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Analytics in action: users and predictive data in the neonatal intensive care unit

机译:行动中的分析:新生儿重症监护室中的用户和预测数据

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As the data phenomenon has grown, researchers have increasingly recognized the need to investigate algorithmic and data-driven technology, practices, and culture. While a number of studies have investigated the process of designing algorithms or examined the contours and consequences of algorithms themselves, more research is needed that details the ways in which users of data-driven technology make sense of algorithmic output and the conditions under which these processes unfold. This paper explores how users derive knowledge from predictive algorithms in medical contexts. Drawing upon interviews and observations of a neonatal intensive care unit, I examine how clinicians use data-driven predictive algorithms designed to forecast the onset of infection. Although the developers intend the technology to function as an early warning system, clinicians do not formulate knowledge from the technology solely as intended. Instead, I find that clinicians engage in a set of interpretive processes that I call 'conditioned reading,' and 'accumulative reading.' I suggest that these processes are possible due to the particular conditions of the medical context, including the institutional entrenchment of evidence-based medicine. I conclude by arguing that fully theorizing the social implications of data analytics will require researchers to investigate the role of institutional contexts.
机译:随着数据现象的发展,研究人员越来越认识到需要研究算法和数据驱动的技术,实践和文化。尽管许多研究调查了设计算法的过程或研究了算法本身的轮廓和后果,但还需要进行更多的研究,详细说明数据驱动技术的用户如何理解算法输出以及这些过程的条件。展开。本文探讨了用户如何在医学环境中从预测算法中获取知识。根据对新生儿重症监护室的采访和观察,我研究了临床医生如何使用旨在预测感染发作的数据驱动预测算法。尽管开发人员希望该技术充当预警系统,但临床医生并不能完全按照预期从该技术中汲取知识。取而代之的是,我发现临床医生参与了一系列解释性过程,我称之为“条件阅读”和“累积阅读”。我认为,由于医学背景的特殊条件,包括基于证据的医学制度化,这些过程是可能的。最后,我认为要对数据分析的社会含义进行完全理论化,将需要研究人员调查机构环境的作用。

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