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Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews

Overview of attention for article published in Systematic Reviews, August 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 (88th percentile)

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1 blog
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Citations

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97 Dimensions

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153 Mendeley
Title
Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
Published in
Systematic Reviews, August 2016
DOI 10.1186/s13643-016-0315-4
Pubmed ID
Authors

Ian Shemilt, Nada Khan, Sophie Park, James Thomas

Abstract

Meta-research studies investigating methods, systems, and processes designed to improve the efficiency of systematic review workflows can contribute to building an evidence base that can help to increase value and reduce waste in research. This study demonstrates the use of an economic evaluation framework to compare the costs and effects of four variant approaches to identifying eligible studies for consideration in systematic reviews. A cost-effectiveness analysis was conducted using a basic decision-analytic model, to compare the relative efficiency of 'safety first', 'double screening', 'single screening' and 'single screening with text mining' approaches in the title-abstract screening stage of a 'case study' systematic review about undergraduate medical education in UK general practice settings. Incremental cost-effectiveness ratios (ICERs) were calculated as the 'incremental cost per citation 'saved' from inappropriate exclusion' from the review. Resource use and effect parameters were estimated based on retrospective analysis of 'review process' meta-data curated alongside the 'case study' review, in conjunction with retrospective simulation studies to model the integrated use of text mining. Unit cost parameters were estimated based on the 'case study' review's project budget. A base case analysis was conducted, with deterministic sensitivity analyses to investigate the impact of variations in values of key parameters. Use of 'single screening with text mining' would have resulted in title-abstract screening workload reductions (base case analysis) of >60 % compared with other approaches. Across modelled scenarios, the 'safety first' approach was, consistently, equally effective and less costly than conventional 'double screening'. Compared with 'single screening with text mining', estimated ICERs for the two non-dominated approaches (base case analyses) ranged from £1975 ('single screening' without a 'provisionally included' code) to £4427 ('safety first' with a 'provisionally included' code) per citation 'saved'. Patterns of results were consistent between base case and sensitivity analyses. Alternatives to the conventional 'double screening' approach, integrating text mining, warrant further consideration as potentially more efficient approaches to identifying eligible studies for systematic reviews. Comparable economic evaluations conducted using other systematic review datasets are needed to determine the generalisability of these findings and to build an evidence base to inform guidance for review authors.

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X Demographics

The data shown below were collected from the profiles of 112 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Unknown 150 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 13%
Student > Ph. D. Student 19 12%
Student > Master 18 12%
Librarian 13 8%
Professor 9 6%
Other 33 22%
Unknown 41 27%
Readers by discipline Count As %
Medicine and Dentistry 28 18%
Computer Science 15 10%
Social Sciences 13 8%
Nursing and Health Professions 11 7%
Agricultural and Biological Sciences 8 5%
Other 30 20%
Unknown 48 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 75. 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 30 July 2019.
All research outputs
#552,974
of 24,892,887 outputs
Outputs from Systematic Reviews
#61
of 2,171 outputs
Outputs of similar age
#10,937
of 350,564 outputs
Outputs of similar age from Systematic Reviews
#5
of 34 outputs
Altmetric has tracked 24,892,887 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 2,171 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one has done particularly well, scoring higher than 97% 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 350,564 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 34 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.