West Peter, Van Kleek Max, Giordano Richard, Weal Mark, Shadbolt Nigel
Faculty of Health Sciences, University of Southampton, Southampton, United Kingdom.
Department of Computer Science, University of Oxford, Oxford, United Kingdom.
Front Public Health. 2017 Nov 1;5:284. doi: 10.3389/fpubh.2017.00284. eCollection 2017.
A characteristic trend of digital health has been the dramatic increase in 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.
数字健康的一个显著趋势是，呈递给临床医生的数据急剧增加，这源于个人自我追踪行为的日益普遍，而这又反过来受到自我追踪工具和技术激增的推动。此类工具不仅使自我追踪变得更加容易，还通过自动化数据收集、整理和存储，使其可能更加可靠。虽然自我追踪行为本身在人机交互文献中已得到广泛研究，但很少有研究探讨这些患者生成的数据是否能够支持临床流程，如为诊断、治疗监测或术后恢复提供证据，以及我们如何定义自我追踪数据的信息质量。在本文中，我们展示了对自我追踪工具实证研究的文献综述结果，其中我们确定了临床医生如何看待此类工具的信息质量。在这些研究中，临床医生认识到与准确性和可靠性、完整性、背景、患者动机及呈现方式相关的几个信息质量特征。我们讨论了在将自我追踪数据作为临床决策证据时所出现的这些问题。
