Wearable Technology Infrastructure to Enhance Capacity for Real-Time, Online Assessment and Mobility (ROAMM) of Intervening Health Events in Older Adults

可穿戴技术基础设施可增强老年人干预健康事件的实时在线评估和移动性 (ROAMM) 能力

• 批准号: 10609536
• 负责人: Todd Manini
• 金额: $ 67.63万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10609536
• 关键词: Acceleration; Accelerometer; Address; Adherence; Adopted; Adverse event; Advisory Committees; American; Apple watch; Area; Automobile Driving; Behavioral; Capsicum; Charge; Clinical; Cognition; Collaborations; Communities; Data; Data Collection; Data Science; Data Storage and Retrieval; Early Diagnosis; Ecological momentary assessment; Elderly; Ensure; Event; Fatigue; Fees; Florida; Focus Groups; Foundations; Frequencies; Geriatrics; Gerontology; Grant; Health; Heart Rate; Home; Hospitalization; Incidence; Infrastructure; Injury; Interview; Licensing; Life; Location; Longitudinal cohort study; Marketing; Measurement; Measures; Medical; Modeling; Monitor; Moods; Nature; Online Systems; Outcome; Pain; Participant; Patient Outcomes Assessments; Patients; Pattern; Persons; Phase; Phenotype; Physical Function; Physical activity; Prevention; Quality of life; Recording of previous events; Recovery; Remote management; Reporting; Research; Research Infrastructure; Research Personnel; Risk; Risk Factors; Safety; Science; Secure; Services; Short-Term Memory; Symptoms; System; Technology; Testing; Time; United States National Institutes of Health; Universities; Voice; Work; advanced analytics; aged; base; cognitive testing; comorbidity; cost effectiveness; data science management; data to knowledge; data visualization; demographics; depressive symptoms; disability; executive function; experience; fall injury; fall risk; falls; focus ultra; graphical user interface; informant; longitudinal, prospective study; mobile computing; mobile sensor; novel; primary outcome; processing speed; prospective; recruit; response; secondary outcome; sensor; smart watch; technology platform; therapy design; tool; usability; walking speed; wearable device; wearable monitor; week trial

ABSTRACT Older Americans experience approximately 29 million falls and 13 million hospitalizations per year. These intervening health events (IHE - episodic falls, injuries, illnesses, and hospitalizations) are strong precipitants of disability in older adults. Because of their episodic nature, IHEs are extremely difficult to study. Continuous, long-term monitoring with remote capabilities using wearable technology is an ideal solution for capturing information surrounding an IHE and in particular, preceding it. This R21/R33 project aims to develop a sustainable research infrastructure built on the foundation of a smart watch application and server called ROAMM (Real-time Online Assessment and Mobility Monitor). It will offer long-term and continuous connectivity, bidirectional interactivity and remote programming. ROAMM will create a detailed narrative about mobility (activity patterns, walking speed, life space), patient reported outcomes/symptoms (pain, poor mood, fatigue, disability), cognition (working memory, processing speed, and executive functioning) and reports of health events (falls and hospitalizations). The infrastructure is composed of a diverse group of investigators with expertise in mobile technology/data science and applied/medical sciences who will serve in the following cores: Wearable Technology, Phenotyping, Clinical Outcomes, Data Science Management & Quality, and Recruitment, Retention & Compliance. In the R21 phase, we will create the ROAMM framework consisting of the watch application and accompanying server. We will also assess test-retest reliability, convergent validity and participant usability/acceptability. Each year, an Independent Advisory Panel and External Advisory Committee will evaluate milestone-driving activities and our Go/No-Go checkpoints for transitioning to the R33 phase. Work proposed in the R33 phase will showcase the ROAMM infrastructure by conducting a prospective, longitudinal study (range 1.25-2.5 yrs) in 200 community-dwelling persons aged 70+ yrs. This phase will test a field deployable version of ROAMM in real world settings to address the following hypotheses: 1) Pre-event patterns of low mobility, disability, fatigue, pain and depressive mood collected by ROAMM are independent predictors of incident IHE's; 2) IHE's will negatively impact the course of ROAMM measures; and 3) Additional value will be gained for explaining the change variability and recovery trajectories. An exploratory aim will evaluate safety while using ROAMM features and identify predictors of ROAMM adherence using both key-informant interviews and examine demographic and health histories to create boundaries for using ROAMM and other systems like it for long-term, continuous monitoring in research and practice. We will sustain ROAMM by targeting grant opportunities for the wearable technology surge for remote patient interaction, adopting licensing fees, and aligning our services with larger entities to become the go-to place for remote data capture. These activities will create a sustainable infrastructure to ensure research on older adults is keeping pace with the state-of-the-art “smart and connected” health with wearable technology.

抽象的 美国老年人每年约有 2900 万人跌倒和 1300 万人住院。这些 干预性健康事件（IHE - 偶发性跌倒、受伤、疾病和住院治疗）是 老年人的残疾。由于其偶发性，IHE 的研究极其困难。连续的， 使用可穿戴技术进行远程监控是捕捉数据的理想解决方案 围绕 IHE 的信息，特别是其之前的信息。该 R21/R33 项目旨在开发 可持续研究基础设施建立在智能手表应用程序和服务器的基础上 ROAMM（实时在线评估和行动监测）。它将提供长期、持续的 连接性、双向交互性和远程编程。 ROAMM 将创建一个详细的叙述 流动性（活动模式、步行速度、生活空间）、患者报告的结果/症状（疼痛、情绪不佳、 疲劳、残疾）、认知（工作记忆、处理速度和执行功能）和报告 健康事件（跌倒和住院）。基础设施由不同的调查人员组成 具有移动技术/数据科学和应用/医学方面的专业知识，他们将在以下领域任职 核心：可穿戴技术、表型分析、临床结果、数据科学管理和质量，以及 招聘、保留和合规。在R21阶段，我们将创建ROAMM框架，包括 手表应用程序和随附的服务器。我们还将评估重测信度、收敛效度 和参与者的可用性/可接受性。每年，独立顾问小组和外部顾问 委员会将评估里程碑驱动活动以及我们过渡到 R33 的通过/不通过检查点 阶段。 R33 阶段提出的工作将通过进行 对 200 名 70 岁以上社区居民进行的前瞻性纵向研究（范围 1.25-2.5 岁）。这 该阶段将在现实环境中测试 ROAMM 的现场部署版本，以解决以下假设： 1) ROAMM 收集的行动不便、残疾、疲劳、疼痛和抑郁情绪的事件前模式是 事件 IHE 的独立预测因子； 2) IHE 将对 ROAMM 措施的进程产生负面影响；和 3) 解释变化变异性和恢复轨迹将获得附加价值。一个探索性的 Target 将评估使用 ROAMM 功能时的安全性，并使用两者来确定 ROAMM 依从性的预测因素 关键知情人访谈并检查人口和健康史，以设定使用界限 ROAMM 和其他类似的系统可在研究和实践中进行长期、持续的监控。我们将 通过针对远程患者可穿戴技术激增的资助机会来维持 ROAMM 互动，采用许可费，并使我们的服务与大型实体保持一致，以成为 远程数据采集。这些活动将创建可持续的基础设施，以确保对老年人的研究 正在通过可穿戴技术与最先进的“智能互联”健康保持同步。