Budget impact analysis
What it will cost the health system, an autonomous community or a hospital to adopt your product, year by year. A model that adapts to each payer in minutes, instead of a spreadsheet rebuilt for every committee.
- Patients treated, year 160,354
- Net impact over 3 years+€33.8M
- Net impact, year 1+€5.7M
- Per patient on Product X, year 3+€1,200
Assumptions9
- Source: National epidemiological study, 2024
- Source: Scientific society registry
- Source: Dispensing data, 2025
- Source: Market access team forecast Share year 1: 7.9% · year 2: 15.0%
- Source: Ex-factory price
- Source: Negotiation proposal
- Source: Current treatment mix
- Source: Pivotal trial, secondary analysis
- Source: Trend 2021-2025
Payer's annual spendSpanish National Health System
- Comparators
- Product X, net of avoided costs
The calculation, year by year
| Year 1 | Year 2 | Year 3 | Total | |
|---|---|---|---|---|
| Patients treated | 60,354 | 62,165 | 64,030 | |
| On Product X | 4,780 | 9,300 | 14,087 | |
| Spend, current scenario | €247M | €255M | €263M | €765M |
| Comparators no longer used | -€19.6M | -€38.1M | -€57.8M | -€115M |
| Cost of Product X | +€29.6M | +€57.7M | +€87.3M | +€175M |
| Avoided costs | -€4.3M | -€8.4M | -€12.7M | -€25.3M |
| Spend, with Product X | €253M | €266M | €279M | €799M |
| Net impact | +€5.7M | +€11.2M | +€16.9M | +€33.8M |
From population to patients
- Population47,900,000
- With the disease143,700
- Diagnosed86,220
- Treated60,354
- On Product X, year 14,780
Sensitivity of the 3-year impact
Each assumption, 20% up and down
- Annual cost of Product X-€1.1M / +€68.7M
- Annual cost of comparators+€10.7M / +€56.9M
- Diagnosed+€27.0M / +€40.6M
- Prevalence+€27.0M / +€40.6M
- Treated+€27.0M / +€40.6M
- Product X share in year 3+€27.0M / +€40.6M
- Costs avoided per patient per year+€28.7M / +€38.9M
- Annual patient growth+€33.5M / +€34.1M
- No exports yet
Population, market shares, price and discount, each assumption with its source. Switch payer or move an assumption and see the result and its sensitivity.Example with fictional data.
The problem
Every payer asks the same question with its own numbers: population, expected uptake, the price of the alternatives and associated costs. The model usually lives in a huge spreadsheet that only its author understands, and adapting it for one hospital takes days.
And when an assumption changes, such as a comparator's price or a generic entering, it has to be rebuilt, and what was presented in each place stops adding up.
What's left running
- The model with a clear structure: population, market shares, costs and time horizon, each assumption with its source.
- A version for each payer: Spanish National Health System, autonomous community or hospital, with their own population and consumption data.
- Sensitivity analysis: which assumptions move the result most.
- Scenarios for negotiation: with and without a discount, with and without competitors entering.
- A tool the access team uses without depending on whoever built the model.
What it moves
The days it takes to adapt the model to each payer, and consistency between what's presented to each region and each hospital. We set the number that matters with you, in writing, before we start.
Tell us how you do it today. Before we start you have in writing what we'd do, which number it will move and what it costs.
Contact meFrequently asked questions
Does it replace a full economic evaluation?
No. Budget impact is one piece. If you also need a cost-effectiveness analysis, we look at it in the diagnostic.
Where does the data come from?
From your dossier, public population and consumption sources, and the assumptions your team sets. Each one is written down with its source.
Who validates the assumptions?
Your medical and access teams. The model makes them visible and open to discussion; it doesn't decide them.