AssistMed is committed to transforming clinical documentation from isolated data collection to meaningful data delivery. Natural Language Processing enables the standardization and normalization of the clinical data captured, so it becomes quantifiable and reportable.
The use of Natural Language Processing provides the ability to dynamically format unstructured documents into data sets with structured terms and relationships. This enables the identification of patterns and associations in the data captured.
With Natural Language Processing, healthcare learns from its own experiences by mining the data of clinical encounters. Retrospective analysis of clinical encouters determines what treatments are more effective, and facilitates comparative effectiveness studies, predictive analyses, and data visualization to occur.
Natural Language Processing analytics can change clinician behavior and care delivery, and ultimately lead to continuous quality improvements and improved medical science. The use of Natural Language Processing facilitates specialty-based optimization and provides the flexibility to meet individual institutional needs.
Natural Language Processing Applications
✔ Clinical analytics
✔ Clinical content indexing
✔ Clinical concept modeling
✔ Computer-assisted coding
✔ ICD-10 and SNOMED mapping