Problems › Should We Raise Our Prices? › Healthcare Providers
The question is never "should we raise prices" in general. It is which customers, by how much, and what you expect to lose. This page works through it for healthcare providers specifically — including an unedited excerpt from a real analysis of a healthcare provider.
The question is never "should we raise prices" in general. It is which customers, by how much, and what you expect to lose. For healthcare providers, this shows up in a particular place. The numbers that carry the answer are cost per episode and payer mix, and the complication specific to this industry is that downside risk has been accepted on 38,000 lives without the cost-per-episode data needed to price it. The general version of this problem and the one you are actually in have different first moves.
Price is the fastest lever in any business — it requires no new customers, no hiring and no new product, and it arrives on the next invoice. It is also the one owners are most reluctant to touch, which is why underpricing is far more common than overpricing.
A useful price analysis does not produce one number. It produces a segmentation: which customers are paying below the value they receive, which are already at the ceiling, and where the discount distribution shows price being set by the sales conversation rather than by policy.
The uncomfortable part is that a good price change deliberately loses some customers. If a rise costs you nobody, it was too small.
These three together are the signature. One on its own usually points somewhere else.
✓ Almost every deal closes, and closes quickly
✓ Discounting is common and inconsistently applied
✓ Price has not moved in more than two years while your costs have
The move that usually makes it worse. A uniform percentage rise across the whole book, which overcharges the price-sensitive customers and still undercharges the ones who were never buying on price.
It is for you if you run or finance a healthcare provider and almost every deal closes, and closes quickly. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.
It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
Below is an excerpt from a real run of this analysis on a healthcare provider. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.
The subject is Cedar Ridge Health Partners, a sample company profile used for testing rather than a customer — 38,000 attributed lives under value-based contracts.
Excerpt from a real Percision run · Quick Market Scan · sample company profile
The move. Turn 38,000 downside-risk lives into a self-funding 36-month analytics platform via payer co-development.
The leak it closes. Settlement lag (6–9 months) and payer audit adjustments reduced via internal attribution engine
The assumption it rests on. Payer agrees to 5-year exclusivity and 15–25% platform margin split — the engine put the probability at 0.75.
| Investment required | $2.5–3.0M over 18 months |
| Expected return | 7.6–9.1× over three years on $2.5–3.0M investment |
| Revenue, year 1 | $0 (platform build phase) |
| Revenue, year 2 | $6.9–11.4M (first shared-savings settlement) |
| Revenue, year 3 | $13.7–22.8M (full run-rate) |
| Exit criteria | Terminate if payer refuses exclusivity by Month 6 OR if attribution accuracy <80% by Month 18 OR if shared-savings pool < $60M by end of contract year 2 |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Pricing & Revenue Optimization, one of 29 engagements the platform runs. For healthcare providers it works through cost per episode, payer mix, panel size and contribution per provider, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.
You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.
There is no general answer, and the useful analysis is per segment. What can be said is that the loss you fear is usually concentrated in a group whose economics you would improve by losing them.
New first is safer and slower; existing is where the money is. A defensible sequence is to move new-customer pricing, watch win rate for a quarter, then bring existing customers up at renewal with notice.
Then you are selling against them on something other than price, or you are not — and that is the real question. Competing on price without the cost structure to support it is the most reliable way to lose money at increasing volume.
Materially, yes. Downside risk has been accepted on 38,000 lives without the cost-per-episode data needed to price it — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are cost per episode, payer mix, panel size, and an answer built on industry-general benchmarks will usually point at the wrong one first.
Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on cost per episode and payer mix. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.
Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
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