Charting is the longest task in most clinicians’ day, and almost none of it happens in front of the patient. Cutting it comes down to one move: stop building the note from memory after the visit and start reviewing a draft that wrote itself during the visit. That’s the whole game. The tools differ. The evidence is honest about how much they save. And the gap between a good answer and a sales pitch is wide.
This is the pillar page for everything we’ve written on documentation burden. Below: where the hours actually go, what the 2026 studies show you can realistically claw back, the methods that get you there, and links down to the specific playbooks, the ROI math, the pajama-time breakdown, the SOAP-note quality test, and the accuracy question nobody answers straight.
Key takeaways
- Primary-care physicians log a median of 36.2 minutes of EHR time per 30-minute visit (JAMA Network Open, 2023).
- About 1 in 5 US physicians spend 8+ hours a week on after-hours EHR work; that share was 20.9% in 2023 and 22.5% in 2024 (AMA).
- A 2026 JAMA study across five health systems measured about 16 minutes of documentation time saved per 8 hours of patient care with ambient AI. Real, not revolutionary.
- The reliable win is removing the keyboard from the visit. With an ambient scribe, the draft lands about 2 minutes after the visit ends.
of EHR time per 30-minute primary-care visit (JAMA Network Open, 2023)
US physicians spend 8+ hours/week on after-hours EHR work (AMA)
to review the AI draft note after the visit ends, with AI Medical Scribe by Patient Square
Where does the charting time actually go?
It goes after the visit, and after the workday. That’s the part the schedule hides.
A 2023 JAMA Network Open study of primary-care physicians found a median of 36.2 minutes of EHR time for every 30-minute visit slot. Read that twice: the documentation now runs longer than the appointment it documents. An older time-and-motion study in the Annals of Internal Medicine put it differently, nearly two hours of EHR and desk work for every hour of direct patient care.
Then there’s the part that follows you home. The AMA’s data shows about 1 in 5 physicians spend more than eight hours a week on after-hours EHR work, what clinicians call “pajama time.” That share was 20.9% in 2023 and ticked up to 22.5% in 2024. Family physicians in one Annals of Family Medicine study averaged 86 minutes of after-hours administrative EHR work a night. The note doesn’t disappear when the clinic closes. It waits.
We dug into the after-hours piece specifically in beating pajama time, because that’s where the burnout pressure concentrates.
How much charting time can an AI scribe actually save?
Here’s where most vendor pages overreach and the studies don’t. We’ll use the studies.
The largest 2026 read is a JAMA study published in April that tracked more than 1,800 clinicians using ambient AI scribes against nearly 6,800 controls across five health systems. The result was modest and measured: about 16 minutes of documentation time saved and 13 fewer minutes in the EHR per eight hours of patient care. Notably, it found no significant drop in after-hours EHR time, and the time freed up translated to roughly half an extra visit a week. The researchers called the savings “modest,” and so do we.
A separate randomized trial from UCLA, published in NEJM AI, measured one tool (Nabla) cutting average note-writing time by about 41 seconds per note, from 4 minutes 30 seconds to 3 minutes 49 seconds, across 72,000 encounters and 238 physicians. The other tool in the trial showed a smaller, statistically insignificant change. Both nudged burnout scores down by around 7%.
So the honest headline isn’t “two hours back every night.” It’s “a real, repeatable slice of documentation time, larger for some clinicians than others, with primary care and high-note-volume practices benefiting most.” If a vendor promises more than the studies support, that’s a flag, not a feature. We worked the dollars-and-cents version in the real ROI of an AI scribe.
What’s the fastest way to cut charting time?
Get the keyboard out of the visit. Every method that works does this one thing.
| Method | When you write the note | Your time per note | What it costs |
|---|---|---|---|
| Type during/after the visit | During or at day’s end | Full write, 5-15+ min | Your evenings |
| Dictation software | After the visit, from memory | 5-10 min speaking + cleanup | Low subscription |
| Human scribe | During the visit (someone else types) | Review only | A salary |
| Ambient AI scribe | During the visit (software drafts) | ~2 min review | A subscription, ~1/10th a scribe salary |
Dictation moved typing to talking, but you still narrate visits you already did once. Human scribes solve the time problem and create a hiring one. Ambient AI is the first version where the documentation happens while the medicine happens. We laid out the head-to-head in ambient AI vs dictation.
AI Medical Scribe by Patient Square is an ambient AI medical scribe that listens during the visit and hands back a structured SOAP note, ICD-10 suggestions, and a prescription draft, ready to review and sign about two minutes after the visit. You read it, you sign it. Which is exactly why “how good is the draft” matters more than any time number. We built a 6-point SOAP-note rubric so you can grade any scribe’s output, ours included.
Does cutting charting time reduce burnout?
For the documentation slice of burnout, the evidence says yes, and it’s the strongest claim in the category right now.
A 2025 JAMA Network Open study across Mass General Brigham and Emory, surveying more than 1,400 clinicians, found a 21.2% absolute drop in burnout prevalence at Mass General Brigham over 84 days, and a sharp rise in documentation-related well-being at Emory. That’s a bigger effect on how clinicians feel than the raw time numbers alone would predict, which is itself a finding: even modest time savings, applied to the most resented task, move the needle on burnout.
What it doesn’t touch: inbox volume, prior authorization, staffing shortages, the parts of burnout that come from workload rather than typing. If charting is your largest after-hours burden, an AI scribe targets it directly. If it isn’t, expect a smaller effect. We covered the full evidence base in the 2026 evidence on AI scribes and burnout and in do AI scribes reduce burnout, caveats and all.
What questions separate real time savings from marketing?
Before you trust any time number, ask these. They map to the deeper pages in this hub.
- “How accurate is the note, and what do you publish about it?” A scribe that drafts a bad note costs you time, it doesn’t save it. Be suspicious of vendors quoting a clean accuracy percentage; we explain why in how accurate are AI medical scribes.
- “What happens to the audio?” Ours is processed in memory and discarded the moment the note drafts. No archive. The full posture is on our security page.
- “What’s the real per-note time, on my patient mix?” Test it on your accents, your languages, your noisy room, during the trial.
- “What does it cost against the time it saves?” Run the ROI math on your own visit volume, not a vendor’s.
- “Does the note quality survive my hardest visit?” Grade it with the SOAP-note rubric.
A scribe that survives those questions will probably survive your Tuesday clinic.
Start with your own clinic day
The honest way to find out how much charting time you’d save is to measure it on real visits, not to trust a number on a pricing page.
AI Medical Scribe by Patient Square launches at $89 per clinician per month (annual billing), with a 7-day free trial. The full ladder, with no asterisks, is on the pricing page, and the rate card breakdown sits beside it in our AI medical scribe pricing breakdown.
The best next step is to book a demo and watch a finished note appear about two minutes after a sample visit, then run the trial on a real clinic week and time yourself. That’s the only charting-time number that matters: yours. If you’re still narrowing the field, our how to evaluate an AI medical scribe scorecard and best AI medical scribes roundup are the next two stops.