Structuring an e-health project: 6 pillars to avoid failure

70% of e-health projects fail before going to market

Between 60% and 80% of digital projects fail. In e-health, the figure is even worse: 70%.

After evaluating more than 30 projects for France 2030 and Bpifrance, the conclusion is implacable: only 3 out of 10 make it through to operational deployment.

But why? It’s never the technology. It’s always the organization.

The three pitfalls that kill projects

A start-up develops a promising algorithm over 18 months.

3 months to launch: discovery that medical device classification requires a further 24 months’ clinical study. Budget exhausted. Project abandoned.

A brilliant technical solution is designed without consulting end-users.

The result? Virtually zero adoption. Caregivers find the interface unsuited to their daily workflow.

A telemedicine tool is built without cybersecurity analysis.

First HDS audit: 47 critical non-conformities. Complete overhaul necessary.

What do they have in common? The absence of a structured methodology that simultaneously integrates technical, regulatory, human and business aspects.

Where the JuliaShift method comes from

My approach combines three rarely connected universes:

17 years with the French Army Health Service: structuring projects in constrained environments where error is not an option. In an overseas operation, when your telemedicine system has to operate at 45°C with an unstable satellite connection, you develop an obsession with resilience.

Scale-up HealthTech: expansion director, I deployed e-health solutions in 12 European countries. I’ ve experienced the pitfalls: multi-country compliance, cultural adaptation, organizational complexity.

France 2030 expert: as an evaluator for Bpifrance, I have developed a precise reading grid of success/failure factors. Unique observatory position on what really works.

Hybridization: military rigor (risk management) + Lean Startup (rapid field validation) + generative AI (prototyping acceleration). This alignment reconciles agility and compliance, speed and security.

The 6 pillars of structuring

Pillar 1: Regulatory expertise from Day 1

The pitfall: Develop for 18 months, then discover the regulatory constraints.

The approach: Regulatory integration from D1, with adaptive roadmap.

Why? The healthcare sector is the most regulated in the world. MDR/IVDR, RGPDHDS, NIS2 cybersecurity… Each regulation impacts technical architecture and timeline.

What we do differently:

• Regulatory classification diagnosis week 1
• Compliance roadmap synchronized with product roadmap (no document big bang on D-30)
• Anticipation of clinical studies from the design phase

Pillar 2: Strategic health go-to-market

The trap: “Our product is great, it will sell itself.”

The approach: market validation before line of code, sales strategy adapted to healthcare sales cycles (18-36 months).

Why is this so? The healthcare market is not a classic B2B market. Multiple decision-makers (management, CIOs, doctors, IMGs) with conflicting objectives. Rigid budgets. Standardized purchasing processes.

Customer case: Startup bed management tool. Targeted CIOs (buyers). But real prescribers = healthcare executives (users). Pivot: 0 → 12 CHU customers in 18 months.

Pillar 3: Data security and compliance

The catch: “We’ll deal with cybersecurity later.”

The approach: Security by design, native RGPD compliance, HDS anticipation.

Key figure: +55% cyber attacks on French healthcare establishments by 2024.

A single data leak = lethal for a startup. CNIL sanctions up to 4% of worldwide sales. Loss of trust. Impossible HDS certification.

Our framework :

• EBIOS RM health risk analysis
• Secure architecture from MVP (HDS J1 hosting, AES-256 encryption, strong authentication)
• Operational RGPD compliance (treatment register, PIA, DPO)
• Tested incident response plan

Gain: No post-launch migration. Integrated security = savings of €150-300K.

Pillar 4: Open technical interoperability

The catch: “We’ll make the connectors if the customers ask for them.”

The approach: Interoperability right from the MVP stage, open standards (FHIR), prioritized connector strategy.

The reality: Healthcare establishments use 50-150 different software packages. Your solution needs to integrate, not work in silos.

Example of failure: brilliant AI tool for clinical decision support. But forced doctors to manually re-enter 15 fields already in the DPI. 4 minutes/patient × 30 consultations = 2 hours lost/day. Adoption < 5%. Project abandoned.

Pillar 5: User-centered business design

The trap: “We’ve made a beautiful interface, users will adapt.”

The approach: Co-design with end-users, business UX adapted to field constraints.

Health UX specificities: frequent interruptions (every 4 min), high cognitive stress, heterogeneous digital skills, safety imperative (UX error = serious clinical consequence).

Methodology :

• Field observations (immersion services)
• Iterative co-design (wireframes tested with 8+ real users before coding)
• Permanent User Committee
• Non-negotiable UX principles (efficiency, safety, adaptability)

Success indicator: SUS > 75/100, adoption > 70% at 3 months post-deployment.

Pillar 6: AI and ethical data science

The catch: “We train our algorithm on open source data, that’s enough.”

The approach: responsible AI, clinical explicability, rigorous validation, ethical governance.

