Comprehensive guide to DTx reimbursement in France. Learn how digital therapeutics (DTx) navigate CNEDiMTS evaluation, PECAN requirements, and scientific methodology standards for HAS approval.
The Urgency of Securing HAS Approval for Digital Therapeutics (DTx)
In the rapidly evolving world of digital health, securing reimbursement is more than just a milestone—it’s essential for patient access and market success. Many digital therapeutics (DTx) find themselves stalled, not because of a lack of efficacy, but because of critical methodological oversights. Our engagement with HAS through repeated organisational interactions has illuminated a fundamental truth: the methodology of DTx validation determines the outcome more than the technology itself.[1]
Understanding the Three-Layer CNEDiMTS Evaluation Framework for DTx
The evaluation framework employed by Haute Autorité de Santé (HAS) through CNEDiMTS remains consistent across all medical devices. It comprises three hierarchical layers grounded in established scientific principles:
1. Patient Benefit (Primary Anchor) for DTx Assessment
Clinical effect size, relevance of endpoints, and durability of therapeutic effects form the foundational evaluation layer for any DTx submission. This requires developers to demonstrate genuine clinical value through rigorous measurement of outcomes that matter to patients and healthcare systems. For digital therapeutics specifically, patient benefit must be measured through validated clinical endpoints that reflect real-world health outcomes rather than engagement metrics or surrogate measures.
2. Organizational Benefit (Secondary but Critical) in DTx Evaluation
This dimension examines whether the DTx produces measurable improvements in care pathways, reduces resource utilisation, or enhances system efficiency.[2] While sometimes overlooked by DTx developers, organisational benefit is not secondary—it represents a critical assessment of real-world implementation feasibility and health system integration. Healthcare systems are increasingly evaluating DTx not just on clinical efficacy but on how digital therapeutics integrate into existing workflows and whether they reduce overall system costs.
3. Methodological Credibility (Gatekeeper) for DTx Validation
Study design integrity, systematic bias control, and structured data collection approaches form the gatekeeping layer for DTx approval.[1] Failure at this level invalidates even the strongest clinical findings. This is where most DTx applications collapse because methodology determines whether DTx results can be trusted and replicated across different healthcare settings.
The Critical Importance of Methodological Soundness in DTx Research
Modern scientific practice increasingly recognizes that methodology is not merely procedural—it is foundational to whether results merit credibility, particularly for digital therapeutics. Peer review processes at leading scientific publishers focus explicitly on “technical soundness, methodological rigor, data quality, and reproducibility” as primary evaluation criteria.[1]
The fundamental principle is straightforward: a well-designed DTx study with modest positive results is more valuable than a poorly designed DTx study with larger apparent effects. For digital therapeutics validation, this means that the rigour of your study design directly impacts whether CNEDiMTS will approve your DTx for reimbursement.
For DTx specifically, methodological concerns extend beyond traditional statistical rigour. The question that regulators pose is whether another researcher, following the same methods, would obtain comparable DTx results.[1] This reproducibility standard is essential because digital interventions vary in implementation, user engagement, and technical functionality. A DTx validated through rigorous methodology in one setting can be more confidently extrapolated to different healthcare systems than one validated through informal observation or post-hoc analysis.
Navigating PECAN: The High-Pressure, Time-Compressed Validation Pathway for DTx
The PECAN pathway is often misunderstood as an “early access” route for digital therapeutics. In reality, it serves as a high-pressure, time-compressed validation mechanism with no margin for methodological error in DTx submissions.[1]
Key Constraints for DTx Under PECAN:
- Approximately 12 months for evidence generation
- Mandatory transition to standard reimbursement pathway
- No formal contradictory phase
- Expectation of pivotal-level thinking from day one[1]
Critical Implication for DTx Developers: You are not designing a pilot; you are creating the initial phase of a reimbursement-grade evidence package for your DTx. This requires substantial upfront planning: allocate months 1-3 for protocol development and HAS consultation, months 4-10 for patient recruitment and follow-up, and months 10-12 for data analysis and reporting.[1]
Single-Arm DTx Studies: Acceptable Evidence Under Strict Conditions
A persistent misconception is that CNEDiMTS requires comparative (controlled) trial designs for PECAN DTx evidence.[3] In reality, single-arm studies are acceptable under precisely defined conditions that ensure methodological integrity for digital therapeutics. The critical requirement is causal interpretability, the observed change must be attributable to the DTx intervention rather than confounding factors, regression to the mean, or natural disease progression.
