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Big Data and Real-World Data based Cost-Effectiveness Studies and Decision-making Models: A Systematic Review and Analysis

Overview of attention for article published in Frontiers in Pharmacology, October 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

policy
1 policy source
twitter
3 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Big Data and Real-World Data based Cost-Effectiveness Studies and Decision-making Models: A Systematic Review and Analysis
Published in
Frontiers in Pharmacology, October 2021
DOI 10.3389/fphar.2021.700012
Pubmed ID
Authors

Z. Kevin Lu, Xiaomo Xiong, Taiying Lee, Jun Wu, Jing Yuan, Bin Jiang

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 21%
Student > Ph. D. Student 5 15%
Student > Doctoral Student 4 12%
Student > Bachelor 4 12%
Lecturer 2 6%
Other 3 9%
Unknown 9 26%
Readers by discipline Count As %
Medicine and Dentistry 6 18%
Pharmacology, Toxicology and Pharmaceutical Science 4 12%
Social Sciences 3 9%
Nursing and Health Professions 3 9%
Business, Management and Accounting 2 6%
Other 7 21%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 November 2022.
All research outputs
#7,725,572
of 25,292,378 outputs
Outputs from Frontiers in Pharmacology
#3,462
of 19,505 outputs
Outputs of similar age
#145,025
of 435,382 outputs
Outputs of similar age from Frontiers in Pharmacology
#207
of 1,124 outputs
Altmetric has tracked 25,292,378 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 19,505 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 81% 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 435,382 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 1,124 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.