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The vast majority of research in computer assisted medical coding focuses oncoding at the document level, but a substantial proportion of medical coding inthe real world involves coding at the level of clinical encounters, each ofwhich is typically represented by a potentially large set of documents. Weintroduce encounter-level document attention networks, which use hierarchicalattention to explicitly take the hierarchical structure of encounterdocumentation into account. Experimental evaluation demonstrates improvementsin coding accuracy as well as facilitation of human reviewers in their abilityto identify which documents within an encounter play a role in determining theencounter level codes.

Assigning Medical Codes at the Encounter Level by Paying Attention to Documents