Active Patient Participation in a Disease Registry for Comparative Effectiveness

描述（由申请人提供）： 为了改善证据基础和护理质量，HHS正在投资数亿美元用于药物监测和依赖于观察队列的比较有效性研究。由于患者的声音在这些数据源中很大程度上缺失，因此关键疗效终点和生活质量指标可能不会影响临床和政策建议。同样缺乏的是患者知道、可以准确报告并愿意分享的关键信息。捕获关于例如非处方药和补充药物、疾病终点和低于典型医疗保健遭遇阈值的不良事件的数据，可以大大增强对疾病进展和最佳实践的了解。我们寻求开发有针对性的HIT和计算方法，以将同意患者的声音添加到队列研究中。我们建立在两个广泛部署的开源技术上-i2 b2分析平台和Indivo开源个人控制健康记录。我们创建了一个基础设施，支持一个自我延续的循环，在这个循环中，共享的研究信息推动了护理的改善，这激励了持续的参与和进一步的同意共享，从而进一步改善了研究和护理。我们称此模型为“学习队列”（TLC），因为参与者获得了一个工具包，可直接访问查询注册表数据-该工具包安全地将患者的查询能力限制在经验证的综合指标上，并提供面向消费者的预处理演示，总结了与个性化健康选择密切相关的实时注册表数据。该机构是儿童关节炎和风湿病研究联盟（CARRA）及其可扩展的60个地点的患者登记处，该登记处可以访问美国一半的风湿病儿童。该项目为标准化措施创建了一个从实践到实践的途径，包括来自NIH患者报告结局测量信息系统（PROMIS）的标准化措施，以获取注册的患者报告。此外，我们为患者提供PCHR“应用程序”，使他们能够同意加入分布式队列，该队列自动匿名地与公共卫生当局共享数据和观察结果，以进行上市后监测。所有软件代码将通过www.INDIVOhealth.org和www.i2b2.org开放源代码。该项目利用了国家卫生信息技术协调员办公室资助的战略卫生信息技术高级研究项目（SHARP）项目（www.SMArtPlatforms.org）下产生的技术。SMART提供了一个通用的应用程序编程接口，使HIT平台能够运行可替代的应用程序，使我们能够为广泛传播本提案所产生的软件技术创造一条途径。

DESCRIPTION (provided by applicant): To improve the evidence base and quality of care, HHS is investing hundreds of millions of dollars in medication surveillance and comparative effectiveness research that relies on observational cohorts. Because the voice of the patient is largely missing in these data sources, key efficacy endpoints and quality of life metrics may not factor into clinical and policy recommendations. Also absent is key information that patients know, can accurately report, and are willing to share. Capturing data about, for example, over-the-counter and complementary medications, disease endpoints, and adverse events below threshold for a typical healthcare encounter, may greatly enhance knowledge of disease progression and best practices. We seek to develop targeted HIT and computational approaches to add the voice of the consented patient to cohort research. We build on two widely deployed open source technologies-the i2b2 analytic platform and the Indivo open source personally controlled health record. We create an infrastructure supporting a self-perpetuating cycle where shared information for research drives improved care, which motivates sustained engagement and further consented sharing, thus, further improving research and care. We call this model "The Learning Cohort" (TLC) because participants are given a toolkit providing them direct access to query registry data - a toolkit which safely constrains a patient's query capability to validated aggregate measures and offers a consumer-oriented presentation of preprocessed, summarized live registry data germane to personalized health choices. The setting is the Childhood Arthritis and Rheumatology Research Alliance (CARRA) and its scalable, 60 site patient registry which has access to half of all US children with rheumatic diseases. The project creates a translation-to-practice pathway for standardized measures including those from the NIH Patient Reported Outcomes Measurement Information System (PROMIS) to capture patient reports for the registry. Further, we provide patients with a PCHR "app" enabling them to consent to join a distributed cohort, which automatically and anonymously shares data and observations with public health authorities for postmarketing surveillance. All software code will be made open source through www.INDIVOhealth.org and www.i2b2.org. This project leverages technology produced under an Office of the National Coordinator of Health Information Technology- funded Strategic Health IT Advanced Research Projects (SHARP) project (www.SMArtPlatforms.org). SMART, which provides a common application programming interface enabling HIT platforms to run substitutable apps, allows us to create a pathway for wide diffusion of the software technology produced under this proposal.