Medical Billing Proposal: Draft Practice Quotes With AI

A medical billing proposal for a practice should show one recommended price model and one alternative (percentage of collections, flat fee per provider, or a hybrid), a scope table of what you will and will not do, an onboarding timeline and the reports you will send. AI drafts it from your discovery notes in minutes; you set the numbers.

Most billing proposals fail for a dull reason: the practice cannot tell what it would have paid last year. The fix is to price against their own recent collections, so the owner sees three monthly figures side by side rather than a rate card. AI is good at the assembly work (turning notes into a scope table, a timeline and plain-English terms) and poor at deciding your margin, so the arithmetic below stays with you.

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What a practice owner looks for on the first page

A practice owner or manager reading a billing quote is usually comparing it to one of three things: the cost of their current biller, a competing company, or doing nothing. They skim for four items in this order: the price, what is included, how long until the money moves, and who they ring when a payer rejects something. If your first page answers those four, the rest of the proposal only has to back them up.

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That gives a simple page order. Page one: a three-sentence summary of their situation in their own words, then the recommended price. Page two: the alternative price and a table of what each would have cost on their recent collections. Page three: scope, with in and out columns. Page four: onboarding timeline and reporting. Page five: terms. A proposal that opens with your company history and pushes the price to page six reads as evasive.

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Three pricing models, side by side

Two definitions belong in the proposal whichever model you choose. First, what "collections" means: payments received from payers and patients on claims you billed, net of refunds and recoupments, or something broader? Second, whether the percentage applies to services dated before you started. Practices argue most about the second one, because old claims paid after your start date arrive as "collections" and look like your work.

A note on incentives. A percentage rate pays you more when more is collected, which is fine when it comes from fewer denials and faster follow-up, and wrong when it comes from aggressive coding. Say in the terms that coding follows the clinician's documentation and that you will query rather than upcode. Practices, and their advisers, read that sentence. The tutorial on audit trails and upcoding risk in AI coding software covers how to evidence it.

Pricing a four-provider primary care practice three ways

All figures here are illustrative. Say you have met a four-provider primary care practice. Their discovery sheet shows average monthly collections of $160,000, mixed payers (a large share commercial, the rest government programmes and self-pay), a part-time biller and a front-desk team who also post payments. Their current billing cost, counting the two part-time staff at loaded cost, is about $9,300 a month. Your own cost to serve a practice that size, from your time sheets, is roughly 90 hours of biller and follow-up time at $30 loaded, $600 for clearinghouse and software, and $800 for quality checks and management: $4,100 a month.

Look at what the table tells you. Option A costs the practice more than their current $9,300, so the pitch cannot be "we are cheaper"; it has to be "similar money, fewer unpaid claims". Option B is the easiest sell on price ($700 under their current cost), but your margin is thinnest if one provider doubles their schedule. Option C sits between them and is the one I would recommend here: the base covers your $4,100 cost to serve with room to spare, and the percentage rewards you for the follow-up work.

The decision rule I would write on your own pricing sheet: recommend the model where your fee still clears your cost to serve by a set margin (say 40 percent of fee) in both a 15 percent worse month and a 15 percent better month. Option A at $136,000 collections yields $8,160, a margin of $4,060, which is under 50 percent of the fee and still clears the floor. Option B stays at $4,500. Option C yields $4,000 + $4,080 = $8,080, a margin of $3,980. All three pass, but only B and C stay predictable. Do this one-line stress test for every quote before you send it, in the spreadsheet rather than the chat window.

What to collect before asking AI to draft anything

The draft can only be as good as the discovery notes behind it. A thirty-minute discovery call gives you what the model needs, and none of it has to identify a patient. The checklist, filled in for the practice above:

• Providers and specialty: four primary care providers, one with a small procedures list.
• Monthly collections band: $150,000 to $170,000 over the last six months; no month below $140,000.
• Payer mix by percentage of collections: roughly half commercial, a third government programmes, the rest self-pay and other.
• Software: named practice management and EHR systems, and whether they already use a clearinghouse.
• Current pain, in their words: "denials sit for weeks", "nobody chases anything over 60 days".
• Who does what today: charge entry, payment posting, patient statements, credentialing, authorisations.
• Start constraints: contract notice period with the current biller, any month-end closing date.

If you have an aged-claims summary (bucket totals only, such as 0-30, 31-60, 61-90 and 90+ days), add those four numbers. Bucket totals identify nobody and are the most persuasive page in the proposal. The routine for working those buckets is in prioritising aged claims with AI; the proposal only needs to promise the cadence.

First prompt: turn discovery notes into a recommendation

Run the drafting in a business-tier AI account with training off (see the tool tiers below). Paste summary figures only. This prompt produces the page-one summary and the three-way price table:

You are helping a medical billing company write a proposal for a medical practice.
Use ONLY the facts below. Do not invent figures, payer names or promises.

