Active Patient Participation in a Disease Registry for Comparative Effectiveness

患者积极参与疾病登记以比较有效性

基本信息

批准号：
8226504
负责人：
KENNETH D MANDL
金额：
$ 50.89万
依托单位：
BOSTON CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-06-01 至 2015-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8226504
关键词：
8 year old Adverse drug effect Adverse effects Adverse event Arthritis Back Caring Child Childhood Chronic Childhood Arthritis Clinical Code Computer software Consent Data Data Quality Data Reporting Data Sources Databases Decision Making Diffusion Disease Disease Progression Disease remission Ensure Enzymes Family Frequencies Funding Grant Health Health system Healthcare Healthcare Systems Immunosuppressive Agents Individual Infection Influenza Information Systems Institute of Medicine (U.S.)Institutional Review Boards Knowledge Learning Left Letters Life Link Liver Measurement Measures Methotrexate Metric Modeling Monitor Multicenter Studies National Institute of Arthritis and Musculoskeletal and Skin Diseases Outcome Parents Participant Pathway interactions Patient Care Patient Outcomes Assessments Patient Participation Patients Pediatric Hospitals Pharmaceutical Preparations Policies Prevalence Process Provider Public Health Published Comment Quality of Care Quality of life Reading Recommendation Recording of previous events Records Registries Reporting Research Research Infrastructure Research Project Grants Rheumatism Rheumatology Running Safety Sentinel Severities Site Symptoms TNF gene Technology Testing Training Translations United States National Institutes of Health Vaccinated Voice authority cohort comparative effectiveness data registry data sharing disease registry effectiveness research evidence base experience flu health care quality health information technology health record improved innovation meetings open source patient registry pediatrician programs response standardize measure

项目摘要

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.

描述（由申请人提供）：为了改善证据基础和护理质量，美国卫生与公众服务部 (HHS) 正在投资数亿美元用于依赖观察队列的药物监测和比较有效性研究。由于这些数据源中很大程度上缺少患者的声音，因此关键疗效终点和生活质量指标可能不会纳入临床和政策建议中。同样缺乏患者了解、能够准确报告并愿意分享的关键信息。例如，获取有关非处方药和补充药物、疾病终点以及低于典型医疗保健阈值的不良事件的数据，可以极大地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，将同意患者的声音添加到队列研究中。我们以两项广泛部署的开源技术为基础：i2b2 分析平台和 Indivo 开源个人控制健康记录。我们创建了一个支持自我延续循环的基础设施，其中共享研究信息可以推动改善护理，从而激发持续参与和进一步同意的共享，从而进一步改善研究和护理。我们将此模型称为“学习队列”(TLC)，因为参与者获得了一个工具包，可让他们直接访问查询注册数据 - 该工具包可以安全地将患者的查询能力限制为经过验证的聚合测量，并提供面向消费者的预处理、总结了与个性化健康选择密切相关的实时登记数据。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 个站点的患者登记处，该登记处覆盖了美国一半患有风湿病的儿童。该项目为标准化措施创建了一条转化为实践的途径，包括来自 NIH 患者报告结果测量信息系统 (PROMIS) 的措施，以捕获患者报告以供登记。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，该队列自动且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 开源。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 IT 高级研究项目 (SHARP) 项目 (www.SMArtPlatforms.org) 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，使我们能够为根据该提案产生的软件技术的广泛传播创建一条途径。