ABSTRACT
Individuals with intellectual and developmental disabilities face significant challenges in accessing and comprehending complex medical documents, contributing to health disparities and unmet healthcare needs. To address this issue an AI-driven tool (MTCAI) was developed and designed to simplify medical texts in accordance with the evidence-based Minimized Text Complexity guidelines. Unlike traditional Plain Language approaches, Minimized Text Complexity guidelines are tailored to readers with limited literacy, including those reading below a third-grade level. This study evaluated MTCAI’s effectiveness in simplifying after-visit medical summaries for adults with IDD. The project involved two phases: (1) development and refinement of MTCAI using large language models to systematically automate and apply the Minimized Text Complexity guidelines, and (2) conducting a participatory needs assessment and message testing with five adults with intellectual and developmental disabilities. Participants reviewed medical reports in both their original format and in MTCAI-simplified formats. Quantitative analyses revealed that MTCAI-generated texts significantly reduced reading complexity, achieving levels comparable to those of second-grade texts. Qualitative findings showed that all participants preferred the simplified reports, demonstrated improved comprehension, and expressed a willingness to engage with the simplified documents independently. These results suggest that MTCAI is a promising tool for enhancing health communication accessibility for individuals with intellectual and developmental disabilities. Future research should investigate broader implementation and assess the long-term effects on health outcomes.