Leveraging Predictive AI and LLM-Powered Trial Matching to Improve Clinical Trial Recruitment: A Usability Assessment of Trialshub

Abstract

ABSTRACT Background Recruitment remains a major barrier to timely clinical trial completion. Trialshub is an LLM-powered, chat-based platform intended to help users identify relevant trials and connect with coordinators to streamline recruitment workflows. Objective To evaluate the perceived usability and operational value of Trialshub, and identify implementation considerations for real-world deployment. Methods A usability test was conducted at Morehouse School of Medicine for the Trialshub application. Purposively selected participants included clinical research coordinators and individuals with and without clinical trial search experience. Participants completed a pre-test survey assessing demographics, digital health information behaviors, and familiarity with AI tools, followed by a moderated usability session using a Trialshub prototype. Users completed scenario-based tasks (locating a breast cancer trial, reviewing results, and initiating coordinator contact) using a think-aloud protocol. Task ratings, screen recordings, and transcribed feedback were analyzed descriptively and thematically, and reported. Results Participants reported high comfort with using digital tools and moderate-to-high familiarity with AI. Trialshub’s chat-first design, guided prompts, and checklist-style eligibility display were perceived as intuitive and reduced cognitive load. Fast access to trials and the coordinator-contact workflow were viewed positively. Key usability issues included uncertainty at step transitions, insufficient cues for selecting results and next actions, and inconsistent system reliability (loading delays, errors, and broken trial detail pages). Participants also noted redundant questioning due to limited conversational memory, requested improved filtering/sorting, and clearer calls-to-action. All participants indicated that Trialshub has strong potential to meaningfully improve clinical trial processes. Conclusions Trialshub shows promise for improving trial discovery and recruitment workflows, with identified design implications for real-world deployment.

Ähnliche Arbeiten