Downtime is not a single number - it is four overlapping ones
When dental practice owners ask "what does an hour of downtime cost?" the honest answer is that the cost is not a single dollar figure. It is the sum of four things: the lost revenue from the schedule the operatory could not run, the labor cost of the staff who could not work, the downstream rescheduling friction, and the harder-to-quantify trust cost with the patients who were affected.
We will work through each component honestly, with the math made visible, so you can compute your own number rather than borrow someone else's average.
Component 1: Lost production from the affected schedule
If a workstation cannot reach Dentrix, the operatory tied to that workstation usually cannot complete the visit it scheduled. Production-per-chair-hour varies dramatically by practice mix - a hygiene-heavy schedule and a restorative-heavy schedule sit at very different points.
The math, made explicit:
Lost production per downtime hour = (chairs offline) × (your practice's production-per-chair-hour for the affected schedule block)
If you have never computed your own production-per-chair-hour, your practice-management software's reporting can produce it from any 90-day window. This number is the foundation; every other downtime cost is calibrated relative to it.
Component 2: Staff cost during the outage
An associate, a hygienist, and an assistant standing in an operatory that cannot start the procedure are still on payroll. If the schedule cannot recover the time, that cost is sunk. If the schedule can recover (visits get rescheduled into open slots later in the week), the cost is "only" the rescheduling friction (component 3) - but the labor hour itself is gone either way.
Component 3: Rescheduling friction
The hidden tax of downtime is the conversations that happen for the next two weeks: "I'm sorry, we need to move your appointment." A meaningful share of those rescheduled patients no-show or push out by a month or more. The administrative cost of the rescheduling itself, plus the small but real attrition rate, is component 3.
Our rough working estimate (from the corpus, not yet in the verified-figure ledger and so rendered here as —): each rescheduled visit costs the practice approximately —% of its full visit revenue in expected attrition. When the verified figure clears the ledger, this paragraph updates.
Component 4: Trust cost
The least quantifiable component, and the one practice owners under-weight. A patient whose appointment was disrupted by "our computer is down" rates the practice's professionalism differently for months. We do not try to put a dollar number on this, but it is real and asymmetric - a practice rarely gains a patient because of strong IT; it can lose them because of weak IT.
A worked example (illustrative, not normative)
A four-chair practice with $400/chair-hour mixed production loses three chairs to a Dentrix outage from 9:00 AM to 11:30 AM (two and a half hours).
- Lost production:
3 chairs × 2.5 hours × $400 = $3,000 - Staff still on payroll during the outage: roughly
$300-$500 - Rescheduling friction across the affected ~10 visits:
~—(depends on your no-show recovery rate) - Trust cost: real but uncomputed
The conservative floor for this single morning is in the low four figures. Repeat events compound nonlinearly.
What an autonomous RMM does about this
The argument for closing the failure-to-fix loop in seconds is not "we save the practice $N" - it is "we change the distribution of outage durations." A Dentrix lock that an autonomous agent clears in under a minute does not produce a measurable component-1 cost. A Dentrix lock that waits for a phone call and a remote session is the worked example above.
The right way to read autonomous remediation is as a tail-risk-reducer, not an SLA. The median outage gets shorter; the outages that go to thirty minutes or two hours get rarer.