Within healthcare IT solutions, vast amounts of clinical information is represented in unstructured text form as a product of narrative-based system interaction, and textual-based clinical reports and publications. The challenge for Clinical Documentation Improvement (CDI) professionals is to ensure their assigned codes derived from these unstructured resources accurately reflects the patients’ clinical status and provided care for quality reporting and assuring that the organization captures all of their entitled reimbursement charges, meanwhile optimizing coding productivity. In answering this need, a common goal of healthcare IT solution providers is to integrate Computer Assisted Coding (CAC) medical autocoding technology within their solution to automatically detect and extract clinical information and medical codes from these unstructured resources. Their customer benefits are to streamline revenue-cycle processes while becoming more compliant with the increasingly complex payer and quality reporting requirements, bolstering their product amongst competitors.
Lexenco CLE™ provides sophisticated CAC clinical Natural Language Processing (NLP) technologies that achieves healthcare IT solution provider’s clinical knowledge extraction and medical autocoding desires. The CAC NLP technologies automatically, accurately and consistently harvests clinical information and medical codes (such as ICD-10-CM, HCC and CPT™) from a patient's record that can be implemented for human review or for other automated healthcare IT solution workflows. Deployed as Software as a Service (SaaS) model, integration requirements are minimal. The realized benefits are increased documentation quality and understanding, optimized claims reimbursements resulting from coding accuracy and coverage, and improved productivity that are demanded in today's clinical engagements.