Code-A-Note's Clinical Code Extractor incorporates an advanced clinical domain Natural Language Processing (NLP) solution to harvest clinical information from unstructured text, and then applies additional filter and data resources from Find-A-Code's digital coding library. The system increases coder accuracy and efficiency, saving you both time and money.
The Clinical Code Extractor implements semantically broad Clinical Ontologies based on trusted health community resources including U.S. National Library of Medicine (NLM) Unified Medical Language System (UMLS), Centers for Disease Control and Prevention (CDC), Centers for Medicare and Medicaid Services (CMS), National Center for Health Statistics (NCHS), American Medical Association (AMA) and NLM clinical resources, enriching terminology variance. A four stage term correlation processor provides high throughput performance across these very large Clinical Ontologies. Other special, advanced clinical NLP techniques to optimize Precision and Recall performance involves: canonicalization and Clinical Synonyms Expansion (CSE); Clinical Semantic Compression (CSC); and section, negation, experiencer and temporality context-aware.
The professional coder selects appropriate codes from the candidate extracted codes. Selected codes can then be validated using Find-A-Code's up-to-date code validation tools. The "Check Codes" button validates the selected codes for Medical Necessity, NCCI Edits, MUE Edits (gender, age, pregnancy, etc.), active/inactive codes, and proper Place of Service values.
Code-A-Note's automatic, thorough analysis of the medical record results and code selection decision aids provides a high quality claim compliance and accuracy while improving the overall coding workflow efficiency and throughput, and minimizing user fatigue errors. Code-A-Note greatly reduces the number of claims rejected, denied, or suspended. Code-A-Note puts your clinic or office on the fast track for coding and claims processing.