Documentation is essential: it tells the patient’s story, supports continuity of care, backs up clinical decisions, and enables billing. But over the past decade, the volume and complexity of charting has exploded—especially in behavioural health and psychiatry.

The costs show up across several dimensions.

1. Time: The Most Obvious (and Painful) Cost

For many clinicians, documentation no longer fits in the clinic day.

Common patterns include:

• Finishing notes after dinner
• Spending weekends catching up on charts
• Shortening patient visits just to keep up

Multiple studies have found that physicians spend a large chunk of their day on documentation and EHR tasks—often rivalling or exceeding direct patient time. This is especially true in specialties that require rich narrative notes, like psychiatry, where the story, context, and nuances of thought and behaviour matter as much as lab values.

That extra time has an opportunity cost:

• Fewer patient appointments
• Less bandwidth for care coordination
• Minimal time for professional development, supervision, or teaching
• Reduced recovery time between emotionally demanding sessions

In short: documentation time displaces everything else.

2. Cognitive Load and Clinician Wellbeing

Even when the clock says “8 hours,” the mental load of documentation can make the day feel like twelve.

Clinicians constantly juggle:

• Listening empathetically
• Extracting key clinical data
• Translating a complex, human interaction into structured, billable language
• Remembering templates, checklists, and billing rules

In psychiatry, this often means toggling between deep listening and “note-thinking” mid-session:

“I need to respond to this disclosure about worsening mood… but also remember to document risk assessment, protective factors, medication adherence, and prior episodes clearly enough to justify the treatment plan and coding.”

That split attention is exhausting. Over time, it contributes to:

• Emotional fatigue
• Detachment from work (“I feel like a data entry clerk, not a doctor.”)
• Increased risk of burnout and leaving clinical practice

The cost here is human: it’s the wear and tear on clinicians, teams, and the quality of engagement with patients.

3. Financial Cost: Under-Documentation and Under-Coding

Documentation isn’t just a legal and clinical record—it’s also the backbone of revenue.

When notes are rushed, incomplete, or missing key elements:

• Visits may get down-coded
• Justifications for higher E/M levels aren’t clear
• Time-based billing opportunities are missed
• Risk and complexity are underrepresented

Psychiatrists and other mental health clinicians feel this acutely with:

• Complex medication management visits
• High-risk patients needing safety planning
• Collateral contacts with family, therapists, or social services

Each of these can support higher levels of billing when properly documented. But when documentation is a burden, people naturally default to:

“Let me just finish this quickly and move on.”

That “quick note” pattern quietly reduces revenue per visit, even while the work per visit stays high (or increases).

4. Impact on Patient Experience

Patients might not see your EHR, but they feel your documentation burden.

It shows up as:

• Eyes on the screen instead of the patient
• Shortened visits to make time for charting
• Delayed or missing visit summaries
• Less time for shared decision-making

In psychiatry and behavioural health, the relationship is treatment. Anything that pulls attention away from patients—especially during sensitive or emotionally charged sessions—can weaken trust and therapeutic alliance.

When documentation dominates the day, the cost is not just inefficiency; it’s a more transactional, less human-feeling experience of care.

Why Traditional Solutions Haven’t Really Fixed It

Clinicians and practices have tried to tame documentation for years, with mixed success.

Common strategies include:

• Templates and smart phrases
  • Pros: Faster than free-typing; helps standardise notes
  • Cons: Risk of “note bloat,” repetitive text, and copying forward outdated information
• Hiring scribes (in-person or virtual)
  • Pros: Offloads much of the typing in real time
  • Cons: Expensive, staffing challenges, variable quality, training overhead, limited scalability
• Shorter notes (“If it’s not required, don’t chart it.”)
  • Pros: Less time per visit
  • Cons: Risk of missing important details, weaker support for coding and medical necessity

These approaches help around the edges, but they rarely change the fundamental math: clinicians still spend a lot of time and cognitive effort transforming conversations into structured documentation.

That’s where AI scribes start to look different.

How AI Scribes Change the Documentation Equation

AI scribes aim to remove (or drastically reduce) the need for clinicians to write notes from scratch. Instead, they listen in, identify key elements of the visit, and generate structured drafts that the clinician reviews and finalises.

Here’s how that changes the “cost structure” of documentation.

1. From “Authoring” to “Editing”

Traditional documentation:

• The clinician must recall the encounter, structure it, and write it out manually.
• The mental work is heavy, and the time cost stacks up across the day.

AI scribe workflow:

• The system listens in the background during the visit.
• It generates a clinically oriented narrative: HPI, ROS where relevant, MSE (for psychiatry), assessment, and plan.
• The clinician reviews, corrects, and finalises.

The shift from full authorship to editing is significant:

• Time per note often decreases because you’re refining, not starting from zero.
• Cognitive load drops: you’re confirming and improving, not reconstructing every detail.

