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Decision-making process for conditions nominated to the Recommended Uniform Screening Panel: statement of the US Department of Health and Human Services Secretary’s Advisory Committee on Heritable…

Overview of attention for article published in Genetics in Medicine, August 2013
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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 (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
4 tweeters

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
53 Mendeley
Title
Decision-making process for conditions nominated to the Recommended Uniform Screening Panel: statement of the US Department of Health and Human Services Secretary’s Advisory Committee on Heritable Disorders in Newborns and Children
Published in
Genetics in Medicine, August 2013
DOI 10.1038/gim.2013.98
Pubmed ID
Authors

Alex R. Kemper, Nancy S. Green, Ned Calonge, Wendy K.K. Lam, Anne M. Comeau, Aaron J. Goldenberg, Jelili Ojodu, Lisa A. Prosser, Susan Tanksley, Joseph A. Bocchini Jr

Abstract

Purpose:The US Secretary of Health and Human Services provides guidance to state newborn screening programs about which conditions should be included in screening (i.e., the "Recommended Uniform Screening Panel"). This guidance is informed by evidence-based recommendations from the Secretary's Advisory Committee on Heritable Disorders in Newborns and Children. This report describes the Advisory Committee's revised decision-making process for considering conditions nominated to the panel.Methods:An expert panel meeting was held in April 2012 to revise the decision matrix, which helps to guide the recommendation process. In January 2013, the Advisory Committee voted to adopt the revised decision matrix.Results:The revised decision matrix clarifies the approach to rating magnitude and certainty of the net benefit of screening to the population of screened newborns for nominated conditions, and now includes the consideration of the capability of state newborn screening programs for population-wide implementation by evaluating the feasibility and readiness of states to adopt screening for nominated conditions.Conclusion:The revised decision matrix will bring increased quality, transparency, and consistency to the process of modifying the recommended uniform screening panel and will now allow formal evaluation of the challenges that state newborn screening programs face in adopting screening for new conditions.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 4%
United States 1 2%
Unknown 50 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 21%
Researcher 9 17%
Student > Ph. D. Student 8 15%
Professor > Associate Professor 7 13%
Other 6 11%
Other 9 17%
Unknown 3 6%
Readers by discipline Count As %
Medicine and Dentistry 19 36%
Agricultural and Biological Sciences 6 11%
Biochemistry, Genetics and Molecular Biology 5 9%
Social Sciences 5 9%
Neuroscience 2 4%
Other 10 19%
Unknown 6 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 27 February 2018.
All research outputs
#1,648,239
of 17,351,915 outputs
Outputs from Genetics in Medicine
#694
of 2,327 outputs
Outputs of similar age
#16,880
of 166,309 outputs
Outputs of similar age from Genetics in Medicine
#12
of 30 outputs
Altmetric has tracked 17,351,915 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,327 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.6. This one has gotten more attention than average, scoring higher than 70% 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 166,309 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.