Improving the accessibility and relevance of Medical Nutritional Therapy among people with Type 2 diabetes in the Latino community through a customizable, AI-powered application.

通过可定制的人工智能应用程序，提高拉丁裔社区 2 型糖尿病患者医疗营养治疗的可及性和相关性。

• 批准号: 10258480
• 负责人: Shireen Abdullah
• 金额: $ 29.79万
• 依托单位: KAMIN CONSULTING, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-17 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10258480
• 关键词: Address; Adherence; Affinity; Algorithms; American; Artificial Intelligence; Awareness; Biological Factors; Budgets; Businesses; Communities; Computer software; Computers; Consult; Cost Savings; Custom; Data Collection; Development; Devices; Diabetes Mellitus; Diet Habits; Dietitian; Dimensions; Educational workshop; Ensure; Equilibrium; Family; Feedback; Food; Food Preferences; Future; Glycosylated hemoglobin A; Goals; Health Resources; Health Services Accessibility; Health behavior; Healthcare; Hispanics; In Situ; Incidence; Income; Individual; Insurance Coverage; Latino; Lead; Location; Low income; Manuals; Medical; Medical Nutrition Therapy; Mexican; Minority; Non-Insulin-Dependent Diabetes Mellitus; Not Hispanic or Latino; Nutritional Support; Nutritionist; Outcome; Participant; Pathway interactions; Patient Monitoring; Patients; Persons; Phase; Pilot Projects; Population; Preparation; Process; Recipe; Recommendation; Research; Resources; Retrospective Studies; Risk; Seasons; Small Business Innovation Research Grant; System; Technology; Testing; Thinking; Time; United States; Visit; base; classification algorithm; compliance behavior; cost effective; design; diabetes management; dietary guidelines; digital; digital health; economic disparity; effective therapy; ethnic minority population; gut microbiome; health care availability; health care service; healthy lifestyle; improved; iterative design; low socioeconomic status; meetings; novel; patient population; preference; prototype; racial and ethnic; social health determinants; success; usability

PROJECT SUMMARY Medical Nutrition Therapy (MNT) is an effective treatment for managing Type 2 diabetes (T2D), but studies have shown that few T2D patients adhere to or access it. This low utilization rate can be attributed to the small number of registered dietitian nutritionists (RDNs) compared to the number of patients with T2D, limited reimbursement pathways for MNT, and resource constraints in the patient population. These issues are exacerbated in the Latino community due to limited access to care, economic disparities, and few resources tailored to culture identity. Currently, incorporating cultural relevance into an MNT plan must be done manually by an RDN. Existing digital applications focus on meal tracking or discrete biological factors (e.g. gut microbiome), supplementing healthy lifestyles rather than supporting MNT delivery and failing to address personal and cultural factors in meal plan creation and adherence. YumAI is a novel AI-based application that delivers and tracks adherence to MNT-compliant recipes that are customized to factors such as budget, family, location, season, food preferences, and preparation complexity. By automating meal plan adjustment, YumAI brings customized, high-quality MNT directly to patients through an easy-to-use digital application available on desktop computers and personal devices. In this Phase I SBIR project, we will further develop this AI-powered application, incorporating feedback from preliminary testing, ensuring compliance with ADA dietary guidelines and MNT stipulations, and optimizing the software specifically for individuals with T2D of Mexican decent. We will conduct two design thinking workshops to identify product features and discover factors in recipe customization and MNT compliance. Through an iterative design process, we will develop a proof of concept of YumAI and demonstrate algorithmic capabilities that enable basic recipe plan customization. Our two-step approach balances compliance with MNT standards and builds in relevant factors to customize recipe recommendations to user needs. Recognizing the complexity of plan customization and the number of possible dimensions of adherence, the purpose of the research is to demonstrate technical feasibility of a solution that can be enhanced in future development and to identify gaps in data collection. Successful completion of this project will result in a functional prototype of YumAI, the first digital health mechanism for increasing access to MNT for the Mexican population with T2D. This project will provide proof of concept and feasibility for future studies to scale YumAI for a broader population. It will prepare us for a Phase II project that explores in situ interaction with the product and efficacy of the product in solving issues of and patient adherence, cultural awareness, and RDN scalability.

项目摘要 医疗营养疗法（MNT）是管理2型糖尿病（T2D）的有效治疗方法，但研究 已经表明，很少有T2D患者遵守或访问它。这种低利用率可以归因于小 与T2D患者数量相比，注册营养师营养学家（RDNS）的数量 MNT的报销途径以及患者人群的资源限制。这些问题是 由于获得护理，经济差异和很少的资源，在拉丁裔社区中加剧了 根据文化身份量身定制。目前，必须手动完成文化相关性 由RDN。现有的数字应用集中于膳食跟踪或离散的生物学因素（例如肠道 微生物组），补充健康的生活方式，而不是支持MNT交付，无法解决 进餐计划创建和依从性中的个人和文化因素。 Yumai是一种基于AI的新型应用 根据预算，家庭，位置，季节，食物偏好和准备复杂性等因素进行定制。 通过自动化膳食计划调整，Yumai通过 台式计算机和个人设备上可用的易于使用的数字应用程序。 在此阶段I SBIR项目中，我们将进一步开发此AI驱动的应用程序，并结合了 初步测试，确保遵守ADA饮食指南和MNT规定，并优化 专门针对具有T2D墨西哥体面的人的软件。我们将进行两个设计思维 讲习班以识别食谱定制和MNT合规性中的产品功能并发现因素。 通过迭代设计过程，我们将制定Yumai概念证明并演示算法 启用基本食谱计划自定义的功能。我们的两步方法平衡符合 MNT标准和建立相关因素，以自定义满足用户需求的食谱建议。 认识计划自定义的复杂性以及依从性的可能维度的数量 该研究的目的是证明可以在以后增强的解决方案的技术可行性 开发并确定数据收集的差距。 该项目的成功完成将导致Yumai的功能性原型，这是第一个数字健康 T2D墨西哥人群增加获得MNT的机制。该项目将提供证明 未来研究的概念和可行性，可为更广泛的人群扩展Yumai。它将为我们做好准备 第二阶段项目，该项目与产品在解决问题中的产品和功效的原位相互作用 以及患者的依从性，文化意识和RDN可伸缩性。