临床医生的价值来自大数据:创造前进的道路

Christopher A. Bain, J. Seah, Bismi Jomon
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引用次数: 0

摘要

虽然许多医疗保健行业的人认为大数据时代的到来是一件非常积极的事情,但也有一些人反驳了这一说法,并越来越多地指出在临床研究中使用大数据衍生数据集的局限性。在本文中,我们研究了一些关于临床医生和研究人员访问数据的挑战和限制,尽管在医疗保健行业中收集和生成了大量数据(大数据)。我们还简要探讨了从这些数据集中识别队列并对其进行分析的一些挑战。作为其中的一部分,我们介绍了定制设计的搜索工具(队列发现工具(CDT))的最新发展,该工具允许此类用户灵活地访问REASON发现平台®内庞大的临床数据存储库。我们还研究了该工具的一些优点和缺点,以及影响临床医生在其原发部位吸收的因素。
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Clinician value from big data: creating a path forwards
Whilst many in healthcare view the arrival of the era of big data as an overwhelmingly positive thing, there are some who refute that claim and increasingly point out the limitations of using big data derived datasets for clinical research in particular. In this paper we examine some of the challenges and constraints regarding access to data for clinicians and researchers, despite the collection and generation of vast amounts of data (big data) in the healthcare industry. We also briefly explore some of the challenges around identifying cohorts from, and performing analysis on, such datasets. As part of this we present on the latest developments with a custom designed search tool (The cohort discovery tool (CDT)) that allows such users flexibility in how they access a vast clinical data repository inside The REASON Discovery Platform®. We also examine some of the strengths and weaknesses of the tool and factors influencing its uptake by clinicians at its primary site.
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