564-P: Insights into How Health Technologies Can Support Patient-Centered Diabetes Self-Management—A Mixed-Methods Approach

Background & Objective: New technologies like mobile applications (apps), activity trackers, and continuous glucose monitors (CGM) are available to support people with diabetes (PWD), but it is not clear how these tools are currently used together for diabetes self-management (DSM). This mixed methods study assessed how PWD use technology to relate diabetes self-care behaviors to DSM goals.

Methods: Sixty-one adults aged 18-75 with type I or II diabetes (DM) who used ≥1 diabetes medication were surveyed about health app and monitor use (glucose, food, exercise/activity, weight, sleep, and stress trackers) as well as digital and general health literacy. 18 survey respondents completed semi-structured interviews examining how technologies were and could be used in daily DSM.

Results: Survey respondents were 34% African American and 38% female, 48% were >45 years old. Regarding DM type and treatment, 72% had Type II diabetes, 59% used insulin, and 56% had used CGMs. Participants had high levels of digital and general health literacy. For tech use, 87% of respondents used ≥1 health app; 59% had used an activity tracker; and 47% had used apps to track ≥3 separate health behaviors. While glucose-tracking apps were more common among CGM (92%) and insulin users (100%), survey respondents used other health apps at similar rates regardless of CGM (57% vs. 60%) or insulin status (61% vs. 60%). Interviewees described using glucose-tracking apps to personalize dietary choices, but less often reported using data from other health apps or monitors for DSM goals. For data to be helpful for DSM, interviewees desired data that was passively collected, easily integrated across monitors, easily visualized, and tailorable to personal health goals.

Conclusion: PWD reported using apps to monitor multiple behaviors that impact DSM. Findings suggest that there are untapped opportunities to integrate diabetes apps with trackable lifestyle data to support patient-centered DSM.