Background: With the rise of connected sensor technologies, there are seemingly endless possibilities for new ways to measure health. These technologies offer researchers and clinicians opportunities to go beyond brief snapshots of data captured by traditional in-clinic assessments, to redefine health and disease. Given the myriad opportunities for measurement, how do research or clinical teams know what they should be measuring? Patient engagement, early and often, is paramount to thoughtfully selecting what is most important. Regulators encourage stakeholders to have a patient focus but actionable steps for continuous engagement are not well defined. Without patient-focused measurement, stakeholders risk entrenching digital versions of poor traditional assessments and proliferating low-value tools that are ineffective, burdensome, and reduce both quality and efficiency in clinical care and research. Summary: This article synthesizes and defines a sequential framework of core principles for selecting and developing measurements in research and clinical care that are meaningful for patients. We propose next steps to drive forward the science of high-quality patient engagement in support of measures of health that matter in the era of digital medicine. Key Messages: All measures of health should be meaningful, regardless of the product’s regulatory classification, type of measure, or context of use. To evaluate meaningfulness of signals derived from digital sensors, the following four-level framework is useful: Meaningful Aspect of Health, Concept of Interest, Outcome to be measured, and Endpoint (exclusive to research). Incorporating patient input is a dynamic process that requires more than a single, transactional touch point but rather should be conducted continuously throughout the measurement selection process. We recommend that developers, clinicians, and researchers reevaluate processes for more continuous patient engagement in the development, deployment, and interpretation of digital measures of health.

中文翻译：

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对患者至关重要的数字措施：指导选择和开发健康数字措施的框架

背景：随着连接传感器技术的兴起，测量健康的新方法似乎有无穷无尽的可能性。这些技术为研究人员和临床医生提供了超越传统临床评估捕获数据的简要快照的机会，以重新定义健康和疾病。鉴于有无数的测量机会，研究或临床团队如何知道他们应该测量什么？尽早且经常地让患者参与对于深思熟虑地选择最重要的内容至关重要。监管机构鼓励利益相关者以患者为中心，但没有明确定义持续参与的可操作步骤。如果没有以患者为中心的测量，利益相关者可能会冒着根深蒂固的不良传统评估的数字版本和激增无效、繁重的低价值工具的风险，降低临床护理和研究的质量和效率。摘要：本文综合并定义了一个核心原则的顺序框架，用于在研究和临床护理中选择和开发对患者有意义的测量方法。我们提出下一步措施，以推动高质量患者参与的科学，以支持在数字医学时代至关重要的健康措施。关键信息：无论产品的监管分类、测量类型或使用环境如何，所有健康测量都应该有意义。为了评估来自数字传感器的信号的意义，以下四级框架很有用：有意义的健康方面、感兴趣的概念、要测量的结果和终点（研究专用）。纳入患者输入是一个动态过程，它需要的不仅仅是一个单一的事务性接触点，而是应该在整个测量选择过程中持续进行。我们建议开发人员、临床医生和研究人员重新评估流程，以使患者更持续地参与数字健康测量的开发、部署和解释。