Charge Capture Leakage Calculator
A missed charge never shows up as a denial. There is no rejection to appeal and no line on a dashboard, so the revenue is gone before anyone notices it left. This model prices that gap from your own net patient revenue, encounter volume and current leakage assumption, benchmarked against HFMA's published ceiling for charge integrity leakage. It stops at one figure: the ceiling any automation business case has to beat before it is worth signing.
Updated August 10, 2026Free, no signupRuns in your browser
Your organisation
After contractual allowances, the figure on your income statement, not gross charges.
Billable encounters across the year, used only to produce a per-encounter reading below.
Leakage assumption
Defaults to HFMA's published ceiling for charge integrity leakage. Edit if an internal audit gives you a better number.
Your model
Annual revenue lost to leakage
$1,500,000
$150,000,000 net patient revenue at a 1% leakage rate, across 150,000 encounters a year.
Your modelled leakage against HFMA's published ceiling
The HFMA figure is a stated ceiling, not an average. Sitting above it is worth a look; sitting below it is not proof leakage is under control, only that it is under this one benchmark.
What an automation business case has to beat
$1,500,000 is the addressable ceiling, not a promised return. No recovery rate is assumed above, because no publisher tracks what share of charge capture leakage a given automation intervention typically recovers. Measure a vendor’s projected annual savings against this figure before you sign, and expect the real recovery to land below it.
Modeling estimate, not a quote or a guarantee. Assumptions are editable and every figure above is derived from the values you entered. HFMA states its figure as a ceiling, not a benchmark to hit exactly, and the leakage rate above is editable for exactly that reason.
How this is calculated
annual revenue lost = net patient revenue x leakage rate
monthly revenue lost = annual revenue lost / 12
revenue lost per encounter = annual revenue lost / encounters per year
HFMA published ceiling = net patient revenue x 1% (HFMA’s stated ceiling for charge integrity leakage, applied to net patient revenue as the closest figure most finance teams have on hand)
Methodology and assumptions
What the model does, and what it refuses to guess
Annual leakage is net patient revenue multiplied by a leakage rate. The default rate, 1 percent, is not this tool's estimate: it is HFMA's own published figure for charge integrity leakage, stated identically in two separate HFMA articles five years apart. "Avoiding the High Cost of High-Capture Leakage" (2017, updated 2025) states that "as much as 1 percent of net charges are lost due to charge integrity leakage." "Capturing All Charges: the Operational Reality" (2019, updated 2022) states that "hospitals lose as much as 1 percent of their potential annual net revenue" to charge capture issues. Neither article discloses a survey, sample size or underlying methodology behind that number, and the two use slightly different denominators, net charges in one and net patient revenue in the other. This tool applies the figure to net patient revenue, the number most finance teams have on hand, and states that substitution here rather than leaving it silent. Both articles frame 1 percent as a ceiling, "as much as", not an average, which is why the field is labelled a leakage assumption and left fully editable rather than presented as a fact about your organisation.
Why encounter volume does not change the total
Encounter volume is used only to divide the annual total into a per-encounter figure. It does not multiply into the leakage total, because the leakage total is already a share of net patient revenue, which already reflects every encounter billed. Using encounter count to scale the dollar figure a second time would double count the same revenue.
What it refuses to do
It does not assume a recovery rate for automation. Prior authorization and denial tooling can point to a measured before-and-after; charge capture automation cannot, because no publisher tracks what share of leakage a given intervention typically recovers. Guessing one would turn the ceiling above into a promised return, which it is not. The figure this tool produces is the addressable amount, the number a vendor's projected annual savings has to be measured against, not a forecast of what you will get back.
It also does not split the total into missed charges versus under-coded charges. HFMA's own copy names both as causes of charge integrity leakage but does not publish a share attributable to each, so inventing a split would manufacture precision neither article offers. And it does not apply AAPC's or AHIMA's commonly cited 95 percent coding accuracy benchmark to derive or check the leakage rate: that figure appears repeatedly in coding-education material from both bodies, but this tool could not locate a citable primary AAPC or AHIMA publication stating it with a methodology behind it, as opposed to secondary summaries of it, so it is left out rather than used on secondhand authority.