Minimum Requirements for DTx Single-Arm Studies
Pre-defined protocol before first patient enrolment: Document the hypothesis, primary and secondary endpoints, sample size justification, and analysis plan before enrolment begins.[1] This addresses a widespread problem in DTx research: “p-hacking” or selective reporting of analyses until statistically significant results emerge.[4][5] When endpoints are defined post-hoc, it becomes impossible to determine whether observed DTx effects represent genuine discoveries or statistical artefacts.
Clear inclusion/exclusion criteria: Prevent what researchers term “fishing expeditions” where selective case inclusion in DTx trials creates apparent benefits.[6] Inclusion criteria must be explicit and applied consistently throughout enrollment.
Structured longitudinal data collection: Implement standardized instruments and defined observation windows for DTx assessment.[1] Retrospective or unstructured data collection introduces systematic biases that CNEDiMTS evaluators specifically identify as disqualifying for digital therapeutics.
Clinically meaningful endpoints: Measure DTx outcomes that reflect real clinical value and are operationalized using validated instruments.[1]
Demonstrable before-and-after effect size: Document the magnitude of DTx change with sufficient statistical precision to allow CNEDiMTS evaluators to assess whether effect size justifies further development.
Real-World Evidence for DTx: Powerful Yet Methodologically Demanding
CNEDiMTS explicitly endorses real-world evidence (RWE) as a pathway to demonstrating DTx innovation, particularly given practical challenges of conducting traditional clinical trials in digital health.[2] However, real-world evidence requires equivalent methodological rigor to prospective randomized studies for DTx validation.
The Distinction: Defensible DTx Evidence vs. Data Fishing
The critical difference between defensible real-world DTx evidence and problematic data analysis is clarity of intent established before analysis begins. Developers must pre-specify their analytical approach before querying databases or datasets: define which patient cohorts will be included in your DTx study, what outcomes will be measured, and what statistical tests will be employed.[1]
This requirement prevents selective presentation of DTx findings, a practice recognized as a fundamental threat to research integrity. Research demonstrates that “presenting post hoc findings as if they were a priori hypotheses” is a “questionable research practice” that creates “the impression that research findings are more robust than they actually are.”[4][5]
Data Collection Infrastructure: The Often-Overlooked DTx Foundation
Many digital therapeutics developers focus resources on DTx technology development and user engagement while underinvesting in data collection infrastructure. This allocation error directly undermines reimbursement success because evidence quality for DTx depends fundamentally on data collection systems.
Scientific institutions now emphasize that “every statistical test named and justified” and “software versions specified” must accompany DTx research findings.[1] For digital therapeutics, this translates to several practical imperatives:
First: Data collection protocols must specify exactly how clinical outcomes are measured in your DTx system—through direct patient assessment, validated questionnaires, digital monitoring, or biomarkers. Casual measurement without standardized instruments introduces systematic error that CNEDiMTS evaluators explicitly reject for DTx submissions.
Second: Data must be collected according to predetermined schedules with documented protocols for managing missing data, DTx participant dropout, and protocol deviations.[1] This prevents selective outcome reporting where favorable DTx results are captured thoroughly while less favorable ones are left incomplete.
Third: Data management systems must maintain audit trails demonstrating who accessed DTx data, when, and for what purpose. This transparency standard prevents “fishing expeditions” that research integrity specialists identify as fundamental threats to scientific validity in digital therapeutics research.[4][5]
Extrapolation to the French Healthcare Context: Critical for DTx Approval
A sophisticated challenge international DTx developers face is demonstrating that evidence obtained in other healthcare systems transfers meaningfully to France. This is not merely regulatory box-checking it represents a genuine scientific question about whether observed DTx effects depend on context-specific factors that may not apply in French clinical practice.
CNEDiMTS evaluates extrapolation by examining whether clinical pathways, treatment decision-making processes, and organizational constraints in the DTx study setting resemble those in France.[1] For example, if a DTx was validated in a healthcare system where patients have limited access to specialist mental health services, its benefits in France (where mental health infrastructure differs substantially) may not materialize equivalently.
Why Digital Therapeutics (DTx) Demonstrates Greater Evaluation Complexity Than Remote Monitoring
An important asymmetry emerges when comparing DTx approval rates to remote monitoring technologies.[2] Remote monitoring devices achieve substantially higher approval rates, while therapeutic DTx faces more rigorous scrutiny. This difference reflects genuine differences in required scientific evidence.
Remote monitoring devices require evidence that they capture relevant clinical data accurately and enable clinical decision-making. This is fundamentally an engineering problem.
