The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop an intelligent self-management tool for the 25 million diabetes patients in the US and the 200 million diabetes patients in the world. The proposed study is consonant with the vision of ?learning health system? from the Institute of Medicine in which appropriate interfaces should be provided to engage individuals in population health monitoring and to optimize chronic disease care and control. The proposed technology (Diabetes Self-Management Dashboard) will be applicable across platforms (i.e., mobile devices and personal computers), and will incorporate novel methods that mitigate the technical limitations of existing tools. The proposed project covers the development and evaluation of the technology. Although diabetes was chosen as the research case, the project is transferable to other chronic conditions that may benefit from an intelligent self-management application.
The proposed project accentuates the inter-relationship among intelligent health IT interventions, theoretical psycho-behavioral determinants, and clinical outcome from self-care. The proposition is that through this multifaceted perspective, we may better delineate the essences in diabetes self-management, and then offer optimized social-technical support accordingly. The team intends to overcome several limitations of existing self-management tools: 1) ignoring the potential of mobile devices in self-care, 2) failing to translate self-monitoring data to patient-interpretable implications, and 3) lacking tailored educational materials and actionable recommendations. The specific technical innovations include: 1) health status monitoring and trend projection, 2) assessment and prediction of risks for major events (e.g., stroke, heart attack, and hospitalization), 3) recommendation of personalized educational materials, and 4) several social functionalities. Along with the technical innovations, we formulate comprehensive evaluation plans that critically assess the usability of the technology (via System Usability Scale and semi-structured interviews), the effectiveness of the technology (via within-subjects and between-groups design of field experiments), and the proposed theoretical model and research hypotheses (via structural equation modeling). The project is expected to result into an advanced and commecializable system is expected t is powered by scientific algorithms and motivated by relevant health behavioral theories, with systematic assessment on its usability and effectiveness.
