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We explore how nephrology documentation can be both clinically faithful and coder-ready, focusing on AKI vs ATN, linking diagnoses to causes, and reducing avoidable queries. We share practical tactics, from lab trend interpretation to medication reviews, and reflect on AI’s place alongside physician judgment.

• AKI and ATN terminology
• Linking diagnoses to clear etiologies
• Education tactics that make codable language second nature
• Respecting clinical judgment when criteria feel incomplete
• Lab and urine trends that signal early kidney injury
• Medication-induced nephrotoxicity as a reversible cause
• ICU triggers, systemic diseases, and combo codes
• Templates, AI assistance, and human oversight