BD Spokes: SPOKE: SOUTH: Large-Scale Medical Informatics for Patient Care Coordination and Engagement

该项目汇集了六所大学，以设计和构建一个以患者为中心的个性化医疗系统，以解决医疗信息分散的性质，以及个人在自己的医疗保健中缺乏参与的问题。通过利用正在创建的关于我们环境的海量信息，通过融合实时、移动和可穿戴设备以及关于患者行为的丰富社交媒体数据，该团队将创建一幅详细而全面的患者健康图景，并创建一个帮助管理患者与其医疗保健提供者互动的工具。该系统有四个关键目标：(1)提供一种以人为中心的方法，将传统方法产生的电子健康记录数据与“野外”收集的数据(如个人健身设备、手机使用情况、当地天气、污染甚至快餐店地图等)整合在一起；(2)开发一个框架，以决定哪些数据来源是可信的；(3)创建一个基于云的系统，允许用户查看和跟踪他们自己的数据随着时间的推移，并改善医疗保健结果；以及(4)提供教育推广和社区参与，特别是在少数群体中，以设计一个短期(通过就业和教育)和长期(通过增加参与和信任)使用户受益的系统。该项目将利用现代基于云的分布式计算基础设施(包括移动电话和亚马逊网络服务)，以及南方BD中心的独特能力，以存储和分析人们每天产生的大量与健康相关的数据，以及他们的环境。通过将电子病历、外部数据库和从患者的互联网设备上获得的“野外”数据联系起来，该项目将解决与整合高分辨率数据以对患者进行纵向跟踪相关的几个问题。这些因素包括技术的可接受性，特别是弱势群体的可接受性、可用性、收集的数据的准确性以及跨大型异质环境的可扩展性/集成。通过采用以患者为中心的敏捷开发，该团队将与社区合作实施基于云的架构，以改进对研究参与者的跟踪，提高数据捕获的易用性，改善患者参与度，并促进护理协调。由此产生的平台将整合大数据分析、实时可扩展数据收集和关于患者行为的社交媒体分析，以分析处于不利地位的非裔美国人和西班牙裔患者群体的心血管疾病结果。此外，该团队将实施数据融合技术，以确保收集的不同质量数据的准确性，并开发机器学习模型来识别高危患者群体，以减少健康差距。最后，将测量患者参与度和健康结果，以评估该系统的有效性和成功。

This project brings together six universities to design and construct a patient-focused and personalized health system that addresses the fractured nature of healthcare information, and the lack of engagement of individuals in their own healthcare. By taking advantage of the enormous amount of information being created about our environment, through the confluence of real-time, mobile and wearable devices and the availability of rich social media data on patient behavior, the team will create a detailed and comprehensive picture of a patient's health, and a tool to help manage patients' engagement with their health care providers. The system has four key aims to: (1) provide a human-centered approach for integrating electronic health record data generated by traditional methods with data collected "in the wild" (such as personal fitness devices, mobile phone usage, local weather, pollution or even fast food restaurant maps, etc.); (2) develop a framework for deciding which data sources are trustworthy; (3) create a cloud-based system to allow users to view and track their own data over time and improve healthcare outcomes; and (4) provide educational outreach and community participation, particularly in minority populations, to design a system which benefits users in both the short term (through employment and education) and the long term (through increased engagement and trust).This project will leverage modern distributed cloud-based computing infrastructure (including mobile phones and Amazon Web Services), and the unique capacities of the South BD Hub to house and analyze the enormous volumes of health-related data that are generated every day by people, and their environment. By linking electronic medical records, external databases and data 'in the wild' harvested from patient's Internet-enabled devices, the project will address several issues related to the integration of high-resolution data for longitudinal tracking of patients. These include acceptability of the technology, particularly by vulnerable groups, usability, veracity of data collected, and scalability/integration across a large heterogeneous landscape. By employing patient-centric agile development, the team will work with communities to implement a cloud-based architecture to improve tracking of study participants, increase the ease with which data can be captured, improve patient engagement, and facilitate care coordination. The resultant platform will integrate big data analytics, real time scalable data collection, and social media analytics on patient behavior to analyze cardiovascular disease outcomes among disadvantaged African American and Hispanic patient populations. Additionally, the team will implement data fusion techniques to ensure the veracity of the varying qualities of data collected, and develop machine learning models to identify at-risk patient populations in order to reduce health disparities. Finally, patient engagement and health outcomes will be measured to assess the validity and success of the system.