How Dragonfly Harnesses Machine Learning, Big Data and Analytics in Healthcare

The electronic medical record is an incredible repository of information. It’s not without drawbacks however. A huge amount of data is locked up in clinical documentation and isn’t necessarily accessible or digestible.

Big data and healthcare don’t automatically create a positive when combined, and this is just one example. Productive use of big data in healthcare management requires effective tools, like machine learning and predictive analytics solutions designed for healthcare providers.

The goal of Xsolis’ CORTEX® technology, now known as Dragonfly is to identify solutions that, without Xsolis and our application of AI to big data in healthcare, are otherwise impossible. Our proprietary artificial intelligence (AI) allows us to do this. How?

Learn more from Senior Director of Data Science Jason King:

Speaking of AI, it’s important to clarify that artificial intelligence is a very generalized, umbrella term. It encompasses all types of machine learning as well as various other data science techniques. Don’t conflate the idea of an autonomous robot with most types of AI used today.

In the context of Xsolis, Natural Language Processing, or NLP, is the primary data science technique used in our technology solutions, which combine big data and artificial intelligence in healthcare to extract information outside traditional discrete data points.

Our NLP focuses on narrative text. This allows us to understand what is important and helpful information within a set of written text.

NLP, Big Data, and Predictive Analytics for Healthcare

The real question is, how does NLP help our clients?

It starts with understanding structured and unstructured data. Structured data in the EMR can include information like intake details, vitals, and labs — data points you might find in an Excel spreadsheet.

Conversely, our proprietary NLP extracts narrative data from an EMR that is most commonly unstructured: written notes and documents that include clinical commentary. Often critical in evaluating the status of a patient, this narrative data is some of the most difficult to work through (or find) as a UM nurse or other clinical user.

Dragonfly, Xsolis’ technology platform, not only parses narrative data, but it compares that data to the millions of other situationally relevant cases it has trained on from across our entire client database. Those valuable insights then offer real-time predictions across a range of clinically important metrics and operational requirements.

To discover more about how the power of artificial intelligence and natural language processing can transform your utilization review framework, schedule a demo today. To hear a more in-depth conversation with Jason, listen in on a podcast appearance of his below.