The Landscape of Documentation Failure: Error Typologies, Temporal Dynamics, and Linguistic Patterns in Hospital Recordss in Academic Writing - Guofang, Lie; Ruiliy, Zhang (Mutiara Intelektual Indonesia Press, 2025)
Clinical documentation failures remain a critical patient safety threat despite widespread electronic health record (EHR) adoption. Yet, the underlying linguistic mechanisms and temporal dynamics driving high-severity errors are poorly understood. This mixed-methods study characterized high-severity documentation failures across three tertiary hospitals, integrating multivariate logistic regression for risk quantification with qualitative discourse analysis and temporal mapping. We analyzed 60 cases using the Documentation Failure Severity Index (DFSI). Omission errors were the most prevalent (38%) and conferred the highest risk of severe adverse outcomes (adjusted odds ratio [aOR] = 3.12, p = 0.001). Crucially, ambiguous negation (e.g.,