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首页> 外文期刊>Frontiers in Public Health >Information Quality Challenges of Patient-Generated Data in Clinical Practice
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Information Quality Challenges of Patient-Generated Data in Clinical Practice

机译：临床实践中患者生成数据的信息质量挑战

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摘要

A characteristic trend of digital health has been the dramatic increase in patient-generated data being presented to clinicians, which follows from the increased ubiquity of self-tracking practices by individuals, driven, in turn, by the proliferation of self-tracking tools and technologies. Such tools not only make self-tracking easier but also potentially more reliable by automating data collection, curation, and storage. While self-tracking practices themselves have been studied extensively in human–computer interaction literature, little work has yet looked at whether these patient-generated data might be able to support clinical processes, such as providing evidence for diagnoses, treatment monitoring, or postprocedure recovery, and how we can define information quality with respect to self-tracked data. In this article, we present the results of a literature review of empirical studies of self-tracking tools, in which we identify how clinicians perceive quality of information from such tools. In the studies, clinicians perceive several characteristics of information quality relating to accuracy and reliability, completeness, context, patient motivation, and representation. We discuss the issues these present in admitting self-tracked data as evidence for clinical decisions.
机译：数字健康的一个典型趋势是，向患者提供给临床医生的患者生成的数据急剧增加，这是由于个体自我跟踪实践的普遍性增加，这又是由于自我跟踪工具和技术的扩散所致。这样的工具不仅可以使自动跟踪变得更容易，而且还可以通过自动执行数据收集，管理和存储来提高可靠性。尽管在人机交互文献中对自我跟踪做法本身进行了广泛的研究，但很少有工作关注这些患者生成的数据是否能够支持临床过程，例如为诊断，治疗监测或术后恢复提供证据，以及我们如何定义有关自跟踪数据的信息质量。在本文中，我们介绍了有关自我跟踪工具的经验研究的文献综述的结果，其中我们确定了临床医生如何从此类工具中感知信息质量。在研究中，临床医生感知到信息质量的几个特征，这些特征与准确性和可靠性，完整性，上下文，患者动机和表示形式有关。我们讨论了在接受自我跟踪数据作为临床决策依据时存在的问题。

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