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Identifying Health Information Technology Needs of Oncologists to Facilitate the Adoption of Genomic Medicine: Recommendations From the 2016 American Society of Clinical Oncology Omics and Precision…

Overview of attention for article published in Journal of Clinical Oncology, September 2017
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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 (90th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
38 tweeters
facebook
2 Facebook pages

Citations

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18 Dimensions

Readers on

mendeley
67 Mendeley
Title
Identifying Health Information Technology Needs of Oncologists to Facilitate the Adoption of Genomic Medicine: Recommendations From the 2016 American Society of Clinical Oncology Omics and Precision Oncology Workshop
Published in
Journal of Clinical Oncology, September 2017
DOI 10.1200/jco.2017.74.1744
Pubmed ID
Authors

Kevin S. Hughes, Edward P. Ambinder, Gregory P. Hess, Peter Paul Yu, Elmer V. Bernstam, Mark J. Routbort, Jean Rene Clemenceau, John T. Hamm, Phillip G. Febbo, Susan M. Domchek, James L. Chen, Jeremy L. Warner

Abstract

At the ASCO Data Standards and Interoperability Summit held in May 2016, it was unanimously decided that four areas of current oncology clinical practice have serious, unmet health information technology needs. The following areas of need were identified: 1) omics and precision oncology, 2) advancing interoperability, 3) patient engagement, and 4) value-based oncology. To begin to address these issues, ASCO convened two complementary workshops: the Omics and Precision Oncology Workshop in October 2016 and the Advancing Interoperability Workshop in December 2016. A common goal was to address the complexity, enormity, and rapidly changing nature of genomic information, which existing electronic health records are ill equipped to manage. The subject matter experts invited to the Omics and Precision Oncology Workgroup were tasked with the responsibility of determining a specific, limited need that could be addressed by a software application (app) in the short-term future, using currently available genomic knowledge bases. Hence, the scope of this workshop was to determine the basic functionality of one app that could serve as a test case for app development. The goal of the second workshop, described separately, was to identify the specifications for such an app. This approach was chosen both to facilitate the development of a useful app and to help ASCO and oncologists better understand the mechanics, difficulties, and gaps in genomic clinical decision support tool development. In this article, we discuss the key challenges and recommendations identified by the workshop participants. Our hope is to narrow the gap between the practicing oncologist and ongoing national efforts to provide precision oncology and value-based care to cancer patients.

Twitter Demographics

The data shown below were collected from the profiles of 38 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 25%
Student > Master 10 15%
Student > Ph. D. Student 9 13%
Student > Bachelor 5 7%
Other 5 7%
Other 11 16%
Unknown 10 15%
Readers by discipline Count As %
Medicine and Dentistry 19 28%
Computer Science 8 12%
Agricultural and Biological Sciences 6 9%
Social Sciences 5 7%
Biochemistry, Genetics and Molecular Biology 4 6%
Other 14 21%
Unknown 11 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 11 October 2017.
All research outputs
#927,729
of 15,690,347 outputs
Outputs from Journal of Clinical Oncology
#2,380
of 14,980 outputs
Outputs of similar age
#26,796
of 271,248 outputs
Outputs of similar age from Journal of Clinical Oncology
#93
of 187 outputs
Altmetric has tracked 15,690,347 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,980 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.8. This one has done well, scoring higher than 84% 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 271,248 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 90% of its contemporaries.
We're also able to compare this research output to 187 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 50% of its contemporaries.