TL;DR: The ROI of automating patient data fetching in CureMD is documents per month × minutes of staff time per document × loaded hourly staff cost, minus the software cost, plus the downstream revenue effect of records arriving before the visit rather than after. Most practices get the first three inputs wrong because they estimate handling time instead of measuring it, and they omit the fourth entirely. Build the model from your own numbers — vendor ROI calculators are marketing instruments.
Start with the number you don't have
Ask a practice administrator how much time the team spends chasing outside records and you'll get a confident answer that is usually about half the real figure.
That's not carelessness. Records retrieval never appears as a task on anyone's job description. It happens in 90-second increments, spread across a medical assistant, a front-desk coordinator, a referral clerk, and occasionally a physician who gave up waiting and logged into the portal himself. No single person experiences it as significant, so the organization doesn't either.
Fix this before you model anything. Pick two ordinary weeks, and have everyone who touches outside records log four fields each time:
- Document type
- Source it came from
- Minutes spent, start to finish
- Whether it was needed for a visit that had already been scheduled
Count the whole chain: noticing the record is missing, logging into the source, hunting through it, reading the document, deciding where it belongs, filing it in CureMD, and closing the loop. Practices that measure rather than estimate routinely find the true figure is 1.5 to 2 times what they assumed.
The core ROI formula
Once you have real numbers, the base calculation is straightforward.
Annual labor cost of manual retrieval = documents per month × average minutes per document ÷ 60 × loaded hourly cost × 12
Two notes on inputs. Loaded hourly cost means wages plus payroll taxes plus benefits — typically 1.25 to 1.4 times base wage, and using base wage alone understates the case by a quarter. And use a blended rate that reflects who actually does the work, including the times a nurse or physician does it.
A worked example for a mid-to-large independent practice:
- 1,400 documents per month requiring retrieval
- 9 minutes average handling time
- $28 per hour loaded cost for the blended staff mix
That's 210 hours a month, or $5,880. Annually: $70,560, and roughly 1.2 full-time equivalents of work that nobody hired for.
Run this with your own three numbers before you take a vendor call. It changes the conversation, because you're no longer evaluating a price against a feeling.
Sanity-check the result against something you already know. Divide the annual figure by 2,080 hours and see how many FTEs it represents, then ask whether that matches your sense of the practice. If the model says 3.5 FTEs and you have four people total in the back office, one of your inputs is wrong. If it says 0.2 FTEs and your MAs complain about records daily, you undercounted the documents. The arithmetic is easy; the value is in the inputs, and the FTE cross-check is the fastest way to catch a bad one.
It's also worth splitting the number by document type before you go further. Automation gets deployed one document type at a time, so a single blended annual figure tells you the size of the prize but not the sequence. A per-type breakdown tells you which rule to write first.
The costs practices leave out of the model
Labor is the visible cost and usually not the largest one. Four others belong in the calculation.
Rescheduled and unproductive visits. When outside records haven't arrived, some visits get pushed and some happen anyway with an incomplete chart. Count how often this happens per month and multiply by your average visit revenue. Even a handful a week is meaningful against a $70,000 labor baseline.
Denials tied to missing documentation. Claims denied for lacking supporting records cost you the rework and sometimes the revenue. Pull your denial reasons for the last quarter and isolate the documentation-related ones.
Overtime during volume spikes. Records volume isn't flat. Post-holiday surges and referral-heavy seasons produce overtime that the average-hours model hides.
Turnover. Records chasing is the part of the job people describe as the reason they left. Turnover cost for an administrative role runs meaningfully into the thousands once you count recruiting, onboarding, and the productivity gap. The 2026 MGMA Regulatory Burden Report ties rising administrative load directly to burnout and access problems, and 40% of practices now run three or more full-time administrative staff per physician on this category of work.
Be honest about the confidence level of each of these. The labor number you can measure. The others are estimates, and it's better to present them as a range than to inflate the model with false precision — a CFO who catches one soft number stops trusting the whole thing.
What goes on the other side of the ledger
A model that only counts benefits isn't a business case. Four costs belong on the other side.
Software cost. Usually subscription-based, priced by volume, seats, or workflow. Get it as an annual figure including any implementation fee.
Implementation time — yours. Somebody at your practice spends real hours on document inventory, filing rules, and credentials. Budget 20 to 40 hours of an ops person's time spread over the first six weeks, and cost it at their loaded rate.
