---
title: Health Economic Evaluation for Medical Devices: A Founder's Primer
description: What health economic evaluation actually is for MedTech startups — cost-effectiveness, budget impact, QALYs, and when to commission a study.
authors: Tibor Zechmeister, Felix Lenhard
category: Funding, Business Models & Reimbursement
primary_keyword: health economic evaluation medical devices
canonical_url: https://zechmeister-solutions.com/en/blog/health-economic-evaluation-medical-devices
source: zechmeister-solutions.com
license: All rights reserved. Content may be cited with attribution and a link to the canonical URL.
---

# Health Economic Evaluation for Medical Devices: A Founder's Primer

*By Tibor Zechmeister (EU MDR Expert, Notified Body Lead Auditor) and Felix Lenhard.*

> **Health economic evaluation (HEE) measures whether a medical device delivers enough health benefit to justify its cost compared with current care. For MedTech startups, it is not a regulatory requirement under MDR — it is a commercial requirement to get paid. The right time to start is earlier than most founders think, and the overlap with MDR clinical evidence is larger than most consultants admit.**

**By Tibor Zechmeister and Felix Lenhard.**

## TL;DR
- Health economic evaluation asks one question: is the extra health benefit worth the extra cost compared with standard care?
- The two workhorse methods for MedTech are cost-effectiveness analysis (CEA, usually with cost per QALY) and budget impact analysis (BIA, which models the payer's total spend shift).
- HEE is not required by MDR — Regulation (EU) 2017/745 is silent on economics — but payers, HTA bodies, and hospital purchasing groups routinely demand it before listing or purchasing.
- A well-designed MDR clinical evaluation under Article 61 and Annex XIV already generates most of the clinical inputs an HEE needs. Running them as separate, parallel projects wastes money.
- For most startups, the right time to commission a formal HEE is after early clinical data exists but before the first major reimbursement push — typically 6 to 12 months before CE mark.
- Bad HEEs are worse than no HEE. Payers read them critically, and a weak model damages credibility for years.

## Why this matters for MedTech founders

Every founder hits the same wall. The device is CE-marked, the clinical data looks good, and the first hospital meeting ends with a version of: "Interesting. What does it cost us, and what do we save?" At that moment, the founder who cannot produce a credible economic answer loses the room.

Health economic evaluation is the language payers and hospital controllers use to decide whether a new device is worth paying for. If your team only speaks clinical and regulatory, you are bringing a knife to a spreadsheet fight. The good news is that HEE is not magic — the core methods are well established, the data you need is largely data you are already collecting for MDR compliance, and most founders can become conversant in the basics over a weekend.

Tibor has watched dozens of startups stall at exactly this point. The pattern is familiar: brilliant clinical story, no economic story, and a payer who politely says "come back when you have data." This post is the primer that unblocks that conversation.

## What MDR actually says about health economics

Nothing directly. Regulation (EU) 2017/745 is a safety and performance regulation, not a reimbursement regulation. There is no article in MDR that requires you to calculate cost-effectiveness, no Annex that defines an acceptable willingness-to-pay threshold, no MDCG guidance on QALYs.

What MDR does require, however, feeds directly into any credible HEE:

- **Clinical evaluation under Article 61** obliges the manufacturer to demonstrate conformity with the relevant General Safety and Performance Requirements based on clinical data. That data — effect sizes, complication rates, durability, usability outcomes — is exactly what an HEE model consumes as inputs.
- **Annex XIV Part A** sets out the clinical evaluation process, including the systematic collection and appraisal of clinical data. A well-run CEP/CER produces the evidence base an HEE relies on.
- **Post-market surveillance under Articles 83 to 86** and post-market clinical follow-up under Annex XIV Part B generate real-world evidence that payers increasingly expect to see woven into economic models, particularly for conditional or coverage-with-evidence arrangements.

The practical consequence: if you design your clinical evaluation plan with one eye on your future HEE, you can satisfy both your notified body and your payer audience from a single evidence programme. If you design them separately, you will duplicate work, collect the wrong endpoints for one audience or the other, and spend twice the money.

