i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management

Uncontrolled Type 2 Diabetes (T2D) is a significant public health concern in the United States, especially among disadvantaged groups, with an annual economic impact of around $250 billion. Despite improvements, over 50 percent of T2D patients do not meet hemoglobin A1c (HbA1c) targets, particularly in resource-limited settings and among Black and Latino populations. Traditional self-management strategies yield modest improvements but often overlook patients' physical and psychosocial experiences. While patient-reported outcomes (PROs) are increasingly integrated to address these perspectives, many tools lack end-user involvement and technical integration, limiting their effectiveness. There is a need for mobile health solutions that provide actionable, patient-centered PROs that support real-time engagement, fit within clinical workflows, and involve both patients and providers in their development.

Researchers adapted iMatter, a text-messaging PRO tool aimed at facilitating behavior change, to the needs of providers and T2D patients. iMatter included three main components: SMS messages for real-time collection of PROs, personalized feedback and motivational texts, and dynamic visualizations of PROs presented in PDF reports that integrated into electronic health records (EHR). This design sought to enhance patient engagement and optimize diabetes management within clinical workflows.

The specific aims of the research were as follows:

• To compare the efficacy of iMatter vs. usual care (UC) on HbA1c reduction at 12-months.
• To compare the efficacy of iMatter vs. UC on adherence to self-care behaviors.
• To evaluate the potential mediators of the intervention effects on adherence to self-care and HbA1c (only if primary aim is statistically significant).

In this mixed-methods study, researchers conducted a two-phase approach, a formative phase and a clinical-efficacy phase. The formative phase aimed to ensure the intervention was tailored to user needs, emphasizing user-centered design and involving qualitative methods to adapt iMatter for T2D patients and providers, integrating it into EHRs, and evaluating usability. The clinical-efficacy phase assessed iMatter’s impact on health outcomes through a randomized control trial with primary care T2D patients that compared its effectiveness against UC in lowering HbA1c levels. Patients participating in the iMatter intervention received daily messages that evaluated key health metrics, including sleep quality, physical activity, diet, and medication adherence. Additionally, they received weekly messages that assessed their diabetes management, quality of life, and progress toward personalized health goals. Patients randomized to the UC group received standard diabetes treatment recommendations as determined by their primary care physician.

The research findings showed that there was no statistically significant difference in HbA1C reduction between the intervention and control groups at 12 months. Notably, the only self-care behavior change that reached significance was a decrease in smoking status in the intervention group. These results highlight that even with the incorporation of end-user feedback in the design, traditional intervention models may still fall short in producing meaningful clinical outcomes for individuals with T2D. These findings underscore the need for future studies to explore tailored interventions that actively collect and share PROs, potentially improving the effectiveness of digital health solutions in diabetes management.

The team has been funded for follow-up research to add artificial intelligence (AI)-supported tools to iMatter to create iMatter2. Enhancements will include an interactive dashboard with PROs and HbA1c data visualizations, clinical decision support tools, behavioral 'nudging' to prompt providers to review the PRO data, and an AI chatbot delivering two-way digital messages that allows patients to share their PROs and receive personalized motivational and educational messages.