Book Review | Data Paradoxes: The Politics of Data-Intensive Sources in Modern Healthcare

Book Review |  Data Paradoxes: The Politics of Data-Intensive Sources in Modern Healthcare

IN Data Paradoxes: The Politics of Data-Intensive Sources in Modern Healthcare, Klaus Hoyer explores the paradoxes associated with health data, using Denmark as an example, arguing that increased data collection does not always lead to improved service efficiency. The result of the book’s extensive interdisciplinary research is a detailed guide to how we can think about how we relate to the data we have received about us. Sam DiBella.

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Data Paradoxes: The Politics of Data-Intensive Sources in Modern Healthcare. Claus Hoyer. Massachusetts Institute of Technology Press. 2023

We usually come across paradoxes as puzzles that force us to change our point of view. IN Data Paradoxes: The Politics of Data-Intensive Sources in Modern Healthcare, anthropologist Klaus Heuer shows how medical data creates its own contradictions, which disappear when you look at it from the right angle, that is, if you determine who finds this documentation useful. Modern data often serves institutional or government purposes while alienating the workers who create it. The resulting generative, extensive study explores the chain of paradoxes generated by data practices: citizens are both empowered and disempowered by their data; meaningless painstaking work promised to give meaning; and erroneous data necessary for any claim under evidence-based medicine.

In this ethnographic study of the Danish healthcare system, open access, “data-intensive research” is changing healthcare policy and the experience of its actors, both workers and patients.

In this ethnographic study of the Danish healthcare system, open access, “data-intensive research” is changing healthcare policy and the experience of its actors, both workers and patients. Denmark created its own data paradoxes by merging American software platforms with a robust national identity and healthcare system. The result is the envy of politicians around the world and far exceeds the technical capacity of the “fragmented” American healthcare system. Hoyer, however, warns that the same paradoxes are likely to be recreated in countries with similar healthcare infrastructures. Developers of Danish data-processing tools, for example, have promised to cut down on workload despite burdening medical staff with endless paperwork.

Critical data studies over the last decade have often used extractive metaphors to describe their subject matter. Data is oil, gold, exhaust or labor. Everything suggests that our information – the wealth of our age – enriches corporations and creates danger for ordinary people. With a background in medical anthropology, Hoyer wants to highlight how data is changing how we perceive and perceive the world: he suggests that data is a drug that we and our medical institutions simply cannot get enough of. Noting this dependence on data is not new. Influential Edited Volume“Raw data” is an oxymoronfor example, explored similar implications of “big data” ten years ago.

Fear that our information—the wealth of our age—is enriching corporations and endangering ordinary people.

Data paradoxes recalls other recent attempts to unravel sites where technology allows its users to channel power through rhetoric as much as craftsmanship, such as Christo Sims’ site. Destructive fixation or Morgan Ames Charisma Machine. In these books, comparing what the proponents of technology promise with its practical effect reveals both politics and ideology. But the way Hoyer sits and tries to explain the conflicting views of the medical professionals and politicians he spoke to seems different. Hoyer is trying to bring together years of disparate research done by him and others at the Center for Health Sciences and Technology at the University of Copenhagen into a single example of Danish health care.

Who benefits from the data daemon now? Hoyer’s discussion of the exclusion of health care workers from working with data begins to lead to an answer: the data collected often serves the interests of the institution or government that collects it, not the worker. Since data workers do not benefit from the cleaning or analysis they do, a healthcare system encouraged to integrate social services is paradoxically seen as a disintegration of interests. Nobody wants to create spreadsheets that they will never use in person.

There are a few places where Hoyer doesn’t quite understand his points of view. The chapter on “data promises” discusses the proliferation of unsubstantiated reports commissioned by consulting companies such as Deloitte and McKinsey to inflate the results of medical data integration. He notes that politicians will, on the one hand, call for the collection of more and better health data, and on the other hand, they will lose sight of the pathetic data that back up their claims or that they themselves produce:

“The coexistence of two truths can be productive for politicians because it creates an aura of legitimacy and allows delay. By arguing that it is better to wait until more data is accumulated, data promises breed a form of temporary breach of public accountability. In this context, data as a promise is—politically—a more powerful resource than data as evidence” (55).

Later in the chapter, Hoyer asks, “Why are (lobbyists) not afraid of data integrity issues?” (113). The consultants he talks to know the data they’re gathering is bullshit, but they don’t seem to mind. However, Hoyer answers his own question elsewhere: consultants are not afraid of data credibility issues because they benefit from it. Their methods of strategic delay create a void that they, and only they, can fill with their experience. This is just one example that came up while I was reading. Despite the fact that his reasoning is correct at every turn, it sometimes seemed to me that Hoyer was not talking about himself.

(Consultants) strategic delay techniques create a void that they and only they can fill with their experience.

Such disagreements in an otherwise well-argued book could be explained Data paradoxes the titanic scope of the discipline: philosophy, medical anthropology, history, science and technology studies, organizational studies, epidemiology, and health policy all get their place. As a result and as an example Data paradoxes unusual. Hoyer explains at the end of the book:

“My analytical goal has always been to synthesize the driving forces and consequences of intensive data mining, rather than a detailed study of the use of any individual data. (…) I wanted to describe the interplay of policy, practice and experience. Therefore, the book was never meant to be a detailed ethnography of a specific patient group, clinic, study, laboratory, administrative office, or country.” (224)

Danish or European health researchers will find descriptions of the design, implementation of the Danish health data portal,, but with an emphasis on how it is perceived and experienced rather than technical details. Hoyer is more interested in using the results of an entire Danish health research program to get a broader picture of the state of health data.

This approach also means that Data paradoxes not read or cited, like most other ethnographies. Hoyer cites extensively and only clarifies the connection and context of the quotation where clearly necessary. Given all the interdisciplinary areas on which it draws, it will be difficult for the reader to analyze the supporting claims unless they are updated in all relevant areas. This is not a criticism; it just means Data paradoxes should be read in a special way. A few chapters—on living with data, work, and pandemics—focus more on the details of field research. Together, the book’s chapters do not build on each other to offer a single theory that explains them all. On the contrary, each of them represents Hoyer’s exploration of a particular paradox. The result is better, as are the data paradoxes themselves, as a guide for thought and research, than as an explanation on its own.

Like our’data relations In order for the data economy to naturalize over time, our perception of data has changed.

The technological utopianism still prevalent today argues that “progress” is inevitable and that the intrinsic qualities of technology are not subject to change or context. Data paradoxes joins a long line of technology research that explores why adoption matters, albeit not in the same way as his peers. Like ours”data relations“The data economy is naturalizing over time, our perception of data is changing. I found the sections in which Hoyer describes his own emotional reactions to the data to be among the most compelling. Our bodies are forced to confess themselves to doctors and machines, only to be cut into data points and returned to us as alienating, even frightening descriptions. Data paradoxes shows, however, that attempts to rationalize health care in such a system will only continue to generate new paradoxes in response.

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