Why is this? Healthcare AI is not consumer AI. A diagnostic algorithm that gets it wrong = potentially fatal medical error, medico-legal liability, impact on trust in the healthcare system.

Real case: Readmission prediction algorithm developed on data from Paris University Hospital. Excellent test performance (AUC 0.89). Rural UHC deployment: poor performance (AUC 0.62). Population bias not detected. Delay 8 months.

Framework IA responsible :

• Multidisciplinary ethics committee (doctors, data scientists, lawyers, patients, ethicist)
• Formalized IA ethics charter
• Data representativeness analysis (bias prevention)
• Explicability implemented (SHAP, LIME)
• Mandatory prospective clinical study
• Ongoing post-deployment monitoring

Case study: from 0 to 3 UHC customers in 18 months

Startup: Remote monitoring solution for heart failure patients

Initial stage: Pre-seed, technical prototype, 0 customers

Objective: CE marking + 3 pilot university hospitals in 18 months

Month 1-2: Audit reveals

• Unclear regulatory classification
• No user validation
• Non-HDS cloud architecture
• Algorithm trained on non-representative US dataset

Structuring results :

• Classification IIa confirmed, prospective clinical study planned
• Pivot identified: targets = coordinating nurses (not doctors)
• HDS host migration, full RGPD compliance
• Easily DPI connector (70% French university hospitals)
• Co-design with 8 nurses: SUS 58 → 82/100
• Re-training algorithm French cohort 2400 patients

At 18 months :

• CE marking obtained (on time)
• 3 pilot hospitals signed up (240 patients remotely monitored)
• Clinical study: -34% rehospitalization vs. control
• Seed round €1.2M (vs. €600K expected)
• Publication European Journal of Heart Failure

Key success factor: User pivot identified Month 2. Without structuring, discovery Month 12+ = critical loss of time/money.

5 fatal mistakes to avoid

Error 1: False technological priority

“We’re developing our revolutionary AI for 18 months, then we’ll look at the regulations.”

→ Regulatory compliance IS the limiting factor.

Error 2: “We know better than the users” syndrome

“Our team understands the problem, no need for interviews.”

→ 80% of founding hypotheses are invalidated by the field.

Error 3: Cosmetic safety

“We’ll put in HTTPS and a password for the MVP.”

→ A security flaw instantly destroys trust.

Error 4: The digital island

“We’ll make the connectors if the customers ask for them.”

→ A solution that doesn’t fit in will never be adopted.

Error 5: Black-box AI

“Our algorithm works very well, no need to explain how.”

→ Clinicians will never adopt an AI they don’t understand.

Evaluate your project: JuliaShift matrix

Where do you stand on each of the 6 pillars (scale 0-5)?

Interpretation :

• 0-10/30: High-risk project → Recasting necessary
• 11-18/30: Fragile foundations → Structuring 2-3 critical pillars
• 19-24/30: Good trajectory → Strengthening before scaling
• 25-30/30: Excellence → Maintain continuous improvement

Why this methodology works

Data on 30 supported projects (2023-2025) :

• Success rate: 73% market reach (vs. 30% industry average)
• Time-to-market: 35% reduction (regulatory anticipation, no late recasting)
• Fundraising: Average amounts +40% (structured projects = investor confidence)
• User adoption: +45% (systematic co-design)
• ROI on structuring: 12x on average (investment €85K → premium of €1M)

Successful projects are not the most technically brilliant. They are the most methodologically rigorous.

Your next steps

1. Diagnose your situation: 6-pillar assessment matrix + identification of 3 priority risks + recommended 90-day roadmap.
2. Talk to us: Express project maturity analysis, identification of bottlenecks, customized recommendations.
3. Structure your project

To find out more

• CNIL – RGPD and health data
• HL7 FHIR – Healthcare interoperability
• Bpifrance – France 2030 digital health

Do you have an e-health project to structure?

Let’s talk about your context. Maturity diagnosis, identification of critical risks, structuring roadmap.

👉 Book free discovery audit 30 min

🎯 Going further

Are you structuring a MedTech fundraiser?

Download our free strategic reports:

• ✓ BPI France 50-point compliance checklist
• ✓ Timeline 0-6 months pre-emergence
• ✓ 3 startup cases (seed → series A)
• ✓ Frameworks valorisation multiples Revenue

📥 Download your free reports → Blueprint MedTech

About the author

Nicolas Schneider is a strategic advisor in digital healthcare transformation and founder of JuliaShift. With 17 years’ experience at the French Army Health Service and 8 years in digital transformation consulting, he assists MedTech startups and healthcare establishments in their financing strategy, structuring pharma partnerships and preparing for fund-raising.

Specialties: healthcare innovation financing, MedTech fund-raising structuring, pharma industrial partnerships, IA regulatory compliance.