Jackalope Plus tool for post-coordination, ontology development, and precise mapping in observational health studies

Abstract

Accurate mapping of complex health data to the OMOP CDM while preserving clinical nuance remains a challenge. We introduce Jackalope Plus, a novel tool leveraging SNOMED CT post-coordination and a GPT-4o mini LLM, to significantly enhance the precision and efficiency of this process. Our two-step approach combines semantic search with LLM-driven standardization, enabling accurate conversion of intricate medical concepts. Evaluation on benchmark and custom datasets demonstrates that Jackalope Plus identifies correct mappings for over 77.5% of complex terminologies, substantially outperforming Usagi (52.5%) and matching the accuracy of manual mapping while offering up to 50% time savings. Jackalope Plus offers a versatile solution for diverse healthcare data environments. Future work will focus on refining the tool through user feedback integration and addressing ambiguities in overlapping concepts. A free beta version is available for research and feedback. Ethical review confirms no storage of patient-identifiable information.