From Episodic to Real-Time Care in Diabetes Self-Management

 描述（由申请人提供）：自我管理是控制2型糖尿病（T2 DM）的组成部分。然而，有效的自我管理需要实时的健康状况和行为信息，以及在患者监测和执行自我管理时持续的健康专业人员协助。目前的医疗保健系统明显缺乏这些活动的准确、及时的信息。提供实时数据将有助于患者及其护理提供者更好地了解疾病动态，开发自适应方法来改善健康结果，并在最需要的时间和地点提供个性化护理。 新兴的移动的医疗技术可以通过捕获糖尿病相关数据并直接向患者提供反馈，促进糖尿病患者的适应性自我管理。与患者和医疗保健提供者实时共享这些数据可以促进协作工作，并在患者最需要的时候将护理服务从不频繁的偶发护理服务转变为实时护理。然而，到目前为止，我们对如何支持患者使用来自移动的技术的数据进行实时护理知之甚少，也不知道患者将跟踪多种类型的糖尿病相关数据多久。此外，我们不知道什么策略可以最好地帮助患者利用自我生成的糖尿病相关数据克服自我管理挑战，或者提供者如何最有效地指导患者更好地实时自我管理。 我们提出了一项混合方法的探索性研究，研究对象是来自初级保健诊所的50名诊断为T2 DM的患者;他们将被要求使用无线体重秤、电话连接血糖仪、腕戴式加速度计（即，Fitbit.），和药物依从性短信调查这些设备产生的数据将被绘制成轨迹，这将有助于我们了解患者在自我管理中面临的适应性挑战。在6个月内，将每月对一部分患者进行访谈，以讨论他们在糖尿病自我管理方面的适应性挑战和成功。在6个月的数据收集期之后，我们将与提供者进行焦点小组讨论，探讨如何利用自我监测数据进行协作，以自我管理糖尿病，并应对糖尿病自我管理方面的真实的挑战。

 DESCRIPTION (provided by applicant): Self-management is integral to control of type 2 diabetes mellitus (T2DM). Effective self-management however, requires real-time information on health status and behaviors and ongoing health professional facilitation of patients as they monitor and perform self-management. Accurate, timely information for these activities is notably absent from the current healthcare system. Providing real-time data would help patients and their care providers better understand illness dynamics, develop adaptive approaches to improve health outcomes, and deliver personalized care when and where it is most needed. Emerging mobile health technologies may facilitate adaptive self-management by patients with diabetes by capturing diabetes-related data and providing feedback to patients directly. Sharing these data in real-time with the patient and healthcare provider can foster collaborative work and change care delivery from infrequent episodic care delivery to real-time care at the point in time when patients need it most. However, to date we have little knowledge of how to support patients to use data from mobile technologies for real-time care and do not know how long patients will track multiple types of diabetes-related data. Moreover, we do not know what strategies will best help patients overcome self-management challenges using self-generated diabetes-related data or how providers might most effectively guide patients to better self-manage in real-time. We propose a mixed-methods exploratory study of 50 patients from a primary care clinic with a diagnosis of T2DM; they will be asked to track relevant clinical data over 6 months using a wireless body scale, phone-tethered glucometer, a wrist-worn accelerometer (i.e., Fitbit.), and a medication adherence text message survey. Data generated from the devices will be plotted as trajectories that will help us to understand the adaptive challenges that patients face in self-management. A subset of patients will be interviewed at monthly intervals over the 6 months to discuss their adaptive challenges and successes in diabetes self- management. Following the 6-month data collection period, we will conduct focus groups with providers to explore ways to address collaborative work to self-manage diabetes using self-monitoring data, and meet real- time challenges in diabetes self-management.