SBIR-STTR Award

The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to provide underserved Medicaid patients with accurate and culturally relevant medical advice outside of a standard healthcare setting. This population often lacks access to timely medical advice and this contributes to further health inequalities and unnecessary rising Medicaid costs. Medicaid patients may be less likely to engage with medical personnel face-to-face for fear of exorbitant out-of-pocket expenses. The proposed mobile text-based solution will provide cost-free and culturally relevant health advice. Proper and timely engagement will result in better outcomes for patients and potentially reduce unnecessary trips to the emergency room for routine care. Currently, there is no firmly established text-based health solution for Medicaid patients. This service will be a key factor in enabling the organization’s objective to increase health literacy in underserved populations. This Small Business Innovation Research (SBIR) Phase I project will develop a culturally-appropriate, text-based, digital platform designed exclusively for Medicaid beneficiaries and underserved populations who have largely been omitted from digital health innovation. This project’s research objective is to examine the receptiveness of the underserved population to this method of health information delivery and healthcare navigation support. This study will explore patient engagement with a healthcare navigator using text messaging. The data will be analyzed for speech and content patterns needed to create an easily accessible artificial intelligence (AI) tool designed specifically for Medicaid and other patients from underserved communities. The data generated from this project will also be useful for researchers to refine methods to recruit underserved, black and Hispanic communities for clinical trials and public health research studies. 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.

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.