Spend More of Your Day Being the Doctor

Live Scribe vs. AI Scribe: What I Learned After Using Both

By Donald E. Pelto, DPM • Approximately 8 minutes to read

For years, one of the best investments I made in my podiatry practice was hiring a live scribe. The reason was not simply that someone else wrote my notes. The real benefit was that I could look at my patients, listen to them and spend my day doing the work only a doctor can do.

A good scribe buys back more than time. A good scribe protects attention. I could move from room to room, stay present with patients and finish the day without carrying a pile of documentation home.

Eventually, however, I began comparing my live-scribe workflow with the AI scribe built into ModMed. I did not make the transition because I disliked my human scribe. In fact, the opposite was true: my scribe was excellent. That is what made the comparison meaningful.

My story is not, “AI is amazing and humans are obsolete.” My story is this: I loved having a human scribe, the switch to AI was painful, but after learning how to use it correctly, I came to believe AI was the better long-term solution for my practice.

What a Great Human Scribe Gave Me

After enough training, my scribe did far more than type what I said. He understood how I practiced. He helped with documentation, prescriptions, physical-therapy and MRI orders, pathology, reminders, messages to surgical staff, ABIs, diabetic foot examinations and the normal sequence of my day.

That is the greatest strength of an experienced human scribe: the person learns you. A trained scribe can recognize not only what happened in the room, but also what you usually do next.

The patient experience changed too. I would explain that my scribe was documenting the visit so I could focus completely on the patient. Instead of the encounter becoming doctor to computer to patient to computer, it became doctor to patient.

That level of presence is difficult to put on a spreadsheet, but patients feel it. The physician feels it too.

The Limitations of a Human-Dependent System

My human scribe was excellent, but the system still depended on one person. People get sick. They take vacations. They require training. They can leave. They also have a limit to how much volume they can manage at once.

On some high-volume Fridays, particularly when I worked alongside my nail technician, I could see close to 50 patients instead of my more usual 20 to 23. Even a very capable scribe could become the bottleneck. When the volume rose, downstream items such as ABIs, diabetic examinations, follow-up tasks or pieces of documentation could be delayed or missed.

Then there was cost. My live-scribe model cost approximately $30,000 to $40,000 per year. The AI scribe was approximately $4,000 to $5,000 per year. Those numbers vary by practice and vendor, but the difference was too large to ignore.

Still, cost was not my only question. My real question was: Can AI actually do everything my scribe does?

My First Experience With AI Was Frustrating

Initially, the answer felt like no. I suddenly had to think about tasks that my scribe had handled almost automatically. I needed to review and reconcile information, learn where items lived inside the EMR, correct details, verify orders and become more intentional about what I said during each visit.

I struggled with things as basic as finding historical images, locating laboratory results, understanding the difference between the iPad and desktop workflows, and learning Visit Overview and reconciliation. There was more mental load, not less.

Over time, I recognized something important: not all of this was an AI problem. The transition exposed an EMR knowledge problem. My scribe had protected me from needing to understand portions of my own software.

That protection had been convenient. It had also made me dependent.

The Turning Point Came About Two Weeks In

After roughly two weeks, my opinion started to change. Each day I became faster. I realized the AI might not replace 100 percent of what an excellent human scribe could do, but it could handle perhaps 80 to 90 percent of what I needed for a fraction of the cost.

The easiest visits became especially efficient: routine nail care, diabetic foot examinations, biopsies, straightforward follow-ups and other predictable encounters. These visits have a consistent structure. Once the AI captures the conversation and the EMR has the right protocol, there is often very little left to do: record, review and sign.

The more complex visits remained harder. Ulcers, wound care, prescriptions, shockwave, DME, procedures and visits with multiple problems have more moving parts. The AI could create a beautiful narrative, but a beautiful narrative is not always a complete medical workflow.

That distinction matters. AI-generated documentation should still be treated as a draft. The physician remains responsible for verifying the clinical information, orders, procedures and billing.

The Biggest Lesson: AI Works Better When I Communicate Better

AI cannot read my mind. I learned to verbalize the details that mattered. Instead of silently thinking that I would order an MRI if the patient failed to improve, I would say, “If you are not improving, our next step will be an MRI.”

This improved the AI output, but it also produced an unexpected benefit: the patient heard the plan more clearly. Better communication for AI often became better communication with the patient.

AI Plus Protocols Is Better Than AI Alone

The real breakthrough came when I stopped thinking of the product as a recorder and started thinking of it as part of an AI-assisted clinical workflow.

For the conditions I treat repeatedly—plantar fasciitis, Achilles tendinitis, ingrown toenails, wound care, compression dressings and other common podiatric problems—I began building condition-specific protocols and templates inside ModMed.

The division of labor became simple:

AI captures what is unique about the encounter.

The protocol supplies the repeatable structure.

Staff complete the appropriate downstream tasks.

The physician verifies the clinical judgment and final record.

If I treat plantar fasciitis in a similar way many times each week, the AI should not be forced to reinvent the entire structure for every patient. I can create that structure once and let AI document what is different about the patient in front of me.

My 60-Second Review Philosophy

AI does not eliminate physician responsibility. My goal is not “AI writes it, and I blindly sign it.” My goal is “AI does the heavy lifting, and I verify what matters.”

My rapid review focuses on six areas: diagnosis, examination, plan, orders, procedures and billing. I do not need to rewrite every sentence. I do need to make sure the clinical record is correct.

In some encounters, the AI note is actually more detailed than the note I might have produced manually. It may capture counseling, treatment discussions and elements of medical decision-making that could otherwise disappear. More detail is useful only when it remains accurate and clinically relevant.

What I Would Tell a Podiatrist Starting Tomorrow

I would not tell a colleague to fire a scribe and simply turn on AI. I would tell the doctor to begin with five to ten predictable visit types and build the workflow deliberately.

Select your most repeatable encounters: routine nail care, diabetic foot examinations, plantar fasciitis, Achilles tendinitis, ingrown nails, warts, fracture follow-ups, orthotic visits, post-operative visits and wound care.

Decide what the AI should capture from the conversation.

Decide what the EMR protocol should supply every time.

Decide which downstream tasks belong to staff.

Create a short physician review checklist and measure actual time saved.

Published implementation research reaches a similar practical conclusion: ambient documentation can reduce burden, but success depends on technical stability, workflow integration, training, product fit and ongoing support. The technology matters, but implementation matters just as much.

The Economics Matter, but Time Is the Real Return

The annual cost difference between a live scribe and an AI scribe can be substantial. But I would not choose a scribe on cost alone. The greater return is physician time and attention.

If AI saves only two minutes per patient across 25 patients, that is 50 minutes in a day. Across four clinical days, it is more than three hours of physician time each week.

That time can become another patient, a procedure, a shockwave consultation, practice development, teaching, exercise, dinner with your family—or simply going home.

My Conclusion

Human scribes taught me what great documentation support could feel like. AI showed me how much of that support could be automated.

I do not believe AI currently replaces every capability of an excellent human scribe. But when I combine AI, ModMed, protocols, staff workflows and physician review, I have a system that is less expensive, more scalable, more consistent, always available and improving over time.

If another podiatrist asked whether I would hire a live scribe or learn to use an AI scribe if I were starting over today, my answer would be simple: I would learn the AI.

Disclosure: Some resource links may become referral links. If so, I may receive compensation at no additional cost to you. I recommend only tools and services I have personally used or carefully evaluated.

References

Implementation evaluation of ambient AI documentation in ambulatory practice: PubMed

ModMed Scribe 2.0 product overview: ModMed