Two pieces on getting paid · Dark Horse Works
For Jane · from Eric

We met at Venture Café, and I said I would send you these two pieces.

Oraxis sells a cleared, staffed, billable block rather than a room. These two pieces do the same thing with price. They ask who carries the risk inside an episode, who gets paid when that risk drops, and how to put the answer in three sentences a CFO can repeat without you.

They were written for a session with health-tech founders and investors and are still unpublished, so please keep them inside your team.

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One · the operator read

From Pilot Purgatory to the Three-Minute Money Story

How health-tech startups can finally get paid for the value they create.

Smart brief

Many health-tech ventures stall in pilot purgatory not because their solutions lack merit, but because they misunderstand how value is proven, priced, and purchased in U.S. healthcare. Teams fixate on “getting a pilot,” “showing clinical lift,” or “finding the right champion,” without realizing that pilots rarely convert unless they tie to a clear, testable economic logic that aligns with the risk-bearing customer. By tracing the flow of incentives across administrators, operators, and financial risk holders, we show that productionized adoption depends less on technical capability and more on whether a startup can articulate, in advance, who wins economically, by how much, and under what conditions.

The growth challenge reframes into three disciplines:

  1. start with a specific workflow or episode and surface the hidden failure costs, manual rework, and leakage that define the real economic baseline;
  2. treat pricing as a portfolio of testable assumptions rather than a one-time number, linking each assumption to a counterfactual and a small, inexpensive test;
  3. craft a concise “three-minute money story” that shows how a pilot becomes a contract, how a contract becomes a budget line, and how learning compounds into durable value.
Companies that transform pilots into economic commitments, through clear baselines, pre-agreed success metrics, and a repeatable value narrative, convert complexity from a friction point into a scalable advantage.

The slide that kills the deal

In health-tech, the single slide most likely to quietly kill a deal is not your science, or your UX, or your team slide. It is your price slide.

You have probably seen it happen. The clinicians love what you are doing. The innovation folks are enthusiastic. And then a CFO or benefits leader leans back, looks at your price, and says some version of: “I like it, but I don’t see how this changes our economics under the contracts we’re actually on.”

Translation: “I can’t connect this to how we make or lose money, so I can’t justify paying you.”

Most founders react by doubling down on the tools they already know: more ROI spreadsheets, one more advisory board, a bit more benchmarking, a few more pilots. But across dozens of companies there is a deeper pattern. The issue is not that your number is slightly too high or too low. The issue is that the whole money story is anchored on the wrong things.

Founders are taught to start with codes and TAM. “We’ll get a code, we’ll get reimbursed, it’s a billion-dollar market.” That sounds sensible, and it hides a critical flaw. Neither codes nor TAM slides tell you who actually gets paid when your product works. In a system where risk has been quietly shifting for decades, that flaw is fatal.

When utilization spikes, somebody gets hurt financially, and it is not always the logo on the insurance card. A majority of large employers are self-insured; it is their money at risk. More and more, health systems and physician groups are in bundles and shared-savings deals, bonused or penalized on the total cost of care rather than line-item volume. The payer often acts more like the plumbing than the actual risk-bearer.

Now layer the usual pitch on top of that reality. If your story is built around a code and a fee-for-service schedule, but your best customers make or lose money under episodes, population targets, and self-funded benefit plans, you are solving yesterday’s problem in a language that does not match their P&L. That is why smart CFOs smile, stall, and move on.

So the real commercial question is not “can we get reimbursed?” It is:

If we’re right about our outcomes, who gets the bonus check, and how do we build everything around them?

Once the world is reframed around that question, a different path appears. Instead of starting with a disease area and a TAM number, start with a specific episode or population and ask who actually bears downside risk. Instead of obsessing over a code, map the contracts: DRGs, bundles, shared savings, self-insured arrangements. Pick one patient journey and identify where you genuinely move the needle on avoidable cost: readmissions, complications, ED revisits, post-acute days, low-value imaging.

For every thousand of these patients we touch, we realistically avoid about this many events, worth roughly this much to this specific risk-bearing customer.

