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用多模态数据衡量健康相关生命质量:观点。

Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.

机构信息

Digital Medicine Society, Boston, MA, United States.

Cambridge Cognition, Cambridge, United Kingdom.

出版信息

J Med Internet Res. 2022 May 26;24(5):e35951. doi: 10.2196/35951.

Abstract

The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.

摘要

客观测量性能和行为方面的能力是数字健康的基本支柱,使数字健康产品、去中心化试验概念、证据生成、数字治疗等成为可能。能够同时测量多种模式的新兴多模态技术以及整合多个来源输入的努力,进一步扩大了数字测量可以评估的范围。数字健康领域的专家作为多方利益相关者研讨会的一部分被召集起来,检查多模态数字测量在两个关键领域的进展:疾病检测和与生活质量相关的健康有意义方面的测量。在这里,我们呈现一份会议报告,总结关键讨论点、相关文献,最后展望近期的未来,包括多模态测量如何为药物开发和医疗服务提供价值,以及如果我们要继续建立迄今为止令人鼓舞的进展,需要在三个关键领域取得进展:合作和数据共享、消除数据集成障碍,以及围绕新测量能力的稳健模块化评估达成一致。

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