Episodic to Real-Time Care in Diabetes Self-Management

This study will use mobile health technologies to provide everyday data to help patients and their care providers better understand illness dynamics and develop adaptive approaches to improve health outcomes in diabetes. Specifically, the study will identify strategies to help patients adapt using multiple types of self-generated diabetes-related data and help providers guide patients to better self-manage in real-time, when guidance is needed most.

The investigators will conduct a mixed-methods exploratory designed study and recruit 60 adult patients (age ≥ 18) with type 2 diabetes who will track relevant clinical data over 6 months. Participants will be asked to use a wireless glucose monitor, a cellular body scale, and a wrist-worn accelerometer, and respond to short bi-weekly text message-based surveys on medication adherence for 6 months. Data generated from the devices will be plotted as trajectories that will allow us to conduct trajectory analyses and identify missing data points and trends leading to attrition, in order to assess the feasibility of having patients engage in this type of self-monitoring for 6 months. A subset of 20 patients will be interviewed via telephone at the end of their 6 month self-monitoring period to discuss their adaptive challenges and successes over the study period. The investigators will present the trajectories of their data during patient interviews using a visual that we will e-mail or postal mail, depending on patient preference. This will facilitate discussion of the challenges participants face in self-management and adaptive practices participants use. Following the 6 months of self-monitoring, we will conduct interviews with health care providers in which the investigators will present the data trajectories and explore ways to achieve continual communication and address real-time challenges with diabetes self-management.

Number of participants with type II diabetes who adhere to using mobile technologies to self-monitor multiple types of diabetes-related data

Explore the adaptive challenges of patients self-managing diabetes, using monthly interviews over 6 months.

Data generated from the phone-tethered glucose monitor and plotted as a trajectory over a 6 month period

Explore health care providers' perspectives on using real-time data, by conducting one-time, individual interviews over a 2 month period.

Explore ways to achieve continual communication that addresses real-time challenges with diabetes self-management while presenting data trajectories during provider interviews.

Inclusion Criteria: ≥18 years old able to speak and read English diagnosed with type 2 diabetes mellitus told by their primary care provider to monitor their blood sugar daily owning and using a smart phone capable of giving informed consent with no pre-existing severe medical condition(s) that would interfere with study participation (e.g., renal failure, severe orthopedic conditions or joint replacement scheduled within 6 months, paralysis, or cancer) Exclusion Criteria: active dementia or psychiatric illness reside in a nursing home participating in another self-management study