That is not a fantasy spreadsheet. It is the beginning of a money story rooted in their actual economics.

Stop there and you would still be missing the hardest part: getting a real decision out of a real buying group. You are not selling to “a hospital” or “an employer.” You are selling into a team: the clinical champion, the gatekeepers in value analysis and IT, the economic buyer, the external partners who influence benefits or coverage. Those people do not just need to be convinced individually. They need to be aligned with each other.

The companies that win are not the ones with the friendliest relationship or the longest feature checklist. They are the ones that teach these buying groups something uncomfortable but true about their own world, then give the internal mobilizer the tools to carry that story forward when you are not in the room. It sounds like this:

You’re leaving money on the table because your innovation pipeline is optimized for codes and pilots, not for the contracts that actually drive your risk and bonus checks.

Then you show them, concretely, on their data and their contracts, how that plays out in one service line or population they care about. You let them feel the gap between the savings they think they are capturing and the savings they could capture by engineering for the real risk-bearer. That is the head and gut moment where a serious buyer leans in. Not because you flattered them, but because you just explained their own business back to them more clearly than most of their vendors, and some of their colleagues.

Only then does the new way of behaving land: start every innovation and vendor decision by asking who gets the bonus check; map one patient journey and quantify value for that specific risk-bearer; design price around the value created, not a code; structure pilots as contracts with a future, with clear metrics, named decision-makers, and a pre-agreed price band that kicks in if outcomes are met; and compress the whole story into three sentences a CFO can repeat without you.

That is the behavior change your product and your company need your customers to make, and it is where you can position yourself: not as another point solution, but as the partner that helps them rewire how they evaluate, price, and scale anything that claims to reduce utilization or improve outcomes.

What does that look like in practice for a founder or investor? Your next big commercial asset is not another deck rewrite. It is one specific, teachable money story for one specific use case, built from the risk-bearer out. A story your team can use to challenge how buyers currently think, and that your internal mobilizers can carry into rooms you will never sit in.

A concrete starting point: pick one high-stakes episode or population your product touches; answer, in writing, “if we’re right, who gets the bonus check?”; map that patient journey and sketch a rough value equation from their perspective; then compress it into a three-sentence money story a CFO could repeat on a Zoom call without you.

Once you have that, you are no longer hoping your price slide survives scrutiny. You are doing what the best challengers do: teaching buyers to think differently about their own business, in a way that happens to make you the obvious partner to solve it with.

Going deeper

On a rainy Thursday in Chicago, a hospital CFO stared at the last slide of a young company’s deck. The founders had just finished a polished presentation on their AI-enabled care-coordination platform. They had graphs showing reduced readmissions, enthusiastic quotes from nurses, and a roadmap rich with features. The final slide was the one they had argued over for weeks: a per-patient-per-month price, benchmarked against industry peers, expressed to the cent.

“Look, I like what you’re doing. The clinicians clearly love it. But my team can’t see how this changes our economics under the contracts we’re actually on. Right now, it just looks like another line item in an already tight budget.”

The room deflated. The team promised to follow up with more detail. They left with compliments, another unpaid pilot, and no clear path to revenue.

The problem is not a lack of intelligence. It is a lack of frames: shared reference points for how money, risk, and decisions actually work in modern healthcare. Without those, even brilliant products end up telling fragile, confusing money stories. What follows is a route that has changed the trajectory of health-tech companies, from the startup hoping someone will pay to the company that can explain its economics in three minutes to a CFO or investor who actually nods.

Start where the money actually moves

Most founders start with a simple answer to “who pays?” The payer. We’ll get a code and get reimbursed. It is understandable. It is also dangerously incomplete.

Behind every claim and remittance advice in the U.S. system is a simpler, more brutal logic: somebody is on the hook if patients consume more care than expected. That somebody is not always the entity mailing the insurance card. Draw a crude funds-flow map for the major coverage types (Medicare, Medicare Advantage, Medicaid managed care, fully insured commercial plans, self-insured employers) and two very different roles appear: administrators who process claims, manage networks and take an administrative fee, and risk-bearers who ultimately lose money if utilization runs hot, including federal and state governments, insurers taking full risk, and, critically, self-insured employers and provider organizations under risk-based contracts.

