Open Tools for Self-Tracking, Self Experimentation, and Patient-Provider Collaboration in Symptom Self-Management and Clinical Care

项目总结/摘要 尽管人们对自我跟踪数据的兴趣日益浓厚，以获取更完整，准确和长期的数据， 对个体健康的理解（例如，活动/症状日志、可穿戴传感器数据）、患者和 医疗服务提供者努力从这些数据中获得见解。技术往往无法带来好处，因为人们 受到数据孤岛的限制，由于其负担而放弃跟踪，无法跟踪潜在的症状触发器或相关 由于缺乏科学严谨性，得出了有缺陷的结论。供应商经常质疑数据，缺乏工具 分析它，并感到没有能力解释它。当人们寻求帮助，从提供商，商业 自跟踪工具通常缺乏对分析和解释中的共享和患者-提供者协作的支持。 长期目标是使患者和提供者能够利用自我跟踪的前所未有的潜力 数据从人口层面的理解转向自我管理和临床护理的个性化见解。 本申请的总体目标是：（1）开发支持创新和研究的开放工具， 自我管理和临床护理的自我跟踪，以及（2）通知，开发和评估这些工具， 通过自我跟踪数据寻求个性化见解的患者和提供者， 头痛和幼年特发性关节炎在五个具体的研究目标中：（1）提出开放工具 将支持端到端的自我跟踪过程，从收集到管理，再到解释多种类型的 自我追踪的健康数据(2)拟议的自我跟踪应用程序和基本工具将得到通报、开发， 并在与患者和提供者的参与性研究中进行评估，包括焦点小组、技术调查， 以及与患者和医疗服务提供者的试点研究。(3)将为自我实验开发拟议的工具支持， 帮助患者使用数据从人群水平的理解（例如，咖啡因会引发症状） 个性化的理解（例如，咖啡因是否会引起个体患者的症状）， 在与患者和提供者的参与性研究中了解，开发和评估。(4)拟议的工具支持 将开发使用自我跟踪健康数据的患者-提供者协作，支持端到端 协作规划，收集，分析和解释自我跟踪的健康数据，如知情，开发， 并在参与性研究中与患者和提供者进行评估。(5)建议的设计模式和基础 开放式工具将支持将这些创新扩展到更多的卫生领域。方法是创新的 在广泛的参与性研究中，患者和提供者检查自我跟踪健康数据的有效使用， 在肠易激综合征，慢性头痛， 青少年特发性关节炎，以及提炼设计模式以将创新扩展到新的环境中。研究 是重要的，因为新的理解和开放的工具的潜力，以改变自我跟踪的作用， 自我管理和临床护理中的健康数据，在当前研究的范围内和范围之外。

Project Summary / Abstract Despite strong and growing interest in self-tracking data to capture a more complete, accurate, and longer-term understanding of an individual's health (e.g., activity / symptom journals, wearable sensor data), patients and health providers struggle to gain insights from such data. Technologies often fail to deliver benefits, as people are limited by data silos, abandon tracking due its burdens, fail to track potential symptom triggers or relevant context, and reach flawed conclusions due to a lack of scientific rigor. Providers often question data, lack tools to analyze it, and feel unequipped to interpret it. When people seek assistance from providers, commercial self-tracking tools generally lack support for sharing and patient-provider collaboration in analysis and interpretation. The long-term goal is to empower patients and providers to leverage the unprecedented potential of self-tracking data in moving from population-level understanding to personalized insights in self-management and clinical care. The overall objective in this application is: (1) to develop open tools that support innovation and research in self-tracking for self-management and clinical care, and (2) to inform, develop, and evaluate these tools with patients and providers seeking personalized insights through self-tracking data in irritable bowel syndrome, chronic headaches, and juvenile idiopathic arthritis. In the five specific aims of the research: (1) Proposed open tools will support the end-to-end process of self-tracking, from collecting to managing to interpreting many types of self-tracked health data. (2) Proposed self-tracking applications and underlying tools will be informed, developed, and evaluated in participatory research with patients and providers, including focus groups, technology probes, and pilot studies with patients and providers. (3) Proposed tool support for self-experimentation will be developed, helping patients use data to move from population-level understanding (e.g., that caffeine can trigger symptoms) to individualized understanding (e.g., whether caffeine appears to cause this individual patient’s symptoms), as informed, developed, and evaluated in participatory research with patients and providers. (4) Proposed tool support for patient-provider collaboration using self-tracked health data will be developed, supporting end-to-end collaboration in planning, collecting, analyzing, and interpreting self-tracked health data, as informed, developed, and evaluated in participatory research with patients and providers. (5) Proposed design patterns and underlying open tools will support extension of these innovations to additional health contexts. The approach is innovative in extensive participatory research with patients and providers examining effective uses of self-tracked health data, in development of self-tracking designs in the contexts of irritable bowel syndrome, chronic headaches, and juvenile idiopathic arthritis, and in distilling design patterns to extend innovation into new contexts. The research is significant because of the potential for new understanding and open tools to transform the role of self-tracked health data in self-management and clinical care, within and well beyond the contexts of the current research.