The supervised validation period. For four to six weeks, a human reviews the automation's filing decisions. That's temporary duplicate work, and pretending it doesn't exist is how a project loses credibility in week two.
Ongoing exception handling. Automation won't resolve everything. If 15% of documents escalate and each takes six minutes, that's real recurring labor. Subtract it from your savings rather than assuming it away.
Payback for most practices lands somewhere between four and nine months once these are included, driven mostly by document volume. Below roughly 500 documents a month the math gets thin and a partial approach may serve you better.
One cost that belongs in the conversation even though it doesn't belong in the spreadsheet: attention. An automation project competes with everything else your ops team is carrying this quarter. If you're mid-EHR-migration or absorbing an acquisition, the model may be excellent and the timing still wrong. Say so out loud rather than letting a good business case get half-implemented during a bad quarter — a stalled rollout costs you the software fee, the setup hours, and the credibility you'd need to try again next year.
Where the second-order revenue shows up
The labor savings justify the purchase. The revenue effect is what makes people glad they did it, and it's the part missing from most models.
When records arrive before the visit instead of during it, three things change. Visits stop getting rescheduled for missing information. Documentation supporting the claim is in the chart when the claim goes out, which shows up in your denial rate a quarter later. And providers stop absorbing the delay — the physician who spends eleven minutes hunting for an outside imaging report is spending clinical time on clerical work, which is the most expensive labor substitution in the building.
Quantify the piece you can. Pull your rescheduled-for-missing-records count and your documentation-related denial count, apply your average visit revenue and average claim value, and present it as a range. Leave the physician-time argument qualitative — it's real, but a number you can't defend weakens the parts you can.
Honey Health's Data Fetching agent is priced as operating expense against this model rather than as a capital project, which is the comparison most practices are making: subscription cost against the labor it displaces, not against an interface build.
How to present this to a board or partners
Three slides, no more.
Slide one: the measured current state. Documents per month, measured minutes per document, loaded cost, annual total. One number, sourced from your own two-week study. Say it was measured, not estimated — that distinction is what earns the room's attention.
Slide two: the model with ranges. Software cost, implementation cost, validation period, ongoing exception handling, against labor savings and a conservative range on second-order revenue. Show the payback month. Use the low end of every estimate; a case that survives pessimistic inputs doesn't need defending.
Slide three: what you'll measure after. Percentage of charts complete 24 hours before the visit, staff hours per week on retrieval, exception queue age. Commit to reporting these at 90 days. Partners approve spending more readily when the person asking has already said how they'll be held to it.
Skip the vendor's ROI calculator entirely. Partners discount numbers that came from the company selling the thing, and they're right to.
Expect one question and prepare for it: what happens if this doesn't work? Have an answer that isn't optimism. A pilot scoped to one or two document types, a defined accuracy threshold that has to be met before expanding, and a contract term short enough that a failed pilot is a bounded loss. Boards approve bounded downside far more readily than they approve confident upside.
Frequently Asked Questions
What is a realistic payback period?
Four to nine months for most practices, driven mainly by document volume and current handling time. High-volume practices with long handling times see payback faster. Under roughly 500 documents a month, expect the longer end and consider automating only your top one or two document types.
How do I calculate loaded staff cost?
Take the base hourly wage and multiply by 1.25 to 1.4 to account for payroll taxes, benefits, and paid time off. Use the blended rate across everyone who actually touches records, not just the lowest-paid person on the list. Your practice's own benefits load is the accurate multiplier if you have it.
Should I count the staff time as savings if I'm not cutting headcount?
Yes, but label it as capacity rather than cash savings, and say what it will be used for. Most practices redeploy the hours to prior authorization follow-up or referral coordination — work that is already behind. A board will accept recovered capacity as a benefit; it won't accept recovered capacity presented as payroll reduction that isn't happening.
What if the vendor's accuracy is lower than promised?
Model it. If 15% of documents escalate to a human instead of the 5% quoted, recalculate with 15% and see whether the case still holds. Build the escalation rate into your contract discussion and ask what happens if it exceeds the threshold. A case that only works at the vendor's best-case numbers isn't a case.
Does automating data fetching reduce denials?
It reduces the denials that stem from missing or late documentation, which is a subset of your total. Pull your denial reasons for the last quarter and isolate the documentation-related ones — that's the addressable slice. Denials from coding errors, eligibility problems, or medical necessity disputes are different problems with different solutions.
