Building and InnovatinG: Digital heAlth Technology and Analytics (BIGDATA)

建设和创新：数字医疗技术和分析 (BIGDATA)

• 批准号: 10704045
• 负责人: JEFFREY R. CURTIS
• 金额: $ 74.27万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10704045
• 关键词: ARHGEF5 gene; Alabama; Big Data; Bioinformatics; Biological Specimen Banks; Biomedical Research; Biometry; Businesses; Clinical; Clinical Data; Clinical Immunology; Clinical Informatics; Clinical Investigator; Clinical Research; Clinical Sciences; Clinical Trials; Collaborations; Collection; Communities; Data; Data Analytics; Data Sources; Development; Devices; Diagnosis; Electronic Health Record; Environment; Epidemiology; Fostering; Funding; Future; Genetic; Goals; Health Information System; Health Technology; Health care facility; Healthcare; Immune System Diseases; Industry; Informatics; Information Services; Institution; Light; Link; Medicine; Methodology; Methods; Mission; Musculoskeletal Diseases; National Institute of Arthritis, and Musculoskeletal, and Skin Diseases; Patient-Focused Outcomes; Patients; Registries; Research; Research Personnel; Research Support; Resources; Rheumatism; Rheumatology; Services; Technology; Training; Translational Research; Universities; advanced analytics; base; care delivery; clinical center; community engagement; comparative effectiveness; comparative safety; computer science; data warehouse; design; digital health; digital technology; health data; health economics; health information technology; health plan; implementation science; improved outcome; innovation; mHealth; member; mobile computing; multidisciplinary; pragmatic trial; skin disorder; smartphone application; social media; success; tool; translational research program; translational scientist; wearable sensor technology

Project Summary The Division of Clinical Immunology and Rheumatology at the University of Alabama at Birmingham (UAB) has long been recognized as an innovative institution advancing clinical and translational research in the study of rheumatic, immunologic, musculoskeletal, and skin diseases. However, there is growing recognition that some of the transformative, technologic advances in business and industry have not been effectively applied to medicine, nor efficiently integrated within clinical environments to support state-of-the-art biomedical research consistent with the NIAMS mission. The future of medicine, particularly clinical research, will see considerable care delivery outside the confines of traditional health care facilities, using data captured by mobile technology including Smartphone Apps and wearable biosensor devices. Our UAB team has developed expertise in many domains of applied health information technology (HIT). Therefore we propose the Building and InteGrating Digital heAlth Technology and Analytics (BIGDATA) Core Center for Clinical Research (CCCR) to harness these technologies and make them available to support a broad base of investigators both within the institution, and externally. We will combine Core capacities with our multiple, leveraged institutional resources to support research relevant to the NIAMS mission. These include the UAB Center for Clinical and Translational Science and its Partner Network that includes Auburn University (a collaborating institution in this application), the UAB Informatics Institute, our Health System Information Services, electronic health record and data warehouse, and collaborative institutional research centers whose members will make up a large portion of our user base. Encompassing three distinct and synergistic cores (the Data Capture and Integration [DCI] Resource Core, Methodologic, and Administrative), all aligned around the theme of mobile and digital health, informatics, real- world data and advanced analytics, the BIGDATA CCCR will bring innovative HIT tools and methods to the research community to effectively advance the NIAMS mission through the following Specific Aims: Aim 1: Promote outstanding, innovative, and synergistic rheumatologic and musculoskeletal disease-focused research and expedite clinical, translational and informatics-related projects at the University of Alabama at Birmingham through the utilization of our Methodologic Core composed of a diverse team with expertise in biostatistics, bioinformatics, clinical informatics, statistical genetics, epidemiology, computer science, health economics, and implementation science; Aim 2: To foster the development, refinement, and application of existing and de novo digital technology data capture and analysis tools integrated with traditional data sources to advance research in rheumatologic and musculoskeletal diseases through our Data Capture and Integration Core (DCI); Aim 3: To promote the training of both junior and established clinical and translational investigators in the current methods of clinical informatics and digital health tools applicable to the NIAMS mission through diverse enrichment activities overseen by our Administrative Core.

