Financial Analysis · Healthcare
A practice model built on provider productivity and payer mix, not wishful volume
A healthcare practice lives or dies on how many patients each provider sees, what each visit collects after the payer takes its cut, and how long it takes cash to arrive. We model those drivers directly so a startup, an acquisition, or a roll-up is priced on economics you can defend.
The Outcome
What a real financial model gives you
Not a spreadsheet of wishful numbers — a model built from your real drivers that a lender or investor can actually trust.
Revenue modeled from real collection rates
We build revenue from encounter volume and payer-specific net collections, so the top line reflects what you actually bank, not gross charges.
A de novo vs. acquisition comparison
A side-by-side model of building a practice from scratch versus buying one, with the ramp, the cash burn, and the breakeven month made explicit.
A valuation you can bring to a deal
A model that translates a target practice's normalized earnings and provider productivity into a defensible value and financing structure.
How we work
Here’s how we’d model it — from your drivers, not our wishes
We won’t hand you a hockey-stick built on invented assumptions. What follows is exactly how we’d model your business — from your real drivers, with transparent, stress-tested assumptions, and honesty about what can’t be known before you have the data. Where a number genuinely can’t be forecast yet, we build a framework to fill, not a fiction to sell.
Who it’s for: Physicians, dentists, and specialists starting or buying a practice; multi-site groups and DSO/MSO platforms modeling roll-up economics; and healthcare operators planning provider additions, new locations, or a capital raise.
What We Model
Four modeling workstreams for practices
Each workstream begins with a real decision, buy or build, add a provider, open a site, and ends with a model you can open and change. We build from your schedule data and payer contracts; where a driver depends on ramp or contracts not yet signed, we make the assumption explicit and stress it.
Revenue Engine
Provider productivity & payer-mix model
The question: How much revenue does each provider actually generate once you account for encounter volume, service mix, and what each payer really pays?
What we’d build: We model revenue bottom-up from provider schedules and encounter volume, apply payer-specific net collection rates by service, and produce a revenue engine where changing a provider's productivity or your commercial-vs-government mix moves the whole model.
De Novo vs Buy
Startup vs. acquisition decision model
The question: Is it smarter to build a new practice and absorb the ramp, or buy an existing one at a multiple and inherit its cash flow on day one?
What we’d build: We build parallel models, one for a de novo build with its patient-panel ramp and pre-revenue burn, one for an acquisition with its purchase price, financing, and existing collections, and put breakeven month, total cash required, and multi-year returns side by side.
Cash & Collections
DSO & collections cash model
The question: How long does it take a dollar of service to become cash in the bank, and how much working capital does that lag demand as you grow?
What we’d build: We model days sales outstanding by payer, connect it to a working-capital schedule, and show how faster or slower collections change the cash you need to fund payroll and rent between service and payment.
Roll-Up Economics
Multi-site & roll-up model
The question: Do the economics of adding sites or acquiring practices improve with scale, or does added overhead eat the synergy you're paying for?
What we’d build: We build a platform model that stacks multiple locations, layers in shared MSO overhead, and tests whether centralized billing, purchasing, and admin actually expand margin, with the integration cost shown honestly rather than assumed away.
The Fuller Scope
The fuller scope
Beyond the four core workstreams, practice owners and platforms ask us to model specific decisions. These come up most often, each built from your real drivers with assumptions you can see and change.
New-provider hiring economics
Modeling the ramp, guarantee, and productivity a new physician or associate needs to hit before they cover their own cost and start contributing.
Ancillary and service-line expansion
Testing whether adding imaging, lab, aesthetics, or a new service line earns its capex and space, built on realistic utilization.
Payer-contract renegotiation impact
Showing how a rate change from a specific payer flows through to collections and margin, so you know what a contract is worth.
De novo site selection and ramp
A location-by-location model of patient-panel buildup and cash burn so you fund each new site to breakeven with eyes open.
Practice acquisition due diligence
Normalizing a target's earnings, testing its payer mix and provider dependence, and pressure-testing the seller's add-backs.
Partner buy-in and buy-out valuation
A model for pricing a partnership stake or funding a retiring partner's exit without starving the practice of cash.
