STTR Phase I: The Development and Evaluation of an Intelligent Diabetes Self-Management Tool

这个小企业技术转让（STTR）第一阶段项目的更广泛的影响/商业潜力是为美国2500万糖尿病患者和世界2亿糖尿病患者开发智能自我管理工具。拟议的研究是一致的愿景？学习卫生系统？其中应提供适当的接口，使个人参与人口健康监测，并优化慢性病的护理和控制。拟议的技术（糖尿病自我管理仪表板）将适用于跨平台（即，移动的设备和个人电脑），并将纳入新的方法，减轻现有工具的技术限制。拟议的项目包括技术的开发和评估。尽管选择糖尿病作为研究案例，但该项目可以转移到其他可能受益于智能自我管理应用程序的慢性病。拟议的项目强调了智能健康IT干预、理论心理行为决定因素和临床结果之间的相互关系自我保健。我们的主张是，通过这种多方面的视角，我们可以更好地描绘糖尿病自我管理的本质，然后提供相应的优化社会技术支持。该团队打算克服现有自我管理工具的几个局限性：1）忽视移动的设备在自我护理中的潜力，2）未能将自我监测数据转化为患者可解释的含义，3）缺乏量身定制的教育材料和可操作的建议。具体技术创新包括：1）健康状况监测和趋势预测，2）重大事件风险评估和预测（如，中风、心脏病发作和住院治疗），3）个性化教育材料的推荐，以及4）若干社交功能。沿着技术创新，我们制定了全面的评估计划，批判性地评估技术的可用性（通过系统可用性量表和半结构化访谈），技术的有效性（通过受试者内和组间设计的现场实验），以及提出的理论模型和研究假设（通过结构方程模型）。该项目预计将产生一个先进的和可商业化的系统，预计将由科学算法驱动，并以相关的健康行为理论为动力，并对其可用性和有效性进行系统评估。

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.