Situated big data and big data analytics for healthcare

M. Sterling
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引用次数: 4

Abstract

Big Data and Big Data Analytics are a set of emerging technologies that allow researchers, organizations, and businesses to draw actionable insights from large data sets. A primary source of such large data sets are those created in a healthcare or medical context. This can include data from, but not limited to, electronic health records, mobile applications (mHealth), diagnostic equipment, genomics, and social media. Consequently, Big Data technologies promise to have a transformative impact in healthcare, public health, and medical research, among other application areas. For example, researchers are already developing new standards, protocols, and study designs that are more suited mHealth interventions as opposed to the traditional randomized clinical trial. Also, the easy availability of data now allows population level studies at scales that were previously unimaginable. Although Big Data and Analytics have the potential to deliver significant benefits in healthcare applications, the full consequences of this technological shift are, as yet, unknown. The application of Big Data in healthcare is often viewed as an inevitability or technological imperative. This perspective discounts the role of human agency in a dangerous way. As a theoretical foundation, we review relevant ideas from the organizational communications literature and discuss theories of technology acquisition such as adaptive structuration. The notion of situatedness is explored with examples drawn from visualization, augmented reality, and cultural heritage. Due to significant interest, systematic literature reviews and meta-analyses on the topic of Big Data in healthcare are already available. These reviews help to delineate both the potential benefits and challenges in this area. In particular, we emphasize challenges with high human costs such as the privacy of patient data and the thoughtful design of technological interventions for at-risk populations. Lastly, we show how a situated perspective is a necessary tool in building next generation healthcare information systems.
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医疗保健领域的大数据和大数据分析
大数据和大数据分析是一组新兴技术,使研究人员、组织和企业能够从大数据集中获得可操作的见解。此类大型数据集的主要来源是在医疗保健或医疗环境中创建的数据集。这可以包括但不限于电子健康记录、移动应用程序(mHealth)、诊断设备、基因组学和社交媒体的数据。因此,大数据技术有望在医疗保健、公共卫生和医学研究等应用领域产生变革性影响。例如,研究人员已经在开发新的标准、协议和研究设计,这些标准、协议和设计更适合移动医疗干预,而不是传统的随机临床试验。此外,数据的容易获得现在可以在以前难以想象的规模上进行人口水平的研究。虽然大数据和分析有可能在医疗保健应用中带来巨大的好处,但这种技术转变的全部后果尚不清楚。大数据在医疗保健领域的应用通常被视为一种必然性或技术上的必要性。这种观点以一种危险的方式低估了人类能动性的作用。作为理论基础,我们回顾了组织传播文献中的相关观点,并讨论了适应性结构等技术获取理论。情境性的概念通过可视化、增强现实和文化遗产的例子来探索。由于人们对医疗保健大数据的兴趣浓厚,已经有了系统的文献综述和荟萃分析。这些评论有助于描述这一领域的潜在利益和挑战。我们特别强调高人力成本的挑战,如患者数据的隐私和针对高危人群的技术干预的周到设计。最后,我们将展示情境视角如何成为构建下一代医疗保健信息系统的必要工具。
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