Practice facts:
- 4 providers, primary care
- Average monthly collections $160,000 (range $140,000 to $170,000)
- Current monthly billing cost about $9,300
- Pain points: denials sit for weeks; nothing over 60 days is chased

Our pricing options:
A) 6% of collections  B) $2,150 per provider per month  C) $4,000 base + 3% of collections
Our cost to serve: $4,100 a month

Write:
1. A three-sentence summary of their situation, in plain words.
2. A table of what A, B and C would cost at $160,000 and at +/-15%.
3. A recommendation with one reason, and one caveat for each rejected option.
Mark any figure you calculated so I can check it.

A realistic output comes back confident and usually has one flaw. In an illustrative run the table showed Option C at the lower collections figure as $8,000 instead of $8,080, because the model rounded the 3 percent. Check every number against your sheet. The other common flaw is a recommendation sentence such as "this will increase your collections by up to 10 percent". Delete that. You have no evidence for it on this practice, and the practice will quote it back to you in a dispute.

Scope: a table that stops arguments in month three

Most billing disputes are scope disputes. A table with an "in" column, an "out" column and a "billed separately" column removes the ambiguity. Ask the AI for a first draft from your standard service list, then trim it to what you genuinely do.

The "not included" column protects you; the "billed separately" column keeps the practice from feeling cornered. A prompt that works well: "Here is our standard service list. Create a four-column scope table. Where a service depends on something the practice must supply, say what and by when." The last sentence is the useful one, because it turns vague dependencies ("timely documentation") into dates you can point to.

An onboarding timeline the practice can plan around

Practices fear the switchover more than the price. They have seen a changeover that left six weeks of claims in limbo. A week-by-week plan, with who does what, is reassurance in itself. Ask AI to lay yours out as a table and then correct it with your real durations. For a small practice that already has a clearinghouse connection, a plan like this is typical (illustrative, your own timings rule):

The week-three parallel run is the line practices remember. It gives the owner a way to say yes without feeling they have handed over the keys blind. Put it in even if your own process does not strictly need it. For the contract and access side of this stage, see client onboarding: contracts, access and AI reports.

Reports and promises you can actually keep

List the reports by name and date. A monthly package of five items is plenty for a small practice: collections by payer, a denial list with causes, an aged-claims summary by bucket, a charge-lag figure (days from visit to submission) and a one-paragraph commentary. AI can draft the commentary each month from your numbers, using the same "only the figures in this table" rule as any monthly practice KPI commentary.

Then, promise processes rather than outcomes. Good promises: claims submitted within two working days of receiving complete encounter data; every denial reviewed within three working days of the remittance arriving; a fortnightly aged-claims pass. Bad promises: a collection rate, a denial rate, "98 percent clean claims". Those figures depend on payer mix, front-desk accuracy and documentation, none of which you control. If a practice asks for a performance target, offer to report on a metric together for 90 days and agree a target from the baseline.

Second prompt: turning a scope table into plain-English terms

Terms written by lawyers for lawyers make a small practice nervous. Have the AI produce a plain-English draft that your own adviser then reviews:

Rewrite the scope table below as a one-page "What we do and what we need from you" section
for a medical practice manager. Use short sentences. Keep every date, number and exclusion exactly as given.
Add nothing that is not in the table. End with five bullet points listing what the practice must supply and by when.

[paste the scope table]

Check that no exclusion has softened. A typical slip is "not included" becoming "may be included on request", which creates an obligation you never agreed. Read the output once against the table, line by line. Contract wording beyond this summary is a matter for a qualified adviser, and so is anything about how payments are handled or held on behalf of the practice.

Four other practices, four adjustments

The same structure bends for different practices. A few scenarios to rehearse (all illustrative):

• A solo therapist with $18,000 monthly collections. A percentage works only if your minimum monthly fee covers your cost. Quote 5 percent with a $600 monthly minimum, which only bites in a month below $12,000, and say so in the first paragraph. Otherwise the practice is subsidising your onboarding effort and you will resent it by month four.
• A twelve-provider multi-specialty group. Flat per-provider pricing becomes awkward because a surgeon and a general practitioner create very different work. Price by specialty band, and say what happens when a new provider joins mid-month (pro-rata from the first billed claim).
• A practice leaving a competitor. Include a "transition of open AR" clause: who works claims dated before your start, at what rate, and for how many days. This is where most disputes occur, so give it its own heading.
• A practice with a messy backlog. Quote the clean-up as a one-off project, priced per hundred claims or per hour with a cap, and keep it out of the monthly fee. Otherwise your monthly margin disappears in the first quarter.

When you decide who to pitch next, the tutorial on outsourced billing versus in-house AI tools shows the objection from the other side, which is worth pre-empting in your summary page.

