A better approach to Natural Language Processing
Clinical Natural Language Processing (NLP)
Meaningful clinical information is trapped as unstructured text in various clinical documents and physician notes.
Clinical Architecture’s solution to this problem is a different approach to Natural Language Processing called SIFT. SIFT (Semantic Interpretation of Free Text) unlocks hidden data by identifying and returning the coded, actionable information you need. Through advanced normalization, mapping, and clinical natural language processing capabilities, SIFT returns coded information by analyzing unstructured text to empower better data exchange, decision support, population health, and analytics.
What does SIFT do?
Analyzes unstructured text, targets and identifies clinical information, and returns structured, actionable data.
Recognizes full, partial, or synonymous terms and matches them to targeted terminologies to impact true semantic meaning.
Uses advanced text analysis and targeted, rules-based matching to go beyond data extraction to meaningful interpretation and analytics based on the structure of the content itself.
Unlocks valuable insights, expanding the actionable data available to healthcare applications and providers.
Fast enough to dynamically process provider notes as they are entered and scalable enough to process a full repository of documents.
Use Cases for SIFT
Population Health/Data Analytics
Computer Assisted Coding
Clinical Documentation Improvement
Clinical Decision Support
Clinical Trial Recruitment
Core Measure Reporting
Download the Data Sheet
How does it work?
We can help you achieve true semantic interoperability for all your data quality initiatives. Schedule a demo and we'll show you how!