This can be particularly impactful in psychiatry and therapy-adjacent work, where the encounter is more narrative than numeric.

2. More Complete Capture of Clinical Nuance

In high-volume clinics, it’s easy for details to be lost between the visit and the note. AI scribes can help surface and organise:

• Symptoms and their evolution over time
• Patient quotes that reflect insight, risk, or functional status
• Medication adherence, side effects, and past trials
• Psychosocial stressors and protective factors

Because the AI is “listening” to the entire visit, it may catch parts that would otherwise be summarised or omitted when the clinician is short on time.

Downstream effects can include:

• Stronger support for diagnoses
• Better justification for treatment decisions
• A clearer picture for other clinicians accessing the chart later

3. Smarter Billing Support (Without Extra Mental Overhead)

Billing is where the clinical narrative and business reality meet. When AI scribes incorporate billing-aware logic, they can help:

• Suggest ICD-10 codes that align with the documented diagnoses
• Propose CPT codes based on visit complexity, content, and duration
• Indicate a likely E/M level, with documentation elements visible for clinician review

This doesn’t replace the clinician’s judgment. Instead, it reduces the constant pressure of “Did I document enough for this level?” by:

• Aligning suggested codes with the actual narrative
• Highlighting missing elements that warrant clarification
• Helping avoid both under-coding and over-coding

Over time, this can:

• Bring billing patterns more in line with actual clinical work
• Improve revenue integrity without asking clinicians to become coding experts

4. Reclaiming Attention During the Visit

One of the biggest qualitative changes with AI scribes is how they can reshape the visit itself.

Instead of:

• Trying to type while listening
• Jumping between EHR fields mid-conversation
• Interrupting the flow to “make sure I get this in the note”

Clinicians can:

• Maintain natural eye contact and conversational flow
• Let the AI handle the first-pass structuring of what’s said

For psychiatry, where trust and nuance are central, this shift back to a more human, uninterrupted encounter is not just a “nice to have”—it can be therapeutic.

5. Scaling Across Solo and Group Practices

The economics of AI scribes also look different from traditional human scribes:

• They can be “present” for every visit without hiring and training multiple staff members.
• They can support varied visit types—intakes, follow-ups, med management, group sessions—using tailored templates or structures.
• In group practices, they can help standardise documentation practices across clinicians while still allowing for individual styles.

Features that matter at the practice level include:

• Tools for managing documentation workflows across multiple clinicians
• Support for group practices, including shared elements and per-patient documentation
• Pre-session information support (e.g., patient questionnaires, chart pre-review notes) to streamline before the visit even starts
• Integration with existing EHRs to reduce double documentation and copying/pasting

All of this changes the math not only for one clinician’s day, but for an entire practice’s operations.

What Changes—and What Doesn’t

AI scribes are not a magic wand. They don’t eliminate:

• The need for clinician oversight and judgment
• Legal and professional responsibility for the chart
• The importance of accurate, honest, patient-centred documentation

Clinicians still need to:

• Review and edit AI-generated notes
• Ensure the documentation accurately represents what occurred
• Make final decisions about diagnoses, plans, and billing codes

What does change is the shape of the work:

• Less time reconstructing the visit from memory
• Less mental juggling of “listen, think, write, and bill” all at once
• More time and energy available for complex clinical reasoning and relationship-building

The goal isn’t to remove clinicians from documentation—it’s to remove as much unnecessary friction as possible.

Bringing It All Together

When you add up the true cost of medical documentation, you’re not just counting minutes spent typing. You’re counting:

• Evenings and weekends lost to charts
• Emotional energy is drained by constant multitasking
• Revenue lost to under-documentation and conservative coding
• Small but meaningful erosions of patient experience over time

In psychiatry AI scribes change that equation by shifting clinicians from authors to editors, capturing more of the clinical nuance that matters, providing structured billing suggestions, and giving back attention during visits.

For psychiatrists and behavioural health professionals in particular—where every session is rich, complex, and narrative—this can be the difference between a day that feels relentlessly administrative and a day that feels clinically meaningful. The math of documentation is changing. The question for many clinicians now isn’t whether to adapt, but how to do it in a way that preserves clinical quality, supports sustainable practice, and keeps patient stories at the centre where they belong.

Disclaimer

This article is intended for informational and educational purposes only and does not constitute medical, legal, financial, or professional advice. The views expressed are based on general observations of clinical documentation practices and the potential role of AI-assisted tools in healthcare settings. They may not apply to every clinical environment, speciality, or jurisdiction. Clinicians remain fully responsible for their own professional judgement, regulatory compliance, coding accuracy, and patient care decisions. Any AI scribe or related technology should be implemented in line with applicable laws, clinical guidelines, data protection requirements, and organisational policies. Readers should seek independent advice or consult appropriate professional bodies before making changes to clinical workflows, documentation processes, or billing practices. Open MedScience accepts no liability for actions taken based on the content of this article.