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Routinely collected data for randomized trials: promises, barriers, and implications

Overview of attention for article published in Trials, January 2018
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About this Attention Score

  • 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 (98th percentile)

Mentioned by

blogs
1 blog
twitter
126 tweeters

Citations

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58 Dimensions

Readers on

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131 Mendeley
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Title
Routinely collected data for randomized trials: promises, barriers, and implications
Published in
Trials, January 2018
DOI 10.1186/s13063-017-2394-5
Pubmed ID
Authors

Kimberly A. Mc Cord, Rustam Al-Shahi Salman, Shaun Treweek, Heidi Gardner, Daniel Strech, William Whiteley, John P. A. Ioannidis, Lars G. Hemkens

Abstract

Routinely collected health data (RCD) are increasingly used for randomized controlled trials (RCTs). This can provide three major benefits: increasing value through better feasibility (reducing costs, time, and resources), expanding the research agenda (performing trials for research questions otherwise not amenable to trials), and offering novel design and data collection options (e.g., point-of-care trials and other designs directly embedded in routine care). However, numerous hurdles and barriers must be considered pertaining to regulatory, ethical, and data aspects, as well as the costs of setting up the RCD infrastructure. Methodological considerations may be different from those in traditional RCTs: RCD are often collected by individuals not involved in the study and who are therefore blinded to the allocation of trial participants. Another consideration is that RCD trials may lead to greater misclassification biases or dilution effects, although these may be offset by randomization and larger sample sizes. Finally, valuable insights into external validity may be provided when using RCD because it allows pragmatic trials to be performed. We provide an overview of the promises, challenges, and potential barriers, methodological implications, and research needs regarding RCD for RCTs. RCD have substantial potential for improving the conduct and reducing the costs of RCTs, but a multidisciplinary approach is essential to address emerging practical barriers and methodological implications. Future research should be directed toward such issues and specifically focus on data quality validation, alternative research designs and how they affect outcome assessment, and aspects of reporting and transparency.

Twitter Demographics

The data shown below were collected from the profiles of 126 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 131 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 23%
Student > Master 15 11%
Student > Bachelor 14 11%
Student > Ph. D. Student 11 8%
Other 10 8%
Other 26 20%
Unknown 25 19%
Readers by discipline Count As %
Medicine and Dentistry 42 32%
Pharmacology, Toxicology and Pharmaceutical Science 9 7%
Nursing and Health Professions 7 5%
Agricultural and Biological Sciences 7 5%
Psychology 5 4%
Other 24 18%
Unknown 37 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 76. 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 September 2019.
All research outputs
#382,319
of 19,463,333 outputs
Outputs from Trials
#52
of 5,021 outputs
Outputs of similar age
#12,889
of 428,277 outputs
Outputs of similar age from Trials
#6
of 476 outputs
Altmetric has tracked 19,463,333 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,021 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 99% 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 428,277 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 476 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.