Towards Error-Free EHRs: Reasoning-Intensive Consistency Verification Between Clinical Notes and Structured Tables in Electronic Health Records
Abstract
Data consistency between unstructured clinical notes and structured tables in Electronic Health Records (EHRs) is essential for patient safety. However, existing work on note-table consistency verification mainly relies on surface-level matching of numeric values or simple events. Such approaches fail to capture the reasoning underlying real-world EHR documentation, including clinical interpretation, event relations, and temporal changes. To address this gap, we introduce EHR-ReasonCon, a reasoning-intensive benchmark for note-table consistency verification. Built on MIMIC-III with expert-guided annotations, it comprises 8,048 entities and provides high-quality ground-truth labels. Our evaluation using expert-validated LLM-as-a-judge metrics reveals the challenging nature of this task; even CheckEHR, the current state-of-the-art in consistency checking, struggles to perform effectively on this benchmark.