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

项目摘要/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、更准确、更长期的 了解个人健康状况(例如，活动/症状日志、可穿戴传感器数据)、患者和 医疗服务提供者很难从这些数据中获得洞察力。技术往往无法带来好处，因为人们 受到数据孤岛的限制，因其负担而放弃跟踪，未能跟踪潜在的症状触发因素或相关 由于缺乏科学严谨性，因此得出了有缺陷的结论。提供商经常质疑数据，缺乏工具 去分析它，却觉得自己没有能力去解释它。当人们向提供者寻求帮助时，商业 自我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变为自我管理和临床护理的个性化洞察。 此应用程序的总体目标是：(1)开发支持创新和研究的开放工具 用于自我管理和临床护理的自我跟踪，以及(2)告知、开发和评估这些工具 慢性肠易激综合征患者和提供者通过自我跟踪数据寻求个性化见解 头痛和幼年特发性关节炎。在研究的五个具体目标中：(1)提出了开放工具 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 自我跟踪的健康数据。(2)拟议的自我跟踪应用程序和基础工具将被告知、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、技术探测、 以及对患者和提供者进行的试点研究。(3)将开发用于自我试验的拟议工具支持， 帮助患者使用数据从人群层面的理解中转移(例如，咖啡因会引发症状) 对个体化的理解(例如，咖啡因是否似乎会导致个别患者的症状)，如 在与患者和提供者的参与性研究中知情、开发和评估。(4)建议的工具支持 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 在规划、收集、分析和解释自我跟踪的健康数据方面的协作，如知情的、开发的、 并在与患者和提供者的参与性研究中进行评估。(5)建议的设计模式和基础 开放工具将支持将这些创新扩展到更多的健康环境。这种方法是创新的 在患者和提供者检查自我跟踪健康数据的有效使用的广泛参与性研究中， 在肠易激综合征、慢性头痛和 青少年特发性关节炎，并在提炼设计模式，将创新延伸到新的背景下。这项研究 意义重大，因为新的理解和开放工具的潜力将改变自我跟踪的角色 自我管理和临床护理方面的健康数据，无论是在当前研究的背景之内还是之外。

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.