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.

Public Health Relevance

Type 2 diabetes is a serious problem in the U.S. and self-management is critical to control the disease. This study will use mobile health technologies to identify strategies that help patients and health professionals use patient-generated data to help patients better self-manage and overcome challenges with diabetes. The results will serve as a cornerstone for creating tools to help patients better self-manage disease through the use of mobile health technologies and real-time patient-provider collaboration.

National Institute of Health (NIH)
National Institute of Nursing Research (NINR)
Academic Research Enhancement Awards (AREA) (R15)
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Special Emphasis Panel (ZRG1-HDM-W (81))
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Huss, Karen
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Duke University
Schools of Nursing
United States
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