Making Clinical Research Understandable With AI

Kim Weeks, Communication Strategist in the Office of Academic Affairs at Denver Health, joins Atom for a candid conversation on how AI can close the gap between complex clinical research and the patients it's meant to serve. In this webinar, she shares how she used AI to translate jargon-heavy clinical trial descriptions into plain language for a safety-net health system, turning invisible research into something patients can actually understand and trust. The discussion covers: How AI can standardize and simplify clinical trial descriptions for patients Why technical language creates a barrier to trust and enrollment, especially for underserved and non-English-first communities Building a strict prompting template (study, verb, object, under 20 words) to keep AI output consistent Keeping a human in the loop: catching hallucinated degrees, credentials, and study details before they go public Turning plain-language research into reach through the website and MyChart research-interest prompts Why visibility, not just enrollment, is the real measure of impact This session is especially useful for research communicators, research development and administration professionals, science communicators, and health system and university leaders looking for practical, responsible ways to make their research more accessible to the communities they serve.