Two facts consistently surprise founders when they first see this drawn out. A majority of large U.S. employers self-insure: they hire insurers to run the machinery, but it is the employer’s money at risk. And a growing share of provider revenue sits under contracts where hospitals and physician groups share in savings, or losses, based on the total cost of care rather than just volume.

If your product reduces readmissions, prevents complications, or shortens post-acute stays, the financial winners are often the health system bearing risk under a bundle or shared-savings contract, or the self-insured employer paying the claims. The administrator remains crucial, but increasingly acts as the plumbing, not the party at risk. Until you see this clearly, it is easy to tell the wrong customer story, point your commercial team in the wrong direction, and build a price model that makes sense only in a world that no longer exists.

Codes are barcodes, not business models

Once we understand who holds risk, we can zoom into the unit of reality where founders often get lost: the claim. A typical hospital claim form, like the UB-04, has four core ingredients: patient demographics, diagnosis codes (ICD-10 and modifiers), procedure and supply codes (CPT, HCPCS, NDC) with billed charges, and coverage information.

Founders tend to zero in on the codes. How do we get a new CPT? Which HCPCS level will this be? Can we get pass-through payment? Codes matter. Without them, providers cannot describe what they did, and payers cannot process the claim. But a code is essentially a barcode. It standardizes language. It does not decide price. It does not guarantee coverage. It certainly does not create an obligation to pay.

Payment is determined by the contract between payer and provider (fee-for-service, DRG, bundle, shared savings, capitation), the rules that tie codes and diagnoses to what is medically necessary, and the risk structure: who ultimately absorbs the cost if utilization rises.

You can have a code and still get paid nothing for it. You can have no dedicated code and still generate enormous economic value inside a bundle or for a self-insured employer. When a strategy slide begins and ends with “we’ll get a code,” what it really says is that the team has not yet thought at the level the system actually works.

If funds-flow is the landscape and claims are the terrain, the next frame is the compass: if we are right about our outcomes, who gets the bonus check? In joint replacement bundles, it is the hospital system, not Medicare, that receives the reconciliation payment if the total episode cost falls below the target. If your technology prevents infection-related readmissions or trims skilled-nursing days, the hospital’s bonus check grows. In a self-insured employer arrangement, if your solution reduces emergency-department visits or duplicative imaging, the employer’s claims bill shrinks. The insurer’s administrative fees change very little.

Once you can answer that question in one clean sentence for a specific use case, the fog starts to lift. Your economic customer is no longer a vague payer or hospital; it is “integrated delivery systems bearing risk for cardiac bundles,” or “self-insured employers with large musculoskeletal spend.” Your roadmap starts to prioritize what matters to that risk-bearer. Your metrics shift from generic engagement toward events they care about: avoided readmissions, shorter post-acute stays, fewer low-value procedures.

Once we know who benefits financially, we can ask a more grounded question: along a specific patient journey, where do we actually move the economics? That means trading the macro total-addressable-market slide for a written narrative of one episode or population. How does a patient enter the system? What is the index event? What happens in the 30 to 90 day window afterward? For a population: who is in the cohort, and over a year, what drives cost? Then: where does our solution touch this journey, what unnecessary steps do we reduce, and what events do we help avoid?

From there, the goal is not a perfectly precise financial model. It is a directional value equation a CFO can follow without a magnifying glass. Done well, this changes the tenor of pricing conversations. You are no longer asking what they will pay for your software. You are asking:

Given that we help you avoid something you already agree is wasteful, what share of those savings is fair for us to capture?

The invisible cast around your price

At this point many teams make a subtle mistake. They have a clear economic beneficiary and a compelling value equation, and they assume the path to a contract is now straightforward. Then they discover that the person who loves the product cannot sign the check. In most health systems and larger employers, price lives inside a small drama with recurring characters.