Tool tiers for drafting proposals safely

A proposal built from summary figures carries little risk, but the habit matters, because the same account will later see more sensitive material. A paid business plan with training off by default is the sensible tier for a billing company. ChatGPT Business is $25 per user per month billed monthly, or $20 billed annually, with a two-seat minimum; Claude Team is priced the same way ($25 monthly, $20 annually) for teams of 2 to 150; Microsoft 365 Copilot Business is $21 per user per month on annual billing, with an $18 first-year offer that runs to 31 December 2026 (list prices checked in November 2026, so confirm on the vendor page before you quote them). Business plans of these tools do not train on your content by default; consumer plans have a training switch you must turn off yourself.

Even on a business plan, keep the rule simple: the proposal uses totals, bands and percentages, never lines from a remittance. If a prospective practice sends you a claims file during discovery, open it in your own secure system, summarise it yourself, and paste only the summary. The related tutorial on ChatGPT for medical billing without patient information sets out the redaction habits in more detail.

A mistake worth seeing before you make it

Picture a small billing company that sends a quote saying "we will increase collections by 15 percent in the first six months". The AI wrote it into a friendly summary and the owner approved it at speed. Six months later the practice's collections are up 6 percent, because two providers have left, and the practice withholds the final month's fee, citing the sentence. It is an illustration, but a sharp one: every sentence that sounds like a result gets deleted, which is why the review checklist below exists.

The pre-send checklist

1. Every number traces to the discovery sheet or your pricing spreadsheet, and the stress test at plus and minus 15 percent still clears your floor.
2. "Collections" is defined, along with the treatment of pre-start claims.
3. No sentence promises a rate, a percentage lift or a denial outcome.
4. The scope table has a "billed separately" column and a dated list of what the practice must supply.
5. Onboarding names a parallel run and an exit check each week.
6. Coding language says documentation drives codes and you query rather than upcode.
7. The price is on page one or two.
8. Nothing in the document came from a patient-level record.

Follow-up message after sending

Do not let the proposal sit. A short message two working days later, drafted with AI and edited by you, works better than a long one. Illustrative wording: "Hi [first name], did the three options make sense against your last six months? If it helps, I can rerun them on a different month, or on the version where you keep credentialing in-house. Twenty minutes this week would settle it. [your name]". Offering a rerun on their own numbers is the useful part, because it keeps the conversation on their data rather than your rate.

If you would rather map your whole quoting process with someone, from discovery sheet to follow-up, that is what my AI implementation consultation covers. For the wider picture of where AI belongs inside a billing business, see the AI guide.

Questions billing company owners ask before sending a quote

Should a medical billing proposal quote a percentage or a flat fee?

Offer one recommended model and one alternative. Percentage of collections suits practices that want no upfront risk; a flat monthly fee per provider suits larger or steadier practices. A hybrid, with a low base plus a smaller percentage, protects your margin when volume is uneven. Whichever you pick, show the practice what each would have cost on its own recent collections.

Can I put practice data into ChatGPT when drafting a quote?

Draft with summary figures only: provider count, specialty mix, monthly collections band, payer mix percentages and software names. Never paste patient names, claim lines, remittances or anything that identifies a person. Use a business plan with training switched off, and keep the patient-level files inside the practice's own systems.

How long should a medical billing proposal be?

Three to five pages is enough for a small practice: a one-paragraph summary of their situation, the pricing option, a scope table, the onboarding timeline, reporting you will send and the terms. Anything longer usually hides the price. Put the price on page one or two, not at the back.

What should the proposal say about denials?

Say what you do and do not own. Spell out who appeals, within how many working days of a denial arriving, what counts as a denial you will work for free and what is billed as project work. Avoid promising a denial rate, because payer mix and front-desk errors sit outside your control.

Further reads

• AI for Medical Billing Companies: Seven Jobs to Automate First — Seven jobs worth automating before you sell the service.
• Best AI Tool for Medical Billing: Scrubbing, Coding, Denials — Pick tools by job so the scope table is honest.
• Using AI for Medical Billing: Spot Missed Charges From Visit Notes — A concrete way to show practices where revenue leaks.
• Can AI Do Medical Billing and Coding? What Still Needs a Human — Where a human must stay in the loop, for your terms.
• AI Denial Management for Medical Billing: Group, Appeal, Track — The denial routine your proposal promises.
• Medical Practice AI Budget: What to Fund First and What It Costs — See how the practice itself thinks about spending.
• Medical Practice KPIs: A Monthly Dashboard Built With AI — The monthly KPI pack and commentary prompt behind your report.
• AI Tools and AI Development: The Complete 2026 Guide — the AI hub, including every tutorial in the AI-for-business series.

Sources: OpenAI business pricing page (archived copy of 27 October 2026), Claude pricing page, Microsoft 365 Copilot Business page, Anthropic's commercial-training article and Microsoft's Copilot privacy documentation, checked 4 November 2026. All pricing arithmetic in this tutorial is illustrative.