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.

项目概要 医学营养疗法 (MNT) 是治疗 2 型糖尿病 (T2D) 的有效方法，但研究 已经表明很少有 T2D 患者坚持或接受它。利用率低的原因可能是规模较小 注册营养师 (RDN) 数量与 T2D 患者数量相比，有限 MNT 的报销途径以及患者群体的资源限制。这些问题是 由于获得护理的机会有限、经济差距和资源匮乏，拉丁裔社区的情况更加严重 适合文化认同。目前，将文化相关性纳入 MNT 计划必须手动完成 通过 RDN。现有的数字应用程序侧重于膳食跟踪或离散生物因素（例如肠道 微生物组），补充健康的生活方式而不是支持 MNT 输送，未能解决 膳食计划制定和遵守中的个人和文化因素。 YumAI 是一款基于人工智能的新型应用程序，可提供并跟踪符合 MNT 的食谱的遵守情况，这些食谱 根据预算、家庭、地点、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 通过以下方式直接为患者带来定制的、高质量的 MNT： 一种可在台式计算机和个人设备上使用的易于使用的数字应用程序。 在这个第一阶段 SBIR 项目中，我们将进一步开发这个人工智能驱动的应用程序，并结合来自 初步测试，确保符合 ADA 饮食指南和 MNT 规定，并优化 专门针对墨西哥裔 T2D 患者的软件。我们会进行两次设计思考 研讨会，以确定产品功能并发现配方定制和 MNT 合规性的因素。 通过迭代设计过程，我们将开发 YumAI 的概念验证并演示算法 支持基本配方计划定制的功能。我们的两步方法平衡了合规性 MNT 标准并内置相关因素，根据用户需求定制食谱推荐。 认识到计划定制的复杂性和遵守的可能维度的数量， 研究的目的是证明未来可以增强的解决方案的技术可行性 发展并找出数据收集方面的差距。 该项目的成功完成将产生YumAI的功能原型，这是第一个数字健康 增加墨西哥 T2D 患者获得 MNT 的机会的机制。该项目将提供证明 未来研究的概念和可行性，旨在将 YumAI 扩展到更广泛的人群。它将使我们做好准备 第二阶段项目探索与产品的原位相互作用以及产品在解决以下问题方面的功效 患者依从性、文化意识和 RDN 可扩展性。