Improving glycemic control among underserved patients with insulin-treated type 2 diabetes through nurse-led, app-based behavioral intervention

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“Therapeutic inertia,” defined as a lack of timely adjustment to therapy when a patient’s treatment goals are not met, is a major cause of poor outcomes in Type 2 Diabetes (T2D). This is especially true for low socioeconomic status (low-SES) populations, who often face barriers to effective disease self-management at three levels: (1) patient (e.g., limited resources, low health literacy, and limited access to care); (2) clinician (e.g., lack of time and/or poor cultural sensitivity); and (3) health system (e.g., poor or absent decision support and effective patient panel management). One way to address the complex challenges of chronic disease management at these three levels is with multi-level health information technology (HIT)-supported behavioral interventions. Such interventions combine changes to clinical workflows and self-management support to help patients track diabetes electronically, transmit data to clinicians, and receive feedback for adjusting treatment. Currently, minimal data exist to inform optimal design, implementation, and use of such multi-level behavioral interventions, particularly for low-SES populations. My career goal is to establish an independently funded research program that helps decrease health disparities using technologies that support effective long-term self-management and improve outcomes. In this project, I propose a 5-year training and research plan for a multi-level app-based intervention to improve outcomes for T2D in low-SES populations. I will develop and pilot-test a nurse-led, app-based behavioral intervention consisting of three evidence-based interventions: (1) education on A1C results and goal setting via MyChart, the patient portal in the Epic electronic health record; (2) a problem-solving action plan developed by clinicians in collaboration with their patients; and (3) remote monitoring via OnTrack, a top-rated diabetes app, to analyze blood glucose and identify the need to adjust treatment. Training in population health informatics, HIT implementation science, health disparities, and pragmatic trials will not only allow me to complete the proposed project, but will set the stage for expanding the concept to other diseases and clinical use cases. Indiana University and the Regenstrief Institute, an informatics powerhouse, plus a strong team of mentors in biomedical informatics, HIT implementation, health disparity, and qualitative methods, provide an exceptional scientific environment. The proposed work includes: (1) time-to-event analysis to understand population characteristics associated with persistent therapeutic inertia, used to guide intervention development and tailoring [Aim 1]; (2) input from diabetes care team to adapt the intervention and implementation strategies to the clinical operations level [Aim 2]; (3) a focus group study with low-SES patients to help tailor the intervention [Aim 3]; and (4) a pilot study at two clinics (n=60, 30 patients per clinic) to assess the feasibility of the intervention for low-SES patients with insulin-treated T2D [Aim 4]. The project will support a future R01 application for a pragmatic trial to assess the effectiveness of a multi-level app-based behavioral intervention for low-SES populations with T2D.