Digital therapeutics (DTx), by contrast, must demonstrate therapeutic efficacy—that the software intervention itself produces health benefits beyond simple information provision.[1]
This distinction parallels evidence requirements for pharmacological interventions compared to diagnostic devices. Like drugs, DTx must establish not just that something measurable changes, but that the DTx intervention caused the change through a plausible mechanism. This necessitates stronger causal inference and more rigorous control of confounding factors in digital therapeutics research
Citation Accuracy and Evidence Integrity in DTx Submissions
Recent analyses of research integrity reveal that citation accuracy is foundational to scientific credibility.[4][5] A comprehensive analysis found that “only 75 (48.7%) of the 154 citations to peer-reviewed studies were accurate, whereas 48 (31.2%) were partially accurate, and 31 (20.1%) were inaccurate.”
This “strikingly high rate of inaccurate and partially accurate citations” is concerning because “when fewer than half of a document’s citations are accurate, epistemic integrity is seriously weakened and the reliability of the evidence becomes unclear.”[4][5]
For DTx developers: Citations to supporting evidence must be accurate and appropriately contextualized. If developers cite studies supporting their DTx claims, those citations must genuinely reflect what studies actually found. Misrepresenting evidence—even through selective quotation—undermines credibility with evaluators who increasingly conduct independent verification of cited evidence for digital therapeutics.
Pre-Defined Protocols and Analysis Plans for DTx Validation
Scientific institutions increasingly emphasize that the distinction between exploratory DTx research and confirmatory research depends on whether analysis approaches were specified in advance.[1] This distinction is critical for DTx evaluation because it determines whether observed findings represent genuine discovery or statistical artifacts in digital therapeutics.
Elements That Must Be Pre-Defined for DTx Studies
- Primary outcomes (what the DTx study principally measures)
- Secondary outcomes (additional measurements of interest)
- Subgroup analyses (analyses in DTx patient subpopulations)
- Sensitivity analyses (tests of whether DTx results depend on specific methodological choices)
- Statistical significance thresholds[1]
When these elements are prospectively defined and documented, evaluators can distinguish between hypothesis-confirming DTx findings and exploratory discoveries that require validation through independent studies.
Quantifying Organisational Benefit for DTx Reimbursement
Many DTx submissions emphasize clinical efficacy while underestimating organizational benefit importance. This strategic imbalance undermines reimbursement success because CNEDiMTS evaluates both dimensions.[1]
What Counts as Organizational Benefit for Digital Therapeutics
Organizational benefit encompasses measurable impacts on healthcare delivery: reduction in required clinical staff time, decreased need for specialist consultations, improved adherence to clinical protocols, enhanced data capture enabling clinical decision-making, or cost displacement to less expensive modalities.
Unlike clinical benefit (which reflects effects on patient health), organisational benefit reflects system-level advantages of your DTx. Healthcare systems adopt new digital therapeutics not purely for clinical efficacy but for implementation feasibility and resource efficiency. A DTx that produces modest clinical improvements while substantially reducing the time required from specialists may be more attractive to healthcare systems than one with larger clinical effects that require intensive professional oversight.
Early HAS Engagement: Strategic Imperative for DTx Evidence Design
Early dialogue with HAS enables alignment of DTx evidence generation strategy with regulatory expectations and serves multiple functions grounded in scientific principles.[1]
First: Early DTx meetings allow developers to present preliminary evidence and receive feedback on whether study designs will generate information CNEDiMTS considers relevant.[1] This prevents investment of substantial resources in DTx studies that, upon completion, are considered methodologically inadequate.
Second: HAS evaluators provide guidance on endpoint selection for your DTx, ensuring developers measure outcomes that are clinically relevant and appropriately operationalized.[1]
Third: Early DTx meetings address questions about comparator selection, study population definition, and outcome measurement approaches before data collection begins, preventing costly protocol revisions during active digital therapeutics research.
Two-Stage Evidence Architecture for Optimal DTx Efficiency
The strategic solution to compressed PECAN timelines involves designing DTx evidence as the first phase of a two-stage evidence architecture:
Stage 1 — PECAN-Compatible DTx Evidence:
- Structured single-arm or controlled observational studies
- Strong signal detection for digital therapeutics
- Early organizational insights for DTx implementation
- Proof-of-concept establishment
Stage 2 — Pivotal DTx Validation:
- Comparative design for digital therapeutics
- Robust endpoints
- Economic linkage
- Standard reimbursement qualification[1]
👉 These DTx stages must be designed together, not sequentially. When designed as integrated stages, this approach creates synergies that improve efficiency without compromising rigour. Data collected in Stage 1 can inform Stage 2 DTx study design, and analytical frameworks developed for Stage 1 can be refined for Stage 2.
