Health care providers need to see a return on any analytic investment they make. Natural language processing (NLP) is one way artificial intelligence (AI) can help providers convert the potential within their health data into quality improvement and cost savings.
NLP is an AI technology that actually makes sense for health care.
ARTIFICIAL INTELLIGENCE LANDSCAPE
SAMPLE HEALTH CARE USES
Clinical Decision Support — Life Sciences — Outcomes Analysis — Documentation Integrity — Computer-Assisted Coding (CAC)
What is natural language processing?
- Computational linguistics technology within the field of artificial intelligence.
- Using NLP, the computer can read, interpret and organize important health data that is buried in unstructured free-text fields, such as physicians' notes.
- NLP converts complex clinical narratives into actionable data points and insights.
Why is NLP important?
- 80 percent of health record content is unstructured (such as descriptions, text fields and narrative notes) and does not fit into easily actionable categories.
- Extracting valuable information from this unstructured data is done manually and is time-consuming.
- NLP enhances the return on hospitals’ electronic medical record (EMR) and analytic investments by improving the amount of usable data and enhancing analytic insights.
How does NLP work?
- NLP takes this large variety of source documentation and organizes it into actionable and indexable data. — NLP preserves the context of medical information, paving the way for in-depth analysis.
- Insights gleaned from NLP-augmented clinical data, adjudicated claims data and other data sources provide new ways for organizations to respond quickly and with material impact on care quality and cost.
Increased administrative cost savings
Heightened staff and operational efficiencies
Improved case mix index and revenue integrity
More accurate quality and safety measures
Data in Focus: Innovating with a Purpose — Artificial Intelligence
See how natural language processing is helping to unlock insights from health care data.