  • Champions, often clinical leaders, who feel the problem every day and want it solved.
  • Gatekeepers (value analysis committees, IT, compliance) who worry about risk, integration, and alignment with institutional goals.
  • Economic buyers (CFOs, service-line leaders, benefit managers) who see budgets, contracts, and trade-offs across the portfolio.
  • Payers or third-party administrator partners, who control claims rules and, in some cases, savings-sharing structures.

If your pitch is a single monologue delivered to all of them, it will resonate with none of them. The value equation that moves a champion is about workflow relief, fewer fires, better patient experience. The one that moves a CFO is about avoided cost or improved margin under specific contracts. The evidence a gatekeeper needs is about safety, interoperability, and alignment with strategic initiatives.

Mapping this invisible cast shows you where a deal is likely to die if the story does not adapt, and it forces different artifacts for different audiences: a clinical narrative, a risk and compliance brief, and a budget-impact story that stands up in a finance meeting. The price itself does not live on a single slide. It lives in the conversations where each of these actors decides whether your solution deserves a share of scarce attention and money.

From ambition to a single, solvable hill

By now the problem can feel bigger, not smaller. You see funds-flow, risk-bearers, value equations, and a crowd of stakeholders. This is the moment when large ambitions become most seductive, and most dangerous. “Triple U.S. revenue in eighteen months.” “Become the leading platform in our category.” There is nothing wrong with big goals. The trouble comes when they masquerade as strategy.

A useful discipline at this stage is to translate the mountain into a single hill that is specific, solvable, and time-bound. For example:

Within 90 days, we will have one regional health system sign a pilot contract that a CFO describes as “fair” and that automatically converts to a paid rollout if pre-agreed metrics are met.

That one sentence does more for focus than any five-year plan. It constrains you to a specific customer type, a specific moment (the CFO’s judgment that the price feels fair), and a specific mechanism (an auto-conversion clause linked to metrics). When teams make this move, their calendars change. Sales and product discussions begin to orbit around the hill. Which system? Which service line? Which metrics? Which internal champion? Which finance leader? Constraint, in this sense, is not a limitation. It is a lens that brings a path into focus.

Treat price as a portfolio of bets

With a clear hill, there is a strong temptation to retreat into a conference room, debate price structures, find industry benchmarks, and emerge with the number. That is the wrong game. A price is not a verdict. It is a bundle of beliefs about who really decides and who merely influences, which unit feels intuitive to the buyer, how much evidence different stakeholders need, and whether a competitor’s position is a useful anchor or a trap.

Left implicit, these beliefs remain invisible and dangerously optimistic. A more robust approach is to make them explicit. Literally list them: “radiology chiefs will think per-study pricing is natural.” “Value analysis committees will sign off based on a 10-bed pilot.” “Community hospitals will pay roughly what academic centers pay.” “CFOs will prefer variable fees to fixed site-level commitments.” “A three-month pilot is enough for payers to recognize our impact.”

Then ask which three of these, if wrong, would hurt most. You have just created an assumption inventory. Price stops being an argument and becomes a series of testable bets.

Now constraints can do their work again. Design experiments that respect two hard limits: no more than two weeks, and no more than a modest, pre-set spend. Those constraints rule out grand studies and elaborate surveys. They force uncomfortable but high-leverage actions: short conversations with CFOs and benefit leaders about which price structures feel manageable; price cards that put three alternative models in front of clinical and economic buyers and ask which feels most natural, and why; quick discussions with payer medical directors about what kind of real-world evidence would move coverage decisions.

None of these will provide perfect information. They will make you meaningfully less wrong, and they will often challenge your most cherished assumptions about what buyers obviously want.

Design pilots as contracts with a future

Many health-tech stories stall at the same point: the pilot. The pattern is familiar. An enthusiastic clinical sponsor. A limited, low-risk implementation. Vague goals about evaluating impact. A promise to talk about price once the results are in.

This is not a pilot. It is a favor. If you have done the work to understand who gets the bonus check, how you move their economics, and who decides, you can design something else, a pilot as a contract with a future. On paper, that looks like a time-bound window, six months for example, with scheduled check-ins; a small agreed set of clinical and economic metrics that matter to your risk-bearer; a pre-negotiated price band and structure for rollout, contingent on hitting those metrics; and a written list of who must say yes at the end, titles rather than departments.

