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A systematic literature review of the key challenges for developing the structure of public health economic models

Overview of attention for article published in International Journal of Public Health, January 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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
32 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
57 Mendeley
citeulike
1 CiteULike
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Title
A systematic literature review of the key challenges for developing the structure of public health economic models
Published in
International Journal of Public Health, January 2016
DOI 10.1007/s00038-015-0775-7
Pubmed ID
Authors

Hazel Squires, James Chilcott, Ronald Akehurst, Jennifer Burr, Michael P. Kelly

Abstract

To identify the key methodological challenges for public health economic modelling and set an agenda for future research. An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review. Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified. Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.

Twitter Demographics

The data shown below were collected from the profiles of 32 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
South Africa 1 2%
Unknown 55 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Master 10 18%
Student > Ph. D. Student 9 16%
Lecturer > Senior Lecturer 4 7%
Student > Postgraduate 4 7%
Other 10 18%
Unknown 10 18%
Readers by discipline Count As %
Medicine and Dentistry 15 26%
Social Sciences 7 12%
Economics, Econometrics and Finance 6 11%
Nursing and Health Professions 4 7%
Decision Sciences 3 5%
Other 5 9%
Unknown 17 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 04 May 2017.
All research outputs
#1,082,174
of 15,798,970 outputs
Outputs from International Journal of Public Health
#120
of 1,161 outputs
Outputs of similar age
#29,457
of 372,148 outputs
Outputs of similar age from International Journal of Public Health
#3
of 29 outputs
Altmetric has tracked 15,798,970 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,161 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. 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 372,148 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 92% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.