Capital raise or lender package
A projection model and supporting narrative structured for an SBA lender, bank, or equity partner evaluating the practice.
The Questions the Model Answers
The questions the model answers
A model earns its keep by answering the decisions that ride on the numbers. Here’s what ours is built to answer.
Net revenue per provider
Built from encounter volume and payer-specific net collections, so you see what each provider truly contributes after payer discounts.
Net collection rate by payer
Modeled from your remittance data, so the revenue line reflects real reimbursement rather than gross charges.
Breakeven month for a new site or provider
The ramp model pinpoints when a de novo location or new hire turns cash-flow positive and how much you fund to get there.
Days sales outstanding and working capital
The collections model links DSO to the cash you must carry between rendering service and getting paid.
Buy-vs-build total cash and return
The decision model compares total cash required and multi-year return for acquiring versus building.
Margin lift from scale
The roll-up model isolates how much overhead leverage each added site produces, net of integration cost.
We build revenue from your actual encounter volume and payer-specific net collection rates, and we normalize a target practice's earnings from its real remittances, not from gross charges or a broker's pro forma. For a de novo build, patient-panel ramp is genuinely uncertain, so we model it as an explicit, adjustable curve and show breakeven under conservative, base, and optimistic ramps rather than a single confident line. The model is a framework for weighing the decision under different conditions; it is not a forecast of guaranteed patient volume or returns.
The Engagement
Investor-grade, driver-based, and yours to run
A scoped modeling engagement built from the drivers you actually control — not a top-down guess. We map the assumptions, build the model, stress-test it with scenarios, and hand you a tool your team can run, present, and defend.
Transparent and honest. Every assumption is visible and sourced, downside cases are shown rather than hidden, and where something can’t be known yet we say so — a model you can stand behind, not one that flatters a deck.
Every business is different. Discovery is where we map the drivers your model runs on.
How It Works
From drivers to a model you can defend
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Discovery & drivers
We map the real operating drivers — pricing, volume, cost structure, cash timing — and the decision the model has to support.
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Model build
A clean, driver-based, three-statement or purpose-built model with a transparent assumptions tab everything flexes from.
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Scenarios & sensitivity
Base, upside, and downside cases plus the sensitivities that show which assumptions actually move the outcome.
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Review & pressure-test
We stress the model against the questions a lender or investor will ask — coverage, runway, returns, breakeven — and fix what doesn’t hold.
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Deliver & support
You get a documented model your team can run, plus support taking it into the raise, the loan, or the board meeting it was built for.
FAQ
Healthcare Practices — financial-modeling questions
Will the model tell me a practice acquisition will pay off?
It will tell you what the numbers imply under stated assumptions and where the deal is fragile. Whether it pays off depends on patient retention, payer contracts, and provider behavior we can't promise, so we stress-test rather than reassure.
How do you handle payer mix and reimbursement?
We model net collections by payer from your actual remittance data. If you're a startup without history, we build explicit assumptions from your expected contracts and show how sensitive the model is to them.
Can you model a de novo build when I have no historical data?
Yes. We build the patient-panel ramp as an adjustable assumption grounded in comparable openings and your market, and we show breakeven across a range of ramp speeds rather than one optimistic path.
Is this financial or clinical or legal advice?
Strictly financial modeling. We don't give clinical, legal, tax, or coding advice, and for regulatory and compliance questions we'll tell you to bring in the right specialist.
Can you build a model for an SBA lender or bank?
Yes. We structure the projection and narrative around what a healthcare lender evaluates. We can't guarantee approval, but we present your economics in the format and terms they expect.
Do you work with DSOs and multi-site groups, not just single practices?
Yes. The roll-up workstream is built for platforms stacking multiple locations and testing whether centralized overhead actually expands margin.
What do you need from me to start?
Provider schedules and encounter volume, payer mix and net collections, a recent P&L and balance sheet, and for an acquisition, the target's financials and add-backs. For a startup, your expected contracts and staffing plan.
Do you keep supporting the model after handoff?
The model is yours and we teach you to run it. Practices commonly bring us back before a new provider, a new site, or a financing decision to refresh and re-stress the assumptions.
The Full Practice