Supplementary Material for: Metadata Concepts for Advancing the Use of Digital Health Technologies in Clinical Research

Digital health technologies (smartphones, smartwatches, and other body-worn sensors) can act as novel tools to aid in the diagnosis and remote objective monitoring of an individual’s disease symptoms, both in clinical care and in research. Nonetheless, such digital health technologies have yet to widely demonstrate value in clinical research due to insufficient data interpretability and lack of regulatory acceptance. Metadata, i.e., data that accompany and describe the primary data, can be utilized to better understand the context of the sensor data and can assist in data management, data sharing, and subsequent data analysis. The need for data and metadata standards for digital health technologies has been raised in academic and industry research communities and has also been noted by regulatory authorities. Therefore, to address this unmet need, we here propose a metadata set that reflects regulatory guidelines and that can serve as a conceptual map to (1) inform researchers on the metadata they should collect in digital health studies, aiming to increase the interpretability and exchangeability of their data, and (2) direct standard development organizations on how to extend their existing standards to incorporate digital health technologies. The proposed metadata set is informed by existing standards pertaining to clinical trials and medical devices, in addition to existing schemas that have supported digital health technology studies. We illustrate this specifically in the context of Parkinson’s disease, as a model for a wide range of other chronic conditions for which remote monitoring would be useful in both care and science. We invite the scientific and clinical research communities to apply the proposed metadata set to ongoing and planned research. Where the proposed metadata fall short, we ask users to contribute to its ongoing revision so that an adequate degree of consensus can be maintained in a rapidly evolving technology landscape.

数字健康技术（智能手机、智能手表及其他可穿戴传感器）可作为新型工具，在临床诊疗与科研场景中辅助个体疾病症状的诊断及远程客观监测。然而，由于数据可解释性不足且缺乏监管认可度，此类数字健康技术尚未在临床研究中广泛体现其应用价值。元数据（Metadata），即伴随并描述原始数据的数据，可用于更好地理解传感器数据的上下文信息，同时助力数据管理、数据共享及后续数据分析。学术与产业研究界已呼吁制定数字健康技术相关的数据与元数据标准，监管机构也对此予以关注。为此，为满足这一尚未被满足的需求，本文提出一套契合监管指南的元数据集，其可作为概念框架：其一，为数字健康研究中的研究者提供元数据采集指引，以提升其研究数据的可解释性与可交换性；其二，为标准制定机构提供指导，帮助其拓展现有标准以纳入数字健康技术范畴。本套元数据集的制定参考了现有临床试验与医疗器械相关标准，以及已支撑数字健康技术研究的现有数据模式（Schema）。我们以帕金森病为例进行具体阐释，将其作为诸多其他慢性病的研究模型——此类慢性病的远程监测在临床诊疗与科研中均具有应用价值。我们邀请科研与临床研究界将本套元数据集应用于正在开展及计划中的研究工作。若本套元数据集存在不足，我们恳请使用者参与其后续修订，以便在快速迭代的技术环境中维持足够的行业共识。