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Evidence synthesis, economics and public policy

Overview of attention for article published in Research Synthesis Methods, October 2010
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Title
Evidence synthesis, economics and public policy
Published in
Research Synthesis Methods, October 2010
DOI 10.1002/jrsm.14
Pubmed ID
Authors

Ian Shemilt, Miranda Mugford, Luke Vale, Kevin Marsh, Cam Donaldson, Michael Drummond

Abstract

Systematic reviews and syntheses of evidence are increasingly used to inform public policy decisions. Growing budgetary pressures mean that decision makers often need to consider evidence on the costs and efficiency of alternatives as well as their effects. There are a number of methodological challenges in the identification, appraisal, synthesis, interpretation and use of economic evidence. This article draws on a recently published edited volume to review the latest developments, proposals and controversies in these aspects of economic evidence synthesis methodology. It focuses on two broad classes of approach: systematic review to summarize and compare the findings of existing economic analyses and synthesis of new economic results using decision models. The availability and scope of economic evidence is currently limited in many fields, but improving. Increased engagement between economists, the wider evidence synthesis community, and decision makers is needed to improve both the production and use of economic evidence. Further research to improve the evidence base that underpins application of economic evidence synthesis methodology will need to embrace a broader range of methods than economic evaluation and systematic review alone. Copyright © 2010 John Wiley & Sons, Ltd.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 3 5%
United Kingdom 2 3%
Ecuador 1 2%
Brazil 1 2%
Netherlands 1 2%
South Africa 1 2%
Peru 1 2%
Spain 1 2%
Unknown 52 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 22%
Researcher 11 17%
Student > Master 8 13%
Professor 6 10%
Professor > Associate Professor 6 10%
Other 12 19%
Unknown 6 10%
Readers by discipline Count As %
Medicine and Dentistry 15 24%
Social Sciences 8 13%
Psychology 6 10%
Agricultural and Biological Sciences 6 10%
Nursing and Health Professions 5 8%
Other 13 21%
Unknown 10 16%