Today, let’s talk about talking. You might be surprised that talking is going hi-tech, but it is! For years, medical care providers have been dictating medical records and transcription companies have been typing those records. Innovations in speech recognition developed wonderful products like Dragon Naturally Speaking that changed how many providers document medical care. Now, speech recognition has gone to new levels with Natural Language Processing (NLP). NLP is not really new. It has been in development for well over 20 years but now it is catching on and changing healthcare as we know it.
So, what is NLP? Natural Language Processing is a form of artificial intelligence that, when used in healthcare, can identify important key components in a medical record and transform a narrative text (e.g. a story) into coded discrete data elements output in an XML format. With that said in such fancy terms, I will translate it to plain English with an example.
Let’s say that a doctor dictates the following statement: “John Doe is a 59 year old male with type 2 diabetes.”
NLP technology can take that statement and identify each important item in the statement individually, give it a header or a tag, and code it (if applicable), a little like this:
patient name: john doe
diagnosis: type 2 diabetes
ICD-9 diagnosis code: 250.00
This is some impressive stuff! It opens up a world of automation related to regular-old speech in medical practices and hospitals. Innovative transcription companies, like StenTel, for example, are working with NLP technology from NLP developers such as MedLEE, CodeRyte, and IBM. Other companies like 3M, and Nuance (the makers of Dragon Naturally Speaking) are also using NLP technology in a variety of ways from highly automated encoders to clinical documentation improvement to population health management.
For these technology companies and the providers of NLP technology, goal is two-fold. First, NLP can help improve provider reimbursement by helping coders to accurately identify patient conditions in otherwise messy and at times voluminous medical records. Secondly and perhaps more importantly, this technology opens the door for data mining and aggregation in ways that were never possible before. This is the heart and soul of the population health movement.
With NLP technology, automated systems are able to warn us about impending outbreaks and so-called ‘clusters’ before they get too big. When we know where these condition ‘clusters’ are (cancer clusters, autism clusters, etc.) and when they are beginning, we are better equipped to find for the cause and implement the appropriate precautions to prevent further problems. Additionally, NLP offers the ability to analyze outcomes to see what treatments work and what treatments do not work for various conditions and diseases. With this kind of information, healthcare (diagnosis and treatment) will improve and become more affordable – all thanks to the handful of innovators developing and promoting NLP.