This design moves the pricing conversation from the foggy, emotional “is this a lot?” to the more grounded “given what we’ve seen together, where in this pre-agreed range should we land?” It also changes incentives. A pilot with no defined future encourages everyone to under-invest. A pilot that encodes a path to scale forces both sides to clarify what good enough to roll out means before everyone is exhausted and attention has moved on.

When these pilots convert, it rarely feels like a dramatic close. More often, the CFO says something like, “given the results and the risk we see, this seems reasonable.” That phrase is the quiet victory of a good pricing system.

The three-minute money story

Follow this route (mapping funds-flow and risk, identifying who gets the bonus check, building a value equation, mapping decision-makers, naming a hill, treating price as a set of bets, and designing pilots with a future) and you earn something rare: a money story that can be told, start to finish, in about three minutes. In its tightest form it has three beats.

  1. Who your economic buyer is.
    “Our customer is regional health systems that bear risk for joint-replacement bundles in Medicare and key commercial lines.”
  2. How they are paid.
    “They’re paid prospectively via DRGs, with a 90-day episode reconciliation. If total episode cost comes in below target, they receive a bonus; if it comes in above, they’re penalized.”
  3. How you move their economics and how you price.
    “Our technology reduces infection-related readmissions by about 25%. In the systems we’ve modeled, that improves episode performance by roughly $1,200 per case. We price at around a quarter of that value, on a per-site basis, with an optional outcome-based kicker once those savings are documented.”

An investor listening to this is not asking whether every number is precise. They are asking whether it clears their rough return bar, whether the logic of how you get paid makes sense, and whether the team understands how contracts, risk, and behavior intersect. A provider or employer leader is asking something simpler: do I recognize my world in this explanation? Your detailed financial model still matters, but its role is different now. It is not a crystal ball. It is an X-ray of how clearly you think.

Even the best three-minute money story has a shelf life. Payment models evolve. Employers experiment with new benefit designs. Health systems take on more risk, or less. The companies that thrive are not the ones that got the price right once. They are the ones that keep learning it: following the risk every quarter or two, revisiting one or two patient journeys, retelling the story, naming the next 60 to 90 day hill, and refreshing the list of beliefs that underpin the price.

Do that, and you change what happens in rooms like that one in Chicago. You stop being the team with the impressive deck and the fragile spreadsheet. You become the team that walks in, explains in plain language how the hospital or employer wins, and then spends the rest of the meeting on the only things that matter more than money: the quality of the science, the strength of the team, and the future of care you are building together.

A thirty-day start
  • List your pricing assumptions.
  • Pick the three that would hurt most if wrong.
  • Run one two-week experiment against each.
  • Debrief as a team on what held up, what cracked, and what changes.
Two · the investor read

Stop Chasing Codes

Three questions investors wish you would answer instead.

Health-tech doesn’t fail for lack of codes. It fails for fuzzy buyers. Follow the risk, then the money, then tell that story.

Smart brief

Many early-stage health-tech ventures fail not for lack of clinical promise, but because they misidentify their true economic customer. Founders typically anchor their revenue strategy on getting a code and saving payers money, assuming insurers are the primary financial winners. By mapping U.S. healthcare funds flow across two dimensions (administrators and risk-bearing entities), we show that providers and self-insured employers increasingly capture the gains from reduced utilization under DRGs, bundles, shared-savings contracts, and employer ASO arrangements. The central strategic question reframes as, “if we are right about our outcomes, who gets the bonus check?” Three disciplines follow:

  1. start from specific episodes or populations and follow utilization risk before following money;
  2. price to the value created for the risk-bearing entity rather than to the reimbursement level of a billing code;
  3. craft a three-sentence money story that any CFO can understand in under three minutes.
Clarity on the real risk-bearing customer converts U.S. healthcare’s complexity from a hazard into a durable competitive advantage.

The story you have been told

You and your team have probably been told the same story about getting paid in U.S. healthcare: get a code, convince payers you save them money, the rest will follow. That story made sense 15 years ago. It is also the fastest way for a great product to die slowly.

