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Computerized clinical decision support systems for therapeutic drug monitoring and dosing: A decision-maker-researcher partnership systematic review

Overview of attention for article published in Implementation Science, August 2011
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Title
Computerized clinical decision support systems for therapeutic drug monitoring and dosing: A decision-maker-researcher partnership systematic review
Published in
Implementation Science, August 2011
DOI 10.1186/1748-5908-6-90
Pubmed ID
Authors

Robby Nieuwlaat, Stuart J Connolly, Jean A Mackay, Lorraine Weise-Kelly, Tamara Navarro, Nancy L Wilczynski, R Brian Haynes, the CCDSS Systematic Review Team

Abstract

Some drugs have a narrow therapeutic range and require monitoring and dose adjustments to optimize their efficacy and safety. Computerized clinical decision support systems (CCDSSs) may improve the net benefit of these drugs. The objective of this review was to determine if CCDSSs improve processes of care or patient outcomes for therapeutic drug monitoring and dosing.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Norway 2 1%
Canada 2 1%
Brazil 1 <1%
Netherlands 1 <1%
Argentina 1 <1%
Indonesia 1 <1%
Unknown 163 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 31 18%
Researcher 28 16%
Student > Ph. D. Student 25 14%
Professor 15 9%
Student > Doctoral Student 14 8%
Other 43 24%
Unknown 20 11%
Readers by discipline Count As %
Medicine and Dentistry 77 44%
Computer Science 27 15%
Nursing and Health Professions 10 6%
Social Sciences 10 6%
Pharmacology, Toxicology and Pharmaceutical Science 7 4%
Other 18 10%
Unknown 27 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 October 2011.
All research outputs
#17,648,479
of 22,653,392 outputs
Outputs from Implementation Science
#1,621
of 1,715 outputs
Outputs of similar age
#97,401
of 119,650 outputs
Outputs of similar age from Implementation Science
#22
of 28 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,715 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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 119,650 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.