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