The MedTRACE (Medical Text Retrieval, Auto-Categorization and Extraction) platform automatically extracts, analyzes and encodes unstructured clinical text from Electronic Medical Record / Electronic Health Record (EMR/EHR) databases and other sources.  Key clinical terms are extracted, processed, and mapped into several standard terminology coding systems defined within the Unified Medical Language System (UMLS).

MedTRACE provides the following mappings and services:

-        Map medical text into SNOMED CT CORE concepts, associated morphologies, finding sites, and other SNOMED relationships.

-        Map SNOMED into ICD-9 codes

-        Map SNOMED into ICD-10 codes

-        Negation Clause Detection to determine whether outcomes are positively or negatively indicated

For example, the output below (with randomized Record IDs) shows 'Impressions' text that has been extracted from EMR records and then automatically mapped to SNOMED Concept ID / Description and Positive/Negative indications by MedTRACE.   


SNOMED Concept IDs can be further mapped into ICD-9, ICD-10 and other results using available UMLS SNOMED data resources.   MedTRACE automatically converts unstructured medical text into a variety of structured data results, adding significant value.

MedTRACE can be customized to handle alternate local medical terminologies, specialized EMR formats, and alternate coding systems.  

Contact us for more information.