Natural Language Processing in Healthcare

The ability to turn written notes into usable data.

The goal of our AI healthcare technology is to process a lot of information more quickly and efficiently through Natural Language Processing (NLP), which mines the information that is in the written notes in the EHR.

The Advantages of NLP in Healthcare and the Medical Field

Tap the Unstructured Healthcare and Medical Data

A lot of the medical data in the EHR is structured data, which means there is a discreet field with a piece of information in it. But the written notes from a clinician are written in natural language that computers typically can’t read or use. This unstructured data can hold as much as 49 percent of the important information within the EHR.

Get a More Complete View

The clinical observations and notes are critical to understanding what is happening with a patient. Our NLP technology can read those notes and turn the information into usable data to inform our algorithms. Natural language processing enhances our healthcare technology’s ability to identify, predict, and surface clinical and social needs to create holistic care plans.

Interact More Naturally

The next step with natural language technologies is delivering healthcare and medical findings, recommendations, and predictions so they are easier to read and interpret by clinicians. This is called Natural Language Generation or NLG. Our AI provides information back in natural clinical language. This way our software can talk to doctors the way they talk to each other.

Our Healthcare NLP Technology in Action

Within Pieces Predict, our AI using NLP is able to parse the clinician’s notes to find actionable data. Perhaps a note was made that the patient had no family present, was malnourished, and had a history of substance use. Those three observations could be made into actionable data by our AI to trigger referrals for community support. Pieces Connect could make those referrals and help manage their care outside the hospital. Those factors would also inform the likelihood for that patient to be readmitted or change the recommended care protocols.

Learn more about how we use NLP to deliver actionable insights.