Illustrating Big Data discourses in the healthcare field

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Over the last few years, there has been a growing critical scholarly discourse that reflects on how Big Data shape our knowledge and our understanding. Primarily the fields of Science and Technology Studies and Critical Data Studies have been instrumental in elaborating the neglected and problematic dimensions of Big Data. However, it is unclear how and to what extent such insights become embedded in the healthcare field.

At the same time, we notice that the healthcare field welcomes initiatives that aim to improve healthcare through Big Data. This development is interesting, as the healthcare field is characterized by a strongly institutionalized set of epistemological principles and generally accepted methodologies. The field favors, for example, high-quality evidence from randomized controlled trials and observational studies to guide treatment decisions. Big Data challenge these principles and methodologies as they promise faster and more representative knowledge on the basis of large-scale data analyses.

In our recent article in Big Data & Society, “Conceptualizations of Big Data and their epistemological claims: a discourse analysis”, we studied the various ways in which Big Data is conceptualized in the healthcare field and assess the consequences of these different conceptualizations. We constructed five ideal-typical discourses that all frame Big Data in specific ways and that use other metaphors to describe Big Data. Three of the discourses (the modernist, instrumentalist and pragmatist) frame Big Data in positive terms and disseminate a compelling rhetoric. Metaphors of capturing, illuminating and harnessing data presume that Big Data are benign and leading to valid knowledge. The scientist and critical-interpretive discourses question the objectivity and effectivity claims of Big Data. Their metaphors of selecting and constructing data illustrate another political message, framing Big Data as limited.

Capturing Data
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During our analysis, it became apparent that especially the critical-interpretive discourse has not broadly infiltrated the healthcare domain, despite the attention that is given to the problematic assumptions and epistemological difficulties of Big Data in fields such as Science and Technology Studies and Critical Data Studies. We argue that the healthcare field would benefit from a more prominent critical-interpretive discourse, as the other discourses do not address important reflections on the normativity and situatedness of Big Data as well as the social and political processes that create Big Data.

For the article, we worked together with an illustrator to visualize the discourses, as we believed that illustrations could help to deepen our and the reader’s understanding of the discourses. We contacted Sue Doeksen (www.suedoeksen.nl) and she was very willing to help us and think along. What followed was an exciting process in which we and Sue both inspired each other. She wanted to have a clear message to present in a simple illustration. We had to make sure that the essence of the discourses was captured in the images.

This paper is part of a broader research project that focusses on the expectations and imaginaries associated with Big Data in healthcare. In the project, we conceptualize Big Data as a collection of practices and we aim to study what sorts of meaning it receives, is given to and how it changes practices. During the study, we specifically focus on the epistemological claims of Big Data.

Source: http://bigdatasoc.blogspot.com/2018/12/illustrating-big-data-discourses…

More information

This blog is written by:

  • Marthe Stevens is a PhD candidate at the department of Healthcare Governance at Erasmus School of Health Policy & Management (Erasmus University Rotterdam, the Netherlands) and WTMC.
  • Rik Wehrens  is an assistant professor at the department of Healthcare Governance at Erasmus School of Health Policy & Management.
  • Antoinette de Bont is an endowed professor at Erasmus School of Health Policy & Management.

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