The last patient leaves around six. Dinner happens, eventually, and the kids go down around eight. The laptop comes back out after that, open to a stack of notes from a day that had exactly zero room in it for finishing them.
Two-fifteen was the closest thing to a gap today, and a nurse used it to grab labs. Four-thirty had five minutes, spent walking a worried mother back to the front desk instead of rushing her out. Every other hour was full, the way clinic hours always are.
Call it a backlog, and you’d expect tomorrow to chip away at it. That’s not what happens. The notes get finished tonight, completely, and by ten tomorrow morning there’s a new stack exactly like it, because nothing about tonight changed how the next day fills up.
The same finding, measured twice, years apart
In 2017, a team including Christine Sinsky pulled three years of electronic health record (EHR) event logs from 142 family physicians in Wisconsin and found something specific enough to survive nearly a decade of people trying to argue with it: 5.9 hours of an 11.4-hour workday spent inside the record, 4.5 of those hours during clinic, and 86 minutes after it ended, at home.
Later research measured it differently and landed in roughly the same place. A study led by Lisa Rotenstein found the typical primary care visit generates 36.2 minutes of total EHR time, and 6.2 of those minutes happen specifically after hours, per visit, not per day. Run that across a real panel and the arithmetic gets uncomfortable fast.
Buried in that same research is the one genuinely useful thing anyone’s found. Physicians whose teams handled more of the order entry, more of the routine legwork, showed measurably less after-hours EHR time, enough of a gap that it’s worth building a practice around.
Two different research teams, measuring a decade apart, using different methods, kept finding the same shape.
Getting faster never made the debt smaller
If speed were the fix, residency should have already fixed it. A 2026 study tracked 144 emergency medicine residents across 167,010 patient encounters over five and a half years of training. As they gained experience, documentation time per encounter fell 69 percent, from an average of nearly 10 minutes down to under 3.
After-shift work stayed put anyway. Across that same stretch of training, something got done after the shift ended in 89.9 percent to 94.4 percent of encounters, no matter how far along a resident was. Year one and year four looked almost identical on that measure, even though everything else about their documentation had transformed.
A separate resident cohort found the same split earlier: Per-patient EHR time drops steadily across a training year. The share of that time happening after hours barely moves.
The instinct to be fast, thorough, and careful with every chart is exactly what makes someone good at this job, and it’s also completely beside the point here. Four years of getting genuinely better at documentation changed almost nothing about when the leftover work actually happened.
ADVERTISEMENT
If faster hands don’t touch it, something else has to.
What actually rides home in the bag
Nothing about it looks dramatic up close, just a note from this morning still open, a couple of orders that never got closed out, a portal message from lunchtime that got read once and then buried under everything that came after it. Here’s why staying late doesn’t solve it. Close tonight’s notes at ten, and tomorrow still opens with a full schedule that starts generating its own version of the same pile before lunch. Because the thing creating more work than the day has room for shows up again the moment the doors open. Staying later tonight just means tonight got handled. It doesn’t touch tomorrow at all.
A real backlog eventually meets a quiet week and shrinks. This one doesn’t get that chance, because the volume behind it was never about how busy any single day happened to be. It’s about how much of the day’s work was assigned to exactly one person from the start, and that number holds steady whether last night was rough or easy. Working faster, staying later, being more disciplined, all the usual fixes for an ordinary pile of work, don’t touch this, because none of them change who the work was handed to in the first place.
Somebody has to take some of the debt off the table
Faster typing was never going to fix this. Neither was more EHR training. The residency data already settled that; four years of measurable improvement barely moved the after-hours pattern at all.
Go back to what actually did move it. Not a quicker physician. A different team structure around them, where more of the order entry and the routine legwork lands on someone else before it ever has the chance to become tonight’s problem. Across two decades of research, on two different sides of the country, using different methods, that’s the one variable that kept correlating with less debt accruing in the first place.
The practices actually pulling this off aren’t running leaner. They’re running differently. The chart prep, message triage, and order follow-through that never needed a physician’s judgment in the first place get handled by someone else, during the day, before clinic ends. By the end of the day, there’s simply less left over to carry out the door.
Try this tonight. Look at what’s actually open on the screen, and sort it into two piles honestly: what needed your judgment specifically, and what didn’t. Most people find the second pile is bigger than they expected.
Karan Kanwar is the CEO of Central AI and Wing Assistant. Central AI provides an AI operating system for appointment-driven medical practices, handling calls, texts, web chat, and messages around the clock, qualifying patients and booking appointments directly into a practice’s existing systems. It is HIPAA compliant and designed to complement the tools practices already use.
Wing Assistant pairs that technology with skilled virtual assistants who take on the administrative work that pulls teams away from patient care. Kanwar writes on where automation and human support meet in health care operations, and how practice leaders can adopt both effectively. He shares updates on LinkedIn.
