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Healthcare

Practice Revenue Leakage: A 20%-to-10% Margin Scenario

Sam YangEx-CFO across trades, SaaS & services · $2.5B in total PE/banking transactions · Stanford MBA
Updated October 7, 2026·Originally published July 20, 2026·8 minute read
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Illustrative leakage waterfall

A full schedule is not the same as a collected schedule. No-shows leave fixed-cost slots empty, denials force rework and partial write-offs, and undercoding gives away revenue you already earned. A full-slot forecast can show 20% while a fictional realized scenario is 10%; that is not a measured typical practice outcome.

Fictional margin scenario, public-source inputs kept separate

8 minute readHealthcare

The short answer

The 20%-to-10% result is a fictional scenario, not a measured medical or dental profit distribution. Separate unsold appointment capacity, final denied-claim write-offs and rework costs. Undercoding is potential upside on work already performed, not a further deduction from reported profit. Source populations differ: MGMA reports a 6.81% single-specialty aggregate no-show rate in 2023; KFF reports a 19% insurer-reported in-network denial average for 2024 ACA marketplace claims, not a practice first-pass rate.

Key takeaways

  • No-shows forfeit contribution while fixed clinician and room costs continue. MGMA Stat puts the single-specialty average at 6.81%, and 10% is a planning review threshold here, not a verified quartile.
  • KFF reports a 19% insurer-reported in-network denial average for ACA marketplace claims in 2024. This is neither a ceiling nor a practice first-pass rate. An older MGMA article cites 86% potentially avoidable denials and $25.20 average claim rework cost; those are historical context, not a guaranteed recoverable share or current practice cost.
  • Undercoding quietly gives away earned revenue: billing a 99214 visit as a 99213 across a panel can cost a physician $30,000+ a year in AAFP's 2009 historical illustration; that is not a current payment-rate estimate.
  • Denials and undercoding concern work performed; no-shows are unsold capacity. Diagnose each mechanism separately rather than assuming all lost dollars can be recovered.

Practice owners judge the business by the schedule. A full schedule feels like a healthy month. But a full schedule is not a collected schedule, and the gap between the two is where a full-slot forecast can differ from realized profit. The worked 20%-to-10% example below is illustrative, not a typical observed outcome. The money leaks out through three costs that never show up as a line item labeled "loss."

The 20% that becomes 10%

Leak 1: no-shows and late cancellations

The clinician's salary and the room's overhead are fixed. An empty slot earns nothing while its scheduled fixed costs remain, and no report captures it as a loss, it just shows up as a lighter day. MGMA Stat put the single-specialty average no-show rate at 6.81%, and a rate above 10% is a planning alert on this page, not a verified population quartile. Do the arithmetic on your own schedule rather than borrowing an average: A fictional 8% of a 30-visit day is 2.4 unfilled slots, not 2.4 clinician hours. At $150 contribution per visit across 250 clinic days, that is $90,000 (2.4 x $150 x250), assuming no same-day refill. Use slot duration separately when computing lost clinician time.

Leak 2: claim denials, rework, and partial write-offs

Charges post at full value, but a meaningful share get denied on first pass and require staff rework, and some never collect. KFF's analysis of 2024 ACA marketplace claims reports a 19% insurer-reported in-network denial average, with rates varying by insurer. It is not a ceiling and not a practice first-pass denial rate. MGMA's 2020 denial discussion cites 86% potentially avoidable denials and a $25.20 average rework cost. Avoidability, appeal success and final collectible dollars are different measures. Track final write-offs and your actual rework cost rather than treating every denial as lost revenue.

Leak 3: undercoding

The quietest leak. When a visit that supports a 99214 gets billed as a 99213 out of caution, the difference is earned revenue given away. Across a panel it adds up fast: the AAFP has historically illustrated that this pattern can cost a physician $30,000 or more a year (AAFP, 2009 historical illustration). That dated dollar estimate is not a 2026 payment-rate forecast. Code only what the documented services and current payer rules support; AAFP's 2021 E/M guide explains the coding criteria. It never appears as a loss because the claim was paid, just for less than the work was worth.

Fictional waterfall on one base: assume $1,000,000 of full-slot revenue at the current code mix and $800,000 of fixed scheduled operating cost, a $200,000 forecast profit (20%). Unfilled slots reduce revenue by $80,000; final denied-claim write-offs reduce it by another $20,000; rework adds $10,000 of cost. Realized revenue is $900,000, cost $810,000 and profit $90,000, or 10% of realized revenue. This simplified example assumes no avoided variable cost and does not add initial denials to final write-offs. A separately verified $30,000 coding correction would be upside, not another reduction: before any added cost, revenue would be $930,000 and profit $120,000. These assumptions do not establish a typical practice result.

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How to find your leakage

  1. No-show cost: multiply no-show rate by annual scheduled slots and contribution per visit, net of refilled slots. Compute clinician hours separately from slot duration. That sizes the potential contribution opportunity; actual recovery depends on refill capacity, patient behavior and workflow cost.
  2. Denial cost: compute denied claim count as annual claims x first-pass denial rate. Rework cost is denied claims x rework cost per claim. Final write-off is denied charge dollars x never-collected share. Use the denied claims' own charges, not the all-claim average, and do not count an initial denial as a final loss. Front-end eligibility and prior-auth fixes target the denials your own root-cause review identifies as preventable. MGMA's 2020 article described 86% as potentially avoidable, not a guaranteed recoverable share.
  3. Coding accuracy: audit a sample of visits against documentation. If your 99214-to-99213 ratio is well below your peers, investigate possible undercoding against the clinical documentation; where the audit confirms it, correct prospective coding and have the authorized billing professional assess any permitted claim correction.

Why this is directional

The 20-to-10 figure illustrates the mechanism; it is not a measured survey of your practice. The waterfall inputs are fictional assumptions. The cited MGMA, KFF and AAFP figures are separate context with different populations and years. KFF's 19% is an insurer-reported in-network aggregate for 2024 ACA marketplace claims, not a ceiling or a practice first-pass rate. The mechanism holds: a full schedule can produce materially less profit than the full-slot forecast through unfilled slots, denial write-offs and rework. Undercoding is separate potential upside on work already performed.

Related reading:

Source dates and scope: MGMA's January 2025 discussion reports the 2023 no-show aggregate. KFF's 2024 insurer measure, MGMA's historical rework figures and AAFP's historical coding estimate have different denominators and years. They cannot be added to infer a national practice profit-margin distribution. Reviewed October 7, 2026.

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Sam Yang

About the author

Sam Yang

Founder & CEO

Founder of Level, the always-on finance team for contractors, service businesses, and ecommerce brands. Ex-CFO across trades, SaaS, and service businesses. 4 years as Director of Growth Product at BuildOps, building financial tooling used by 1,000+ commercial contractors. Four years in PE and investment banking rolling up and acquiring service businesses, $2.5B in total transactions including M&A and IPOs. Stanford MBA, Brown undergrad. The Level founding team's analysis of 2,200+ contractors ($13.25B in job revenue) across operating, private-equity, and CFO roles anchors the Level Index benchmark research.

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