Manta Christine, Patrick-Lake Bray, Goldsack Jennifer C
Digital Medicine Society, Boston, Massachusetts, USA.
Elektra Labs, Boston, Massachusetts, USA.
Digit Biomark. 2020 Sep 15;4(3):69-77. doi: 10.1159/000509725. eCollection 2020 Sep-Dec.
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 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.
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.
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.
随着互联传感器技术的兴起，测量健康状况的新方法似乎有无穷的可能性。这些技术为研究人员和临床医生提供了机会，使他们能够超越传统临床评估所捕获的简短数据快照，重新定义健康和疾病。鉴于测量机会众多，研究或临床团队如何知道该测量什么呢？尽早且经常让患者参与，对于审慎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，但持续参与的可操作步骤并未得到明确界定。如果没有以患者为中心的测量，利益相关者可能会陷入糟糕传统评估的数字版本，并使低价值工具泛滥，这些工具无效、繁琐，还会降低临床护理和研究的质量与效率。
本文综合并定义了一个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的核心原则的顺序框架。我们提出了后续步骤，以推动高质量患者参与的科学发展，以支持数字医学时代重要的健康测量方法。
所有健康测量方法都应具有意义，无论产品的监管分类、测量类型或使用背景如何。为了评估从数字传感器获得的信号的意义，以下四级框架很有用：健康的有意义方面、感兴趣的概念、要测量的结果以及终点（仅适用于研究）。纳入患者意见是一个动态过程，需要的不仅仅是单个的、一次性的接触点，而是应该在整个测量选择过程中持续进行。我们建议开发者、临床医生和研究人员重新评估流程，以便在数字健康测量方法的开发、部署和解释中更持续地让患者参与。