Why the range is 1 percent, not 3 to 5 percent
Higher figures, commonly 1 to 5 percent or 3 to 5 percent of net revenue, circulate widely in vendor and consultancy material about charge capture. This tool checked HFMA's own site directly for the source of those figures and could not find one: both HFMA articles it could locate state only the 1 percent ceiling above. Until a primary HFMA, MGMA or AHA publication for a wider range turns up, this tool uses the figure it could verify rather than the figure that is more common in secondary sources.
What it leaves out
Denial-driven write-offs are a related but separate loss, already modelled in the denial rate benchmark. Payer mix, specialty mix and documentation workflow all affect how close an individual organisation sits to HFMA's ceiling, and none of them are represented here. Overcoding, billing at a higher level than the documentation supports, is a compliance and False Claims Act exposure in the opposite direction from the leakage this tool prices, and is not something this model touches.
Sources
The named reports and rules this calculator’s figures are drawn from. Where a figure moves, this calculator moves with it.
Questions we get asked
Where does the 1 percent leakage figure come from?
HFMA, stated the same way in two separate articles published five years apart. "Avoiding the High Cost of High-Capture Leakage" (2017, updated 2025) puts it as "as much as 1 percent of net charges", and "Capturing All Charges: the Operational Reality" (2019, updated 2022) puts it as "as much as 1 percent of potential annual net revenue." Neither publishes a survey or methodology behind the number, so this tool treats it as a stated ceiling rather than a measured average, and leaves it fully editable.
Why does the calculator apply the rate to net patient revenue when one HFMA article says net charges?
Because net patient revenue is the figure most finance teams can enter without pulling a separate gross charge schedule, and it is the closest match to the second HFMA article's own denominator. That substitution is a modelling choice this tool is making, not something HFMA specifies, and it is stated in the methodology rather than left hidden in the formula.
Why doesn't encounter volume change the total, only the per-encounter figure?
Because net patient revenue already reflects every encounter billed across the year. Multiplying the leakage total by encounter count a second time would double count the same revenue. Encounter volume is used only to divide the annual total into a per-encounter reading, which is a division, not a separate assumption.
Why is there no assumed recovery rate for what automation would actually get back?
Because no publisher tracks what share of charge capture leakage a given automation intervention typically recovers, unlike denial rework or prior authorization, where a before-and-after can be measured directly. Assuming a recovery percentage here would turn a sourced ceiling into an invented forecast. The figure this tool shows is the addressable amount, the ceiling a vendor's projected savings has to be measured against, not a promise of what you will collect.
Why doesn't this use AAPC's or AHIMA's 95 percent coding accuracy benchmark?
That figure is widely repeated in coding-education material, but this tool could not find a citable primary AAPC or AHIMA publication stating it alongside a methodology, only secondary summaries of it. Rather than borrow a number on secondhand authority, this tool leaves coding accuracy out of the formula entirely and prices leakage from the one figure it could verify at the source.
Other sites say hospitals lose 3 to 5 percent of net revenue to charge capture. Why does this tool use 1 percent?
Because 1 percent is the figure this tool could actually verify against HFMA's own published articles, and 3 to 5 percent is not. That wider range appears often in vendor and consultancy material, but checking HFMA's site directly turned up only the 1 percent ceiling, stated twice, five years apart. If a primary HFMA, MGMA or AHA publication for the wider figure surfaces, this tool will cite it and move; until then it uses what it can source rather than what is more commonly repeated.
How is this different from the denial rate benchmark tool?
They price two different failures. The denial rate benchmark covers claims that were submitted, then rejected. This tool covers charges that were never submitted at all, or were submitted below the level the service warranted, which is exactly why charge capture leakage does not appear on a denial report: there is no claim to deny.
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