How Much Time Do BMETs Spend on Documentation?
Ask an HTM director what share of a technician's day goes to documentation and you will get a shrug, an estimate, or a number remembered from a staffing consultant's slide. Ask the same question about physicians and you get peer-reviewed time-and-motion studies. Nobody has published the equivalent for the biomed shop, which is strange, because the answer drives staffing plans, backlog math, and every conversation about why CMMS data is thin.
This article puts a number on it, shows the math it implies for an HTM department, and explains why all that time still fails to produce good data.
How much time does documentation actually take?
In our field observations across HTM teams at major US health systems, the pattern is consistent. A properly documented work order takes roughly 15 minutes of writing: problem, cause, remedy, parts, labor time, failure code, and the free-text narrative. A technician closes five to six work orders on a typical day. That puts documentation at about 90 minutes to two hours per technician per day, or roughly 20% of the working day.
The range depends heavily on when the writing happens. Techs who document as they go pay the cost in constant interruption: stop the work, deglove, find a keyboard or a phone, type, return. Techs who batch it pay at the end of the shift, reconstructing the morning's repairs from memory at 4:30 pm. Batching feels faster and usually is, but the speed comes from writing less, and the record shows it.
To be clear about what these numbers are: they come from shadowing technicians and timing the work, not from a published benchmark, because no published benchmark exists. Which raises the obvious question.
Why is there no published number for HTM?
The clinical side of the same hospital has measured its documentation burden exhaustively. A time-motion study of primary care physicians found they spend nearly two hours on EHR tasks for every hour of direct patient care. A descriptive study in the Annals of Internal Medicine measured about 16 minutes of EHR time per patient encounter. Those numbers created the political will, and the market, for the ambient AI scribes now standard in clinical documentation.
HTM never got its version of those studies. Work order time is recorded in the CMMS, but documentation time is not a field in any CMMS we have seen: the minutes spent typing disappear into "labor time" or into unpaid end-of-shift overtime. What does not get measured does not get fixed, and it certainly does not get budgeted for.
The result is that most departments carry a significant, invisible line item. Making it visible is worth doing even if nothing else changes, and the method is simple enough to run in a week. We describe it below.
What does 20% cost an HTM department?
Run the math on a 10-technician shop. If each tech spends roughly a fifth of the day documenting, the department spends about 16 hours a day on data entry. That is two full-time positions' worth of skilled labor, typing.
Now put that against the labor market. As 24x7 Magazine reported in its coverage of HTM workforce shortages, the field faces about 7,300 openings a year against roughly 400 graduates from formal programs, with a wave of retirements approaching. AAMI's State of HTM survey tells the same story from the demand side: the work keeps growing while the pipeline does not.
In that market, a director who cannot fill two open reqs is, on paper, already paying for two FTEs of documentation. The documentation tax is the one capacity lever that does not require hiring anyone.
At one health system where we shadowed technicians, a senior BMET had developed a workaround that says everything about the problem: he photographed device screens and part labels all day on his phone, then scrolled back through the camera roll at the end of the shift to reconstruct what he had done. The phone had become the real capture system. The CMMS got whatever survived the transfer.
Why doesn't all that time buy good data?
Here is the uncomfortable part: after paying 20% of capacity, the data is still thin. Monty Gonzales made the point memorably in AAMI News with the two-word work order note, "Good to go," and the framing that follows from it: garbage in, garbage out. Every benchmark, AEM justification, and AI initiative downstream inherits whatever the work order says.
The reason the time does not translate into quality is timing. Documentation written at the end of shift is not a record; it is a reconstruction, and reconstructions flatten detail: the error code that appeared twice and vanished, the diagnostic dead ends, the note about a second pump on the same floor doing the same thing. None of that survives eight hours of new problems landing on the bench.
This is not a technician problem, and directors who treat it as one will keep getting the same results. Nobody becomes a biomed because they love typing. Asking someone to do skilled work with both hands inside a device and then write it up from memory is a workflow design that reliably produces "Good to go," no matter how good the tech is or how stern the staff meeting.
What can HTM leaders do with this number?
First, measure your own. Pick five technicians, one ordinary week, and have them tally documentation minutes per work order, separating as-you-go writing from end-of-shift batching. Two numbers fall out: your department's real documentation tax, and how much of your record-writing happens from memory. Both are worth knowing before any data quality initiative, benchmarking effort, or AI purchase.
Second, attack the capture moment rather than the review stage. Templates, mandatory fields, and audits all operate after the detail is already lost. The gains are at the bench, while the tech's hands are still inside the device. That is the problem we build for at Leera: ambient voice documentation that captures the work as it happens and drafts the work order for the tech to review, built in the field with HTM teams at major US health systems. How that works end-to-end is covered in our guide to voice documentation for CMMS.
However, a department solves it, the first step is the same: stop treating documentation time as invisible overhead. A fifth of your capacity deserves a line in the plan.
FAQ
How much time do BMETs spend on documentation per day? In our field observations across HTM teams, roughly 90 minutes to two hours per technician per day, or about 20% of the working day. A properly documented work order takes about 15 minutes to write, and most techs close five to six a day.
Is there a published industry benchmark for HTM documentation time? No. Physician documentation time has been measured in peer-reviewed time-motion studies, but no equivalent published benchmark exists for HTM. Departments that want a number need to measure their own, which takes about a week.
Does documentation time show up in CMMS labor hours? Usually not as a separate figure. Typing time gets absorbed into overall labor time on the work order or pushed into end-of-shift batching, which is why the cost stays invisible in most staffing plans.
Why do work orders stay thin if techs spend so much time on them? Because most documentation is written from memory at the end of the shift. Reconstruction flattens detail regardless of effort, so the fix is capturing information during the work rather than adding more review steps after it.
Dima Okhrimchuk, CEO & Founder, Leera AI