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Designing and Undertaking a Health Economics Study of Digital Health Interventions

Overview of attention for article published in American Journal of Preventive Medicine, November 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
20 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
130 Mendeley
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Title
Designing and Undertaking a Health Economics Study of Digital Health Interventions
Published in
American Journal of Preventive Medicine, November 2016
DOI 10.1016/j.amepre.2016.05.007
Pubmed ID
Authors

Paul McNamee, Elizabeth Murray, Michael P. Kelly, Laura Bojke, Jim Chilcott, Alastair Fischer, Robert West, Lucy Yardley

Abstract

This paper introduces and discusses key issues in the economic evaluation of digital health interventions. The purpose is to stimulate debate so that existing economic techniques may be refined or new methods developed. The paper does not seek to provide definitive guidance on appropriate methods of economic analysis for digital health interventions. This paper describes existing guides and analytic frameworks that have been suggested for the economic evaluation of healthcare interventions. Using selected examples of digital health interventions, it assesses how well existing guides and frameworks align to digital health interventions. It shows that digital health interventions may be best characterized as complex interventions in complex systems. Key features of complexity relate to intervention complexity, outcome complexity, and causal pathway complexity, with much of this driven by iterative intervention development over time and uncertainty regarding likely reach of the interventions among the relevant population. These characteristics imply that more-complex methods of economic evaluation are likely to be better able to capture fully the impact of the intervention on costs and benefits over the appropriate time horizon. This complexity includes wider measurement of costs and benefits, and a modeling framework that is able to capture dynamic interactions among the intervention, the population of interest, and the environment. The authors recommend that future research should develop and apply more-flexible modeling techniques to allow better prediction of the interdependency between interventions and important environmental influences.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
Portugal 1 <1%
United Kingdom 1 <1%
Norway 1 <1%
Unknown 126 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 23%
Student > Ph. D. Student 25 19%
Unspecified 18 14%
Student > Master 18 14%
Other 11 8%
Other 28 22%
Readers by discipline Count As %
Unspecified 30 23%
Medicine and Dentistry 22 17%
Social Sciences 15 12%
Computer Science 14 11%
Psychology 13 10%
Other 36 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 21 October 2017.
All research outputs
#1,023,789
of 13,073,777 outputs
Outputs from American Journal of Preventive Medicine
#914
of 3,344 outputs
Outputs of similar age
#35,900
of 287,585 outputs
Outputs of similar age from American Journal of Preventive Medicine
#34
of 93 outputs
Altmetric has tracked 13,073,777 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.9. This one has gotten more attention than average, scoring higher than 72% 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 287,585 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.