Clinical language is complicated. It takes deep domain expertise to interpret clinical language and extract meaning. Concepts like diagnosis, contraindications, degrees of disease, absence of symptoms and family history can be understood by technology if it is trained to do just that.
NLP understands clinical concepts
We use natural language processing (NLP) to comprehensively understand clinical concepts in patient encounter notes, versus just programing our software with rules or computations to locate and flag clinical words and phrases in a document.
Identifies clinical concepts and billable codes
NLP is a type of artificial intelligence that aims to learn, understand and interpret human language. NLP tries to mimic human understanding and interpretation, taking patterns like context, linked concepts which may be in two different sentences or paragraphs, semantic meaning and ontology frameworks. Coding Accelerator is using clinical NLP to mimic tasks that coders are performing – to identify clinical concepts and billable codes.
Machine learning keeps evolving with updates
Machine learning models continue to evolve as more clinical information is processed by our technology and code updates and changing guidelines occur. Other technologies are not conducive to handle such intricacies.