COVID 后数字医疗未来的破坏与错位。

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Big Data & Society Pub Date : 2020-07-01 Epub Date: 2020-08-20 DOI:10.1177/2053951720949567
Richard Milne, Alessia Costa
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引用次数: 0

摘要

在这篇文章中,我们将探讨 COVID 大流行作为阐述和实现数字健康未来的契机。我们的讨论借鉴了围绕 COVID-19 出现的论述,以及正在进行的关于未来护理想象的工作,这些想象与用于检测认知能力下降和痴呆症风险的数字工具有关。我们描述了后 COVID 时代的数字医疗未来是如何从其诞生的时机和速度方面进行叙述的,因为市场参与者试图建立 COVID 转型的规模和持久性。不过,我们也注意到了它们所设想的医疗实践的空间变化。在一个距离和隔离的时代,有效的远程操作能力已成为未来医疗评估、诊断和护理不可或缺的一部分。然而,数字医疗的空间化承诺和远程行动的能力分布不均--一些组织和实体不可避免地拥有更大的影响力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disruption and dislocation in post-COVID futures for digital health.

In this piece we explore the COVID pandemic as an opportunity for the articulation and realization of digital health futures. Our discussion draws on an engagement with emergent discourse around COVID-19 and ongoing work on imaginaries of future care associated with digital tools for the detection of cognitive decline and the risk of dementia. We describe how the post-COVID futures of digital health are narrated in terms of the timing and speed with which they are being brought into being, as market actors attempt to establish the scale and durability of the COVID transformation. However, we also point to the particularly spatial changes to medical practice they envisage. In a time of distancing and isolation, the ability to operate effectively at a distance has become integral to the future of medical assessment, diagnosis and care. However, spatialized promises of digital health and the ability to act remotely are unevenly spread - some organizations and entities inevitably have greater reach.

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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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