## The two methods that matter for startups

There are many flavours of health economic evaluation in the academic literature. For MedTech founders, two matter.

**Cost-effectiveness analysis (CEA).** CEA compares two alternatives — typically the new device versus current standard of care — on both cost and health outcomes. The headline output is the incremental cost-effectiveness ratio (ICER): the extra cost divided by the extra health benefit. When health benefit is measured in quality-adjusted life years (QALYs), CEA becomes cost-utility analysis, and the ICER is expressed as cost per QALY gained.

Payers and HTA bodies across Europe use cost per QALY as a decision input. NICE in England, IQWIG in Germany, HAS in France, and similar bodies each have their own methodological preferences and, implicitly or explicitly, their own willingness-to-pay thresholds. For a MedTech founder, the key point is that CEA tells the payer whether your device delivers "enough health for the money" compared with what they are already paying for.

**Budget impact analysis (BIA).** BIA asks a different question: if this device is adopted at expected uptake, what does the payer's total annual spend look like over the next three to five years? BIA is affordability analysis, not efficiency analysis. A device can be highly cost-effective *per patient* and still fail a BIA because the aggregate spend is too large for the payer to absorb.

Most mature payers look at CEA and BIA together. A startup pitching only one of them is telling half the story.

Other methods — cost-minimisation analysis, cost-consequence analysis, cost-benefit analysis — exist and have their uses, but for an early-stage MedTech the CEA-plus-BIA combination is usually what the payer wants to see.

## A worked example

A startup has developed a Class IIa wound care device that reduces the number of dressing changes for chronic venous leg ulcers from three per week to one per week, with equivalent healing outcomes based on a 60-patient pilot study. The device costs EUR 85 per application. Standard dressings cost EUR 6 each. Community nurse visit cost: EUR 45 per visit.

A rough cost-effectiveness sketch over 12 weeks of treatment:

- **Standard care:** 3 visits per week times 12 weeks = 36 visits. Dressing cost: 36 times EUR 6 = EUR 216. Nurse cost: 36 times EUR 45 = EUR 1,620. Total: EUR 1,836.
- **New device:** 1 visit per week times 12 weeks = 12 visits. Device cost: 12 times EUR 85 = EUR 1,020. Nurse cost: 12 times EUR 45 = EUR 540. Total: EUR 1,560.

Incremental cost: EUR 1,560 minus EUR 1,836 = minus EUR 276 per patient. The device is *cost-saving* at equivalent health outcomes. This is the best possible result for an HEE — you do not even need a QALY discussion because you are dominant on both cost and outcomes.

Now the BIA. If the payer treats 20,000 leg ulcer patients per year and uptake reaches 30% over three years, annual savings scale to roughly 6,000 patients times EUR 276 = EUR 1.66 million. The payer sees a small but real saving, and adoption becomes a rational decision.

The same numbers tell a very different story if the device cost were EUR 150 per application instead of EUR 85. Incremental cost per patient would flip to plus EUR 504. You would then need a QALY improvement large enough to justify that EUR 504 per patient — and you would need a much better pilot study to estimate it. This is why pricing decisions and HEE design must happen together, not sequentially.

## The Subtract to Ship playbook for HEE

You do not need a PhD health economist on day one. You need five moves.

**1. Write a one-page economic hypothesis before clinical evaluation starts.** What costs do you expect to save? What costs do you add? Which clinical endpoints drive those costs? If you cannot sketch this on one page, you do not yet understand your own value proposition well enough to design a study.

**2. Align your clinical evaluation plan with your economic hypothesis.** Under Article 61 and Annex XIV Part A, you are already choosing clinical endpoints. Choose endpoints that also feed your HEE model. Length of stay, complication rates, device durability, time-to-next-intervention — these are clinical *and* economic endpoints.

**3. Collect resource use data from the start.** The single biggest reason early HEEs fail is missing resource use data — nobody recorded how many nurse visits, how many minutes of theatre time, how many follow-ups. Build a simple resource use form into your clinical investigation and your PMCF plan.

