Much of it comes down to … words.

In most areas of health care, words describe symptoms, suggesting routes to an underlying problem hidden deep within the body, in some malfunctioning organ or system.

But for behavioral health care providers, the situation is very, very different.

For psychologists and psychiatrists and mental health clinicians, words provide not a “route” to a problem but rather, in essence, the locus - words themselves are the heart of the challenge, the tangible manifestation of hidden, intangible spurs to problematic mindsets and/or destructive behaviors. Words are windows into emotions, clues to modes of perception, exemplars of affliction, and ultimately tools for therapeutic intervention.

How do we understand a patient’s pain? By listening to the words the patient uses. How do we determine the patient’s pathology? By analyzing those words. How do we measure success? Again, by hearing the words of patients – who tell us how they feel.

Diet has a role in mental health, so does exercise, so too in today’s world do medications. And perhaps, in the area of substance abuse, a blood test is telling; in the area of gambling addiction, fluctuations in a bank account may be revealing. But still, in the end, for the practitioner, the bottom line is … words.

So … what does a practitioner do with those valuable words? Well, the bedrock foundation of organization and analysis of the words exchanged in mental health treatment is, was, and always will be session notes – the written record of a patient’s ruminations and the practitioner’s observations and conclusions.

And now, as in so many other areas of modern life, the propagation and use of session notes is being altered in fundamental ways by the application of A.I.

So again, we pose the fundamental question: Why A.I.? With the above emphasis on words in mind, the answer to that question is so readily apparent that it practically jumps out at you: A.I. is extraordinarily well-suited for adaptation to a field that relies, first and foremost, on words. Algorithms developed using machine learning on vast verbal data sources have led to the evolution of something called NLP – short for “natural language processing” – and NLP is bringing dynamic change to procedures associated with session notes. A typical A.I. program can use NLP to organize the words that are exchanged between patient and practitioner - and generally includes a sophisticated large language model (“LLM”) which can be specifically trained to “understand” the specialized language of mental health applications, adding area-specific comprehension as well as targeted content generation to the basic processing of NLP.

A program using these tools can organize data at an operational level – transcribing sessions, crystallizing those sessions into accurate and thorough session notes, and issuing billing invoices. In addition, raw output can be formatted into the formal written submissions necessary for obtaining insurance reimbursement – thus providing a prompt and efficient method for enhancing the clinician’s revenue stream.

And such innovative programs integrating A.I. can also generate content at an analytical level - assisting with diagnosis and treatment plans, producing reports, preparing action items and to-do lists. Human oversight is of course still a necessity, but the time saved by using A.I.-enhanced programs for the preparation and analysis of session notes, and the generation of supporting materials, will open up more time for additional clinical sessions, or for simply pondering various alternative clinical solutions in difficult cases.

In behavioral health, it’s all about words. And A.I. can make words work, for the benefit of both the patient and the therapist.

So words are paramount – but is it just about words? Before we answer that question, let’s take a closer look at NLP and charting efficiency.