AAMC 2026 Emerging Technologies for Teaching and Learning: Digital Demonstrations Virtual Conference.

AI-Assisted Patient Education & eConsent Readability

Presented research on the use of artificial intelligence to improve the readability and accessibility of patient-facing healthcare documents, including informed consent materials. The project explored how AI can enhance patient understanding while maintaining clinical and regulatory accuracy, using established evaluation frameworks such as PEMAT and readability metrics (e.g., Flesch Reading Ease, SMOG). Key contributions included: Designing and demonstrating an AI-assisted approach to simplifying complex healthcare content Evaluating readability and patient comprehension outcomes Translating technical and regulatory requirements into patient-centered language Presenting findings to a national audience in health informatics This work supports broader efforts to improve health literacy, patient engagement, and equitable access to healthcare information. This project reflects my broader interest in bridging clinical technology, research, and human-centered design to improve healthcare communication and outcomes.