Founder & CEO, PMHScribe
I have a slightly different opinion about AI scribes than you might expect from someone who built one: The goal should not be to capture everything.
In fact, I think one of the most important differences between a useful AI scribe and a frustrating one is knowing what belongs in the clinical note, and what doesn’t.
Psychiatry is not a field where more words automatically create better documentation. Our visits are nuanced. Patients tell stories. Conversations move between symptoms, relationships, medications, history, risk, sleep, work, family and whatever else is happening in someone’s life. A psychiatric note still has to turn all of that into clear, clinically useful documentation. That requires more than transcription; it requires structure.
This is probably the biggest misconception I hear about AI documentation. An AI scribe should not simply reproduce a psychiatric appointment word for word. If that were the goal, we already had technology capable of doing that.
The real value of an AI scribe for psychiatry is helping transform a clinical conversation into documentation that reflects the encounter in a way that is organized, useful and appropriate for the medical record.
A patient may spend several minutes describing an argument with a family member. The clinically relevant information may be that the conflict contributed to increased anxiety, poor sleep and worsening irritability. Those are not the same thing.
The conversation gives us context. The note needs to capture the clinical meaning.
There is no single perfect psychiatric note because documentation depends on the clinician, setting, type of visit and patient. But generally, a good psychiatric AI scribe should be able to recognize and organize the information clinicians routinely need to document.
That may include:
presenting symptoms and changes since the previous visit
relevant psychiatric history
medication response, adherence and side effects
sleep, appetite, energy and concentration
substance use when clinically relevant
functional changes
mental status examination findings
safety and risk assessment
diagnostic considerations
treatment planning
medication changes
patient education
follow-up recommendations
psychotherapy documentation when applicable
For an initial psychiatric evaluation, the documentation needs may be very different from a 15-minute medication management follow-up.
That is exactly why psychiatric documentation tools should understand different psychiatric workflows rather than trying to force every encounter into the same generic medical template.
The mental status exam is one of the clearest examples of why psychiatry needs specialty-specific documentation.
During a visit, we are observing and assessing things like behavior, speech, mood, affect, thought process, thought content, cognition, insight and judgment. A generic transcript does not automatically turn those observations into a useful MSE.
And simply inserting a completely normal mental status exam into every note is not the answer either. The documentation should reflect the clinical encounter.
That means AI can help organize information, but the clinician still needs to review the note and make sure it accurately represents what they observed. That review step is very important.
This may be my biggest documentation hot take. More documentation is not automatically better documentation. AI makes it remarkably easy to generate a lot of text. That does not mean all of that text belongs in the medical record.
A useful note should make it easier for another clinician, or your future self, to understand what was happening with the patient, what you assessed and what you decided to do. If the important information is buried inside several pages of unnecessary detail, the note may technically be longer while becoming less useful.
The best AI documentation tools should help clinicians create clarity, not volume for the sake of volume.
At the same time, psychiatric documentation cannot become so abbreviated that we lose the story. Mental health care is longitudinal. A medication may appear ineffective unless you know the patient just lost a job. Sleep problems may look like a medication side effect until you understand there is a newborn at home.
Context matters in psychiatry.
The challenge is capturing the relevant context without turning the medical record into a transcript of someone’s life. That balance is one of the reasons I believe AI documentation for mental health needs to be designed differently from documentation for many other specialties.
This question deserves just as much attention as what the technology includes. Not every sentence spoken during a psychiatric appointment belongs in the note. Clinicians should be able to review what has been generated and remove information that is unnecessary, overly detailed or not clinically relevant.
This becomes particularly important in mental health because our patients often share extremely personal information. Good documentation should support continuity of care, clinical reasoning and appropriate recordkeeping without automatically preserving every detail of every conversation.
An AI scribe should help organize the encounter. It should not decide that every spoken detail deserves a permanent place in the medical record.
I sometimes describe this as the new documentation skill AI is creating. We used to spend an enormous amount of time producing the first draft. Now technology can help with that part.
But the clinician still needs to ask:
Does this accurately reflect what happened?
Is anything missing?
Is anything overstated?
Is there unnecessary information here?
Does the assessment make sense?
Does the plan reflect what I actually decided?
The clinician remains responsible for reviewing and approving the final documentation. That is not an AI limitation. I actually think that is exactly how the technology should work.
If you’re evaluating an AI scribe for psychiatric or behavioral health documentation, I would look beyond how quickly it produces a note.
Speed matters.
But I would also ask:
Does it understand psychiatric terminology?
Can it handle different types of psychiatric encounters?
Does it support medication management documentation?
Can it create a useful mental status exam?
Can it support risk assessment documentation?
Can it distinguish psychotherapy documentation from medication management documentation?
Can you easily review and edit the output?
Does the final note sound like a psychiatric note, or like a generic medical template?
And perhaps most importantly:
Does the tool make documentation easier without asking you to lower your clinical standards?
That is the bar.
The Best AI Scribe Should Feel Less Like AI
My goal has never been to make clinicians think more about technology during a patient visit, It is actually the opposite.
The technology should quietly handle the administrative work it can handle so the clinician can stay present for the part that requires a human being.
Listen. Observe. Ask another question. Notice when the answer changes. Think clinically.
Connect the pieces. Then review the documentation and make sure the record reflects the care you actually provided. That is where I believe AI scribes are most useful in psychiatry.
— Allison
What is an AI scribe for psychiatry?
An AI scribe for psychiatry is a clinical documentation tool that helps psychiatrists, psychiatric mental health nurse practitioners and other behavioral health clinicians turn patient encounters into structured psychiatric notes. Unlike basic transcription software, psychiatry-focused AI scribes are designed around mental health documentation workflows such as psychiatric evaluations, medication management, mental status examinations, risk assessments and psychotherapy documentation.
Should an AI scribe record everything said during a psychiatric appointment?
No. The purpose of an AI scribe is not necessarily to create a word-for-word transcript of the visit. A useful psychiatric AI scribe should help organize clinically relevant information into structured documentation that the clinician can review and edit before finalizing.
Can an AI scribe create a mental status exam?
Psychiatry-focused AI scribes can help organize information relevant to a mental status examination, but clinicians should review any AI-generated MSE to ensure it accurately reflects their observations and assessment during the encounter.
What should psychiatrists look for in an AI scribe?
Psychiatrists and PMHNPs should consider whether an AI scribe understands psychiatric terminology and workflows, supports the types of notes they routinely use, provides appropriate privacy and security protections and allows clinicians to review and edit documentation before it becomes part of the medical record.
Are AI scribes useful for medication management visits?
AI scribes can help streamline medication management documentation by organizing information such as symptom changes, medication response, adherence, side effects, mental status findings, treatment decisions and follow-up planning. Clinicians should review generated documentation for accuracy before finalizing it.
Is an AI scribe the same as medical transcription?
Not exactly. Traditional transcription primarily converts speech into text. An AI scribe can additionally organize information from an encounter into structured clinical documentation, although the clinician should still review and approve the final note.
Why use an AI scribe designed specifically for mental health?
Psychiatric and behavioral health documentation includes workflows and clinical concepts that may not be emphasized in general medical documentation, including mental status examinations, psychiatric evaluations, medication management, risk assessment and psychotherapy documentation. A specialty-specific AI scribe is designed around those needs.
About PMHScribe
PMHScribe is an AI documentation platform built specifically for psychiatrists, psychiatric mental health nurse practitioners, therapists, counselors and behavioral health clinicians. Founded by practicing PMHNP Allison Sikorsky, PMHScribe helps clinicians turn patient encounters into structured psychiatric and mental health documentation while keeping the clinician in control of the final note.
