SBIR Phase II: HealthText: Providing digital healthcare navigation for underserved communities in the US

小型企业创新研究(SBIR)第二阶段项目的更广泛影响/商业潜力旨在进一步开发HealthText，这是一个人工智能(AI)驱动的数字健康信息和导航平台，专为支持Medicaid人群而定制。该项目的更广泛影响在于，它有可能通过用户友好的短信息/信息服务提供可信和相关的健康知识内容，从而解决资源不足社区的健康差距问题。由于健康和科学素养低以及不信任，资源不足的少数群体往往健康状况不佳，脱离护理。基于技术的参与战略没有充分接触到这些服务不足的人群，使HealthText成为弥合这一差距的宝贵解决方案。该项目的核心重点是直接向医疗补助受益人提供有针对性和符合文化需要的健康信息宣传活动。通过相关的内容和直观的短信，该平台旨在促进信任，增加医疗参与，并减少可避免的急诊室就诊、住院和可预防的健康相关死亡。考虑到美国每年超过7200亿美元的医疗补助市场规模，与改善服务不足和少数族裔社区的医疗保健参与度相关的商业机会是巨大的。通过解决健康素养和导航支持问题，这项技术可以帮助实现每年可超过1亿美元的大量成本节约，同时改善健康结果。该项目在医疗补助人群中展示了成功的参与结果，表明医疗补助保险公司有广泛商业化的潜力。该项目涉及使用聊天机器人和生成性人工智能等基于人工智能的通信工具来改进定制健康信息的交付。现有的人工智能资源缺乏对教育成就较低的服务不足人群中普遍存在的交流细微差别的考虑。为了解决这个问题，人工智能组件将专门为服务不足和少数族裔社区设计，从而最大限度地减少对现有健康相关人工智能解决方案中偏见的担忧。解决方案包括：1)高优先级质量指标的差距分析；2)利用定制内容和交付平台，通过文本、视频和按需AI聊天向患者发送有针对性的消息；以及3)对改善的临床结果进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project aims to further develop HealthText, an artificial intelligence (AI) driven digital health information and navigation platform tailored to support the Medicaid population. The project's broader impact lies in its potential to address health disparities in under-resourced communities by providing trusted and relatable health literacy content through a user-friendly Short Message/Messaging Service (SMS). Under-resourced and minority communities often experience poor health outcomes and disengagement from care due to low health and science literacy and distrust. Technology-based engagement strategies have not adequately reached these underserved populations, making HealthText a valuable solution to bridge this gap. The core focus of this project is to deliver targeted and culturally appropriate health information campaigns directly to Medicaid beneficiaries. Through relatable content and intuitive SMS messaging, the platform aims to foster trust, increase healthcare engagement, and reduce avoidable emergency room visits, hospital admissions, and preventable, health-related deaths. The commercial opportunity associated with improving healthcare engagement in underserved and minority communities is significant, given the annual US Medicaid market size of over $720 billion. By addressing health literacy and navigation support issues, this technology can help achieve substantial cost savings that could exceed $100 million annually, while improving health outcomes. This project has demonstrated successful engagement outcomes among Medicaid populations, suggesting the potential for widespread commercialization to Medicaid insurance companies. The project involves refining the delivery of tailored health information using AI-based communications tools like chatbots and generative AI. Existing AI resources lack consideration for communication nuances prevalent in underserved populations with lower educational achievements. To address this, the AI components will be specifically designed for underserved and minority communities, thereby minimizing concerns about bias in existing health-related AI solutions. The solution include: 1) gap analysis with high priority quality measures; 2) utilization of custom content and delivery platform to send targeted messaging via text, video, and on-demand AI chat to patients; and 3)evaluation of improved clinical outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.