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  1. KEEP
  2. Theses and Dissertations
  3. Barrett, The Honors College Thesis/Creative Project Collection
  4. Preliminary Results and the Unconsidered Potential of the 2014 Open Payments Research Dataset: Introducing a Complex Systems Framework for Extracting Meaningful Information from Big Data
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Preliminary Results and the Unconsidered Potential of the 2014 Open Payments Research Dataset: Introducing a Complex Systems Framework for Extracting Meaningful Information from Big Data

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Description

This work challenges the conventional perceptions surrounding the utility and use of the CMS Open Payments data. I suggest unconsidered methodologies for extracting meaningful information from these data following an exploratory analysis of the 2014 research dataset that, in turn, enhance its value as a public good. This dataset is favored for analysis over the general payments dataset as it is believed that generating transparency in the pharmaceutical and medical device R&D process would be of the greatest benefit to public health. The research dataset has been largely ignored by analysts and this may be one of the few works that have accomplished a comprehensive exploratory analysis of these data. If we are to extract valuable information from this dataset, we must alter both our approach as well as focus our attention towards re-conceptualizing the questions that we ask. Adopting the theoretical framework of complex systems serves as the foundation for our interpretation of the research dataset. This framework, in conjunction with a methodological toolkit for network analysis, may set a precedent for the development of alternative perspectives that allow for novel interpretations of the information that big data attempts to convey. By thus proposing a novel perspective in interpreting the information that this dataset contains, it is possible to gain insight into the emergent dynamics of the collaborative relationships that are established during the pharmaceutical and medical device R&D process.

Date Created
2016-05
Contributors
  • Velez-Cruz, Nayely Luz (Author)
  • Laubichler, Manfred (Thesis director)
  • Van Der Leeuw, Sander (Committee member)
  • School of Sustainability (Contributor)
  • Sanford School of Social and Family Dynamics (Contributor)
  • School of Human Evolution and Social Change (Contributor)
  • School of Historical, Philosophical and Religious Studies (Contributor)
  • School of Life Sciences (Contributor)
  • Barrett, The Honors College (Contributor)
Topical Subject
  • Big Data
  • public health
  • Sociology
  • Complex Systems
Resource Type
Text
Extent
99 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Barrett, The Honors College Thesis/Creative Project Collection
Series
Academic Year 2015-2016
Handle
https://hdl.handle.net/2286/R.I.37367
Embargo Release Date
Fri, 04/13/2018 - 03:48
Level of coding
minimal
Cataloging Standards
asu1
System Created
  • 2017-10-30 02:50:58
System Modified
  • 2021-08-11 04:09:57
  •     
  • 1 year 7 months ago
Additional Formats
  • OAI Dublin Core
  • MODS XML

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