 10 13%
Social Sciences 7 9%
Engineering 4 5%
Computer Science 3 4%
Other 19 24%
Unknown 15 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 October 2012.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Journal of Multidisciplinary Healthcare
#900
of 1,001 outputs
Outputs of similar age
#171,292
of 190,995 outputs
Outputs of similar age from Journal of Multidisciplinary Healthcare
#3
of 4 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,001 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 190,995 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.