An Intelligent Trial Eligibility Screening Tool Using Natural Language Processing With a Block-Based Visual Programming Interface: Development and Usability Study

Abstract

The iTEST demonstrated superior performance in clinical trial eligibility screening, delivering improved accuracy, reduced completion time, lower cognitive workload, and better usability when evaluating preconfigured eligibility rules. The improved accuracy is critical for patient safety, as the misidentification of eligibility criteria could expose patients to inappropriate treatments or exclude them from beneficial trials. The adaptability and ability of the iTEST to process both structured and unstructured data make it valuable for time-sensitive scenarios and evolving research protocols. Future research should evaluate clinicians' ability to create and modify eligibility rules using the block-based authoring interface, as well as assess the iTEST across diverse types of clinical trials and health care settings.

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