When you look at how money actually moves in the U.S. system today, you do not see a simple line from payer to provider. You see a web. On one side are the state and federal governments, insurers, and employers. In the middle, programs like Medicaid, Medicare, Medicare Advantage, exchanges, fully insured plans, and self-insured employer schemes. On the other side, patients and employees who consume care. Here is the uncomfortable surprise:

In many of the episodes and populations you care about, the entity that pays the claim is not the one that profits when utilization drops.

Under DRGs and bundles, hospitals earn more when they cut complications and readmissions. Under shared-savings models and ACOs, provider groups share in the upside if they deliver care at a lower cost than a benchmark. Under self-insured arrangements, employers, not insurers, burn cash when your target cohort hits the ER or the ICU more than expected.

So when a founder tells an investor “we’ll get a code and save payers money,” that investor hears something very specific: this team does not yet understand who their real economic customer is.

The cost of that misunderstanding gets real quickly. It shows up in pitches that spend 10 minutes defending a TAM slide instead of 20 minutes building conviction about the team. It shows up in pilots sold to the wrong buyer, a payer with no real financial upside, that quietly stall after 12 months. It shows up when pricing is anchored to the wrong unit of value, leaving millions on the table or making you look irrationally expensive. The result is a book of business full of almosts: almost funded, almost reimbursed, almost scaled.

You do not need more features or fancier models to fix that. You need a different starting question. Not “how do we get reimbursed?” but: if we are right about our outcomes, who gets the bonus check? When you can answer that precisely (this category of hospital under this bundle, or self-insured employers with this risk profile, or this ACO taking downside risk for this population), three things snap into focus. Your economic buyer becomes obvious. Your pricing logic becomes a value-share rather than a guess at reimbursement. Your money story compresses to three sentences any CFO can follow.

Going deeper

On a gray Boston morning, a gene-therapy founder walked into a pitch she had been preparing for months. Her slides were immaculate. The science was breathtaking. By the time she arrived at the financials, she felt confident enough to exhale. Then an investor leaned forward, squinted at her “Market Opportunity” slide, and asked a deceptively simple question:

“Help me understand this: you’re calling this a curative therapy, but your model shows the number of eligible U.S. patients increasing every year. How does that work?”

The founder launched into a careful, technically correct explanation: diagnosis rates would rise as awareness grew, there would be a lag between cure introduction and full uptake, genetic testing would uncover previously undiagnosed cases. Her answer made conceptual sense. It also consumed four minutes of a 30-minute meeting. By the time she recovered and moved on to her strategy and team, the room’s energy had shifted. The investors were now evaluating her spreadsheet, not her company.

Nothing on that slide was wrong. But it was doing real damage. We are over-investing in financial fireworks and under-investing in the one thing that actually changes the game: a simple, credible answer to “who really benefits economically if this works, and why will they pay?” In the U.S. healthcare system, that is much harder than it sounds.

Investors don’t fund spreadsheets

Founders often assume that market-size slides and revenue projections win or lose the deal. But listen closely to experienced investors and a different pattern emerges. They typically use your financial model for three things.

  1. A rough return check. They have a threshold in their head, sometimes a billion-dollar outcome, sometimes less. Their first question is binary: could this plausibly clear my bar? Not: is this forecast precise?
  2. Efficient diligence. A well-structured model is a fast way to test the operational logic of your business. At a glance, they can see whether your adoption curve, pricing, and cost structure hang together.
  3. A proxy for your thinking. Investors know most health-tech founders come from scientific backgrounds. Your model is an X-ray of how deeply you have thought about the business, not just the biology.

This explains why the gene-therapy slide caused so much trouble. The issue was not the precise patient numbers. It was the logic: a curative therapy with a growing pool of eligible patients, presented without context, read as sloppy thinking.

The lesson is counter-intuitive but liberating. You rarely win the deal on the financial slide. You can absolutely lose it there. Your job is to chin the bar: show that the opportunity is big enough, that the logic holds together, and that you understand how you get paid. Then get off the slide and spend your scarce attention on what does win deals, the quality of your science, your team, and your strategic position.