项目摘要 阿拉巴马大学伯明翰分校(UAB)临床免疫学和风湿病学部 长期以来一直被认为是推动临床和翻译研究的创新机构 风湿性、免疫性、肌肉骨骼和皮肤病。然而，越来越多的人认识到，一些人 在变革性的商业和工业技术进步中，没有有效地应用于 医学，也没有有效地整合到临床环境中，以支持最先进的生物医学研究 与NIAMS的任务一致。医学的未来，特别是临床研究，将看到相当大的 使用移动技术捕获的数据提供传统医疗设施之外的医疗服务 包括智能手机应用和可穿戴生物传感器设备。我们的UAB团队已经在许多方面开发了专业知识 应用卫生信息技术(HIT)领域。因此，我们提出了构建和整合 数字健康技术和分析(BigData)临床研究核心中心(CCCR) 这些技术并使其可用于支持机构内广泛的调查人员基础， 和外部。我们将把核心能力与我们的多种杠杆机构资源结合起来，以支持 与NIAMS任务相关的研究。其中包括UAB临床和翻译科学中心 及其合作伙伴网络，其中包括奥本大学(本申请中的合作机构)、UAB 信息学研究所、我们的卫生系统信息服务、电子健康记录和数据仓库、 以及协作机构研究中心，其成员将占我们用户基础的很大一部分。 包括三个不同的协同核心(数据捕获和集成[DCI]资源核心、 方法论和管理学)，都围绕移动和数字健康、信息学、实时- 世界数据和高级分析，BigData CCCR将为 研究界通过以下具体目标有效推进NIAMS任务：AIM 1：促进突出、创新和协同的风湿病和肌肉骨骼疾病 阿拉巴马大学的临床、翻译和信息学相关项目的研究和加速 伯明翰通过利用我们的方法核心，该核心由一个具有以下专业知识的不同团队组成 生物统计学、生物信息学、临床信息学、统计遗传学、流行病学、计算机科学、卫生 经济学和实施科学；目标2：促进开发、改进和应用 与传统数据源集成的现有和全新的数字技术数据捕获和分析工具 通过我们的数据采集和数据采集来推进风湿病和肌肉骨骼疾病的研究 整合核心(DCI)；目标3：促进初级和已建立的临床和翻译培训 研究人员在临床信息学和数字健康工具的当前方法适用于NIAMS 通过由我们的行政核心监督的各种浓缩活动，执行特派团的任务。

项目成果

Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data: Longitudinal Observational Study.

使用活动跟踪器数据来对自我报告的类风湿关节炎健康评分进行分类的机器学习方法：纵向观察研究。

• DOI: 10.2196/43107
• 发表时间: 2023-06-26
• 期刊: JMIR FORMATIVE RESEARCH
• 影响因子: 2.2
• 作者: Rao, Kaushal;Speier, William;Meng, Yiwen;Wang, Jinhan;Ramesh, Nidhi;Xie, Fenglong;Su, Yujie;Nowell, W. Benjamin;Curtis, Jeffrey R.;Arnold, Corey
• 通讯作者: Arnold, Corey

Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study.

• DOI: 10.2196/44034
• 发表时间: 2023-11-07
• 期刊: JMIR HUMAN FACTORS
• 影响因子: 2.7
• 作者: Nowell, William B.;Curtis, Jeffrey R.;Zhao, Hong;Xie, Fenglong;Stradford, Laura;Curtis, David;Gavigan, Kelly;Boles, Jessica;Clinton, Cassie;Lipkovich, Ilya;Venkatachalam, Shilpa;Calvin, Amy;Hayes, Virginia S.
• 通讯作者: Hayes, Virginia S.

Remote Therapeutic Monitoring in Rheumatic and Musculoskeletal Diseases: Opportunities and Implementation.

风湿病和肌肉骨骼疾病的远程治疗监测：机会和实施。

• DOI: 10.18103/mra.v11i7.2.3957
• 发表时间: 2023
• 期刊: Medical research archives
• 作者: Nowell,WBenjamin;Curtis,JeffreyR
• 通讯作者: Curtis,JeffreyR

Real-World Sarilumab Use and Rule Testing to Predict Treatment Response in Patients with Rheumatoid Arthritis: Findings from the RISE Registry.

• DOI: 10.1007/s40744-023-00568-8
• 发表时间: 2023-08
• 期刊: RHEUMATOLOGY AND THERAPY
• 影响因子: 3.8
• 作者: Curtis, Jeffrey R.;Yun, Huifeng;Chen, Lang;Ford, Stephanie S.;van Hoogstraten, Hubert;Fiore, Stefano;Ford, Kerri;Praestgaard, Amy;Rehberg, Markus;Choy, Ernest
• 通讯作者: Choy, Ernest

The Art of Communicating Risk and Benefit to Promote Shared Decision-Making, Informed by Behavioral Economic Principles.

根据行为经济学原理，沟通风险和利益以促进共同决策的艺术。

• DOI: 10.1002/art.42742
• 发表时间: 2024
• 期刊: Arthritis & rheumatology (Hoboken, N.J.)
• 作者: Curtis,JeffreyR;Fraenkel,Liana
• 通讯作者: Fraenkel,Liana