Nym’s innovative clinical language understanding (CLU) technology leverages proprietary machine-learning models and rules-based clinical ontologies to accurately translate clinical data in patient records into a comprehensive narrative of the patient encounter.
Combining our CLU technology with medical coding ontologies, Nym’s autonomous medical coding engine translates provider notes within patient charts into medical codes in seconds with over 95 percent accuracy and absolutely zero human intervention.
Discover how Inova, the leading health system in Northern Virginia, leveraged autonomous medical coding to eliminate staffing challenges, expensive coding practices, and delayed payment cycles across multiple emergency department (ED) facilities.
Nym’s CLU technology and rules-based approach to medical code assignment enable our engine to produce audit-ready, traceable documentation for every code it assigns. These audit trails provide healthcare organizations with a comprehensive, actionable resource that they can use in the event of an audit, denial, or other matter related to compliance.
Clinical Language Understanding (CLU) is Nym’s proprietary technology that combines machine learning models with rules-based clinical ontologies to understand the complexity of clinical documentation. CLU enables Nym’s engine to comprehend clinical context, negation, temporality, and subjectivity within provider notes, understanding the difference between "patient denies chest pain" versus "patient reports chest pain," or distinguishing "history of hypertension" from a current condition.
While traditional NLP systems rely on keyword matching or pattern recognition, Nym’s CLU technology understands true clinical meaning. CLU processes unstructured clinical language with full medical context, differentiating between subjective patient-reported symptoms and objective clinical findings. Unlike pure NLP approaches, CLU’s rules-based ontologies combined with machine learning maintain complete explainability, providing transparent reasoning for every coding decision rather than operating as a "black box."
Nym’s engine analyzes patient records using CLU technology to extract clinically relevant information, then applies rules-based clinical ontologies that encode medical coding guidelines from AMA, CMS, and WHO. The engine identifies documented diagnoses, procedures, and services, then assigns appropriate ICD-10-CM/PCS and CPT codes based on current standards. The entire process operates autonomously in seconds, with encounters routed directly to billing when coding confidence exceeds 95%.
Unlike "black box" AI solutions, Nym’s CLU-powered engine provides complete transparency through comprehensive audit trails for every coding decision. Each coded encounter includes supporting documentation showing which clinical findings informed code selection, references to coding guidelines applied, and clear reasoning for code assignments. This enables healthcare organizations to quickly respond to audits, defend coding decisions with confidence, and accelerate appeals processes.
Nym’s Compliance and Clinical teams proactively implement all coding guideline updates directly into the autonomous medical coding engine, including annual CPT and ICD-10 changes, quarterly NCCI updates, and ongoing HCPCS modifications. Our team translates new guidelines into technical updates and deploys them on their official effective dates. This eliminates training requirements, productivity disruptions, and compliance gaps, ensuring customer operations continue without interruption while maintaining automatic alignment with current standards.