Ask a typical founder who pays for healthcare in the United States and you will hear some version of: payers, we’ll get a code, we’ll get reimbursed, and everyone will save money. It is understandable. It is also dangerously incomplete. Consider a simplified funds flow diagram: on one axis the major administrators (Medicaid, Medicare, Medicare Advantage, the ACA exchanges, fully insured commercial plans, self-insured employer arrangements), on another the entities that truly hold the risk that patients will consume more care than expected (state governments, the federal government, insurance companies, and employers).

Two facts on that diagram tend to surprise founders. The majority of large U.S. employers are self-insured: they hire insurers to administer claims, but the employer’s money is at risk. And a growing share of provider revenue sits in contracts where hospitals and physician groups share in savings, or losses, based on the total cost of care rather than the volume of services delivered.

In other words, the entities that benefit financially when utilization falls are often not the ones sending remittance advices. Payers still play a crucial role, but increasingly they are the pipes, not the primary risk-bearers. That distinction is not academic. It should reshape how the business is designed.

If funds flow is the macro-map, the healthcare claim is the micro-unit of reality, and founders are often obsessed with one tiny element of it: the code. Codes matter. Without them, providers cannot describe what they did, and payers cannot process the claim. But a code is essentially a barcode. It standardizes language. It does not set price. It does not guarantee coverage. It certainly does not create an obligation to pay. You can have a code and still get paid nothing for it, or have no dedicated code and still create massive value under a bundle or employer arrangement.

How Medicare quietly flipped the game

When Medicare launched in 1965, the logic was simple: hospitals listed every service and supply they billed, and Medicare paid those charges plus 2%. Costs exploded.

In the early 1980s, Medicare introduced Diagnosis-Related Groups for inpatient stays. Each admission is assigned to one of roughly 740 DRGs, each with a relative weight. Payment is based on a base rate for the hospital adjusted for local wages and other factors, the DRG weight, and adjustments for disproportionate share of low-income patients, teaching status, and extreme outliers.

Crucially, the individual line items on the claim do not determine payment. They justify the assigned DRG. Two hospitals caring for similar patients under the same DRG receive similar payments, even if one uses twice as many supplies. That change created an incentive for hospitals to control their cost of delivering a DRG rather than to maximize line-item revenue.

In the 2000s, Medicare went further. It piloted shared-savings models (the Physician Group Practice demonstration, later the Medicare Shared Savings Program) that benchmarked cost for a population and rewarded providers for beating that benchmark, and episode-based payment models (the Acute Care Episode demonstration, precursor to Bundled Payments for Care Improvement) that defined an episode around a hospitalization and a 30 to 90 day post-acute window, then reconciled total spending against a target.

Graphically, the evolution looks like a rope being dragged, knot by knot, from payer-held utilization risk toward provider-held utilization risk over time. Commercial payers, especially in advanced markets like Massachusetts, have adopted their own versions. Employers, frustrated with rising costs, have embraced self-insurance and direct contracts. The implications are profound: reducing readmissions may not save Medicare a dollar if the savings are contractually shared back with providers as bonuses; helping a hospital shorten length of stay can increase its DRG margin even if the payer’s per-case outlay does not change; steering employees to higher-value providers can save a self-insured employer millions even if the insurer’s administrative fees stay constant.

The economic beneficiary of your innovation is not a philosophical question. It is a function of contract design.

Your first strategic task is to find them.

Who gets the bonus check?

Strip away the complexity and the biggest solvable challenge for most health-tech ventures in the next 18 to 36 months is surprisingly clear: identify, with precision, who truly benefits financially from your impact, and build your revenue story around that entity.

In Medicare joint-replacement bundles, the hospital system receives a reconciliation payment if the total cost of the episode, surgery plus 90-day post-acute care, comes in below the target. If your product reduces infection-related readmissions or cuts skilled-nursing days, the hospital, not the payer, gets that check. In a self-insured employer arrangement, if your solution lowers emergency-department visits or specialist referrals, the employer’s claims spend falls. The insurer’s role as administrator does not change much.

