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This paper presents a formative study using a two-stage LLM pipeline (Gemini 2.5 Pro and Flash) to detect internal documentation inconsistencies in electronic health records, analyzing 3,000 discharge summaries and proposing a graded ontology for categorizing inconsistencies.