Abstract: Systems and methods for using NLP techniques to improve search engine results for computer-assisted coding. The method includes building a search index for each of the concepts of a health care-related code set, separately or in parallel building a query comprising data from concepts and/or lexicals of a second health care-related code set, pre-processing the data elements derived from each code set, applying a natural language processor to one or both sets of data to generate the search index and the query, inputting the query into a search engine to evaluate the query against the search index, identifying potential matches, presenting the potential matches to the user and receiving a selection of one potential match to be the match, and mapping the concept in the health care-related code set corresponding to the match to the concept and/or lexical of the second health care-related code set corresponding to the query.

Abstract: A system, method, and user interface for optimizing encoding of a patient problem list in an electronic medical record or electronic health record. The system is operable on one or more computers with one or more processors that are configured to construct a database of HCC signatures, each HCC signature including one or more ICD-10 and/or SNOMED codes, deconstruct a patient problem list within an electronic medical record or electronic health record to generate an identification of one or more ICD-10 and/or SNOMED codes included within the patient problem list, evaluate the identified ICD-10 and/or SNOMED codes against each HCC signature to determine sufficient matches to one or more HCC signatures, cross-check HCC concepts related to the sufficiently-mapped HCC signatures and eliminate HCC concepts already identified in the record to generate a group of at least one non-eliminated, sufficiently-mapped HCC concepts, and displaying the non-eliminated, sufficiently-mapped HCC concepts.