Discipline 1: follow the risk before you follow the money

Start with a specific episode or population, not with an abstract disease category. For an episode: map the patient journey (primary care, then specialist, then the index event, then the 30 to 90 day follow-up window); identify high-cost events you can influence (readmissions, complications, ED revisits, post-acute facility days); determine what payment models apply (DRGs only, DRGs plus bundles, shared-savings agreements).

For a population: define the cohort (diabetics in a Medicare ACO, sepsis survivors, NICU graduates under Medicaid managed care); understand who holds downside risk for the total cost of care (ACO entity, integrated delivery system, managed-care plan, or employer); quantify the cost drivers you can realistically move.

At the end of this exercise, you should have a simple statement in your materials: our initial focus is this procedure or population, where this provider, employer, or plan holds utilization risk under these contracts. That is not a slide decoration. It is a strategic choice.

Discipline 2: price to the value created, not to the code

Once you have a clear risk-bearer, your pricing logic changes. Instead of asking what the payer will reimburse for a CPT code, ask how much value, in dollars, your solution creates for the entity that holds risk, and what share of that is fair.

For example, a device that reduces surgical site infections in bundled joint replacements might cut readmission rates by two to three percentage points, save the hospital thousands of dollars per case in post-acute and complication costs, and improve its bundle reconciliation performance enough to increase bonus payments meaningfully.

You can then build a simple unit-economics story: average episode cost for complications avoided, expected reduction in event rates given your technology, translation into incremental margin or bonus dollars per case, and your proposed price as a fraction of that value. This logic is legible to CFOs. It is also far more durable than a code-centric story, because it aligns with the direction of travel in payment models.

Discipline 3: tell the three-minute money story

With a clear risk-bearer and value logic, the final task is narrative. In a 30-minute pitch, you should be able to explain who your economic buyer is (“our customer is the health system that bears risk for joint-replacement bundles in Medicare and commercial lines”), what contract structure they operate under (“they are paid prospectively via DRGs, with retrospective reconciliation under a 90-day episode model”), and how you move their economics (“our technology reduces infection-related readmissions by 25%, which improves episode performance and generates approximately this much additional margin per case, and we price at roughly this share of that value”).

That is the entire financial story in three sentences. The details, exact ICD-10 codes, outlier thresholds, risk-adjustment formulas, belong in a backup deck and the data room. They do not belong in the main narrative unless an investor explicitly wants to go there.

Remember the opening gene-therapy example. The problem was not the complexity of the underlying epidemiology. It was forcing investors to process that complexity in real time to make sense of a single slide. A simple, coherent revenue story signals mastery. An intricate, fragile one, however clever, signals risk.

Founders are not the only ones who need a better map. Investors can improve their own hit rate by probing for risk-bearer clarity early: who actually holds utilization risk in your primary use case? If you are right about your outcomes, who gets the bonus check, and how much is it? Walk me through one real episode or population: where do you enter, and where does the money show up? Teams who answer crisply are more likely to have done the work that de-risks go-to-market.

Provider and employer partners can raise the quality of innovation they entertain by flipping the usual conversation. Instead of asking whether there is a code, ask how this changes total cost or episode performance under current contracts, whether the vendor understands how the service line is paid, and what metrics would prove to us, not to the payer, that the solution is working.

Choosing the right mountain

Strategy, at its core, is the art of choosing which mountain to climb next. In a world of shifting payment models and crowded innovation, the mountain that matters most for early-stage health-tech is not a billion-dollar TAM or a new code. It is something more grounded and more demanding. Do we know, with confidence, who really benefits financially from our success? Are we designing our product, pricing, and narrative for that entity? Can we explain the answer in under three minutes, in a way a CFO would nod along to?

Many things are outside our control: macro interest rates, regulatory delays, the appetite of large strategics. This is not. Follow the risk, then follow the money, then tell that story simply, and the labyrinth of U.S. healthcare becomes an advantage rather than a hazard.

You stop being the founder explaining a fragile spreadsheet and start being the founder who walks into the room, draws a quick line from patient to bonus check, and spends the next 25 minutes talking about the only things that matter more than money: the science, the team, and the future you are building.