**4. Commission a formal HEE only when you have real data.** Paying a health economics consultancy to model vapor is a waste of money. Wait until you have pilot data, then commission a proper model. Budget EUR 25,000 to EUR 80,000 for a credible first HEE, depending on complexity. [Ranges are market observations, not regulated prices.]

**5. Use the HEE as a living document.** As PMS and PMCF data accumulate under Articles 83 to 86 and Annex XIV Part B, update your model. Payers respect manufacturers who come back with improved evidence. They do not respect manufacturers who wave a three-year-old model at every meeting.

## Reality Check

1. Can you state, in one sentence, the economic hypothesis of your device — what cost it saves or what health it adds for what price?
2. Are your clinical evaluation endpoints aligned with the cost drivers in your economic hypothesis, or did you choose them independently?
3. Do your study protocols capture resource use — nurse visits, theatre minutes, follow-up appointments — or only clinical outcomes?
4. Do you know which HEE methodology (CEA, BIA, or both) your first target payer prefers?
5. Have you sketched an ICER using current pilot data, or are you waiting for a consultant to do it for you?
6. Is your device priced based on what payers can absorb, or based on what you hope they will pay?
7. Would you be comfortable showing your draft HEE model to a sceptical hospital controller tomorrow?

## Frequently Asked Questions

**Is HEE required by MDR?**
No. MDR is a safety and performance regulation. Health economic evaluation is a commercial and reimbursement requirement, not a regulatory one. But your MDR clinical evaluation under Article 61 generates most of the inputs an HEE needs.

**When should I commission my first formal HEE?**
Typically 6 to 12 months before CE mark, once you have enough clinical data to populate a model with real numbers instead of assumptions. Earlier than that and you are modelling hope. Later and you miss the first payer conversations.

**What does a first HEE cost?**
Market rates for a credible first CEA plus BIA from a specialist consultancy typically run from EUR 25,000 to EUR 80,000 depending on complexity. Academic collaborations can be cheaper but slower and less payer-ready.

**Do I need QALYs specifically?**
For formal HTA submissions to bodies like NICE or IQWIG, yes. For hospital-level purchasing decisions, often no — cost savings per patient and budget impact are often enough. Know your audience.

**Can I use the same HEE across multiple European markets?**
The core model structure, yes. The inputs — unit costs, standard of care, willingness-to-pay thresholds — must be localised per country. Plan for a core model plus country adaptations rather than a single universal model.

**What is the single biggest mistake startups make with HEE?**
Running it as a separate project from MDR clinical evaluation. Design one evidence programme that serves both audiences. Running two parallel evidence programmes is how startups run out of money.

## Related reading
- [HTA Submissions for Medical Devices](/blog/hta-submissions-medical-devices) — when and how to submit HEE evidence to formal HTA bodies.
- [Health Insurance Reimbursement in Europe](/blog/health-insurance-reimbursement-europe) — the payer landscape your HEE must speak to.
- [Austrian Reimbursement for Medical Devices](/blog/austrian-reimbursement-medical-devices) — how economic evidence lands in the Austrian payer system.
- [German Reimbursement for Medical Devices](/blog/german-reimbursement-medical-devices) — IQWIG and the German evidence expectations.
- [MedTech Business Model Analysis](/blog/medtech-business-model-analysis) — how HEE shapes pricing, positioning, and revenue model.

## Sources
1. Regulation (EU) 2017/745 on medical devices, consolidated text. Articles 61, 83–86, Annex XIV Parts A and B.
2. ISPOR Good Practices Task Force reports on budget impact analysis and cost-effectiveness analysis methodology.
3. EUnetHTA core model documentation for relative effectiveness assessment of medical devices.

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*This post is part of the [Funding, Business Models & Reimbursement](https://zechmeister-solutions.com/en/blog/category/funding-reimbursement) cluster in the [Subtract to Ship: MDR Blog](https://zechmeister-solutions.com/en/blog). For EU MDR certification consulting, see [zechmeister-solutions.com](https://zechmeister-solutions.com).*