Emerging International Collaboration: Shared Standards for Digital Therapeutics
France and Germany have recently initiated collaborative efforts to develop shared evaluation frameworks for digital medical devices and digital therapeutics, with planned publication of joint DTx guidance in mid-2026.[1] This emerging international coordination reflects recognition that digital therapeutics operate across borders, yet different national healthcare systems have developed independent evaluation processes.
Current divergence is significant: France publishes both positive and negative CNEDiMTS opinions with detailed reasoning, enabling transparency and allowing digital therapeutics stakeholders to understand DTx evaluation criteria. By contrast, some national systems publish only approved digital therapeutics, providing limited insight into which evidence standards resulted in DTx rejection decisions.[1]
Conclusion: Scientific Rigor as Competitive Advantage for DTx Approval
The core insight emerging from HAS evaluation experience is that scientific methodology functions not as an obstacle to DTx approval but as the foundation enabling approval. Developers who invest in methodological excellence—transparent DTx evidence generation, pre-specified analyses, rigorous data collection, and contextual literature integration—create competitive advantages in regulatory success.
The most sophisticated digital therapeutics technology, inadequately validated, fails regulatory scrutiny. Modest DTx innovations, rigorously evaluated, succeed.
Organisations that prioritise scientific excellence in their DTx programs will establish market leadership through genuine credibility. The future of digital health will ultimately depend less on technological sophistication than on DTx developers’ ability to demonstrate credible value through scientifically rigorous pathways.
References
[1] RegDesk. (2026). Medical devices: Compliance requirements in France. Retrieved from https://www.regdesk.co/blog/things-you-should-know-before-registering-your-medical-devices-in-france/
[2] PMC NCBI. (2024). Organizational impact in healthcare in France: A decade of insights on digital medical device evaluation. Retrieved from https://pmc.ncbi.nlm.nih.gov/articles/PMC12979018/
[3] Veristat. (2026). Single-arm studies: A strategic path to oncology drug approval and digital therapeutic validation. Retrieved from https://www.veristat.com/blog/single-arm-studies-a-strategic-path-to-oncology-drug-approval
[4] Taylor & Francis Online. (2026). Citation accuracy in the Make America Healthy Again report. Retrieved from https://www.tandfonline.com/doi/full/10.1080/15265161.2026.2623873
[5] Bioethics Today. (2026). Citation accuracy and research integrity in health policy documents. Retrieved from https://bioethicstoday.org/blog/citation-accuracy-in-the-make-america-healthy-again-report-maha/
[6] Thesify. (2026). Essay improver: How to fix weak evidence in academic writing. Retrieved from https://www.thesify.ai/blog/essay-improver-how-to-fix-weak-evidence-in-academic-writing
[7] ISPOR Europe 2025. (2025). DTx digital poster: Digital therapeutics evidence requirements and reimbursement pathways in Europe. Retrieved from https://www.ispor.org/docs/default-source/cti-meeting-21305-documents/785a73b4-546e-4473-9e4d-54680d45c5ad.pdf
10 Frequently Asked Questions About DTx PECAN Approval
1. Do we absolutely need a randomized controlled trial for DTx PECAN approval?
No. CNEDiMTS accepts single-arm DTx studies under strict conditions that ensure causal interpretability.[3] The critical requirement is demonstrating that observed changes result from the digital therapeutics intervention rather than confounding factors or natural disease progression. This requires pre-defined protocols, structured data collection, and rigorous bias control, not necessarily a comparator group. However, a well-designed single-arm DTx study with clear methodology is more persuasive than a poorly designed comparative digital therapeutics study.
2. What’s the practical timeline for DTx PECAN evidence generation?
Approximately 12 months, but this requires substantial upfront planning for your digital therapeutics program. Allocate months 1-3 for DTx protocol development and HAS consultation, months 4-10 for patient recruitment and follow-up, and months 10-12 for data analysis and DTx reporting.[1] Attempting 12-month evidence generation without adequate planning results in incomplete digital therapeutics studies with insufficient follow-up and methodological shortcuts that undermine credibility. The compressed timeline is achievable only with strong project management and pre-established infrastructure for your DTx program.
3. Can we use real-world data from our existing DTx patient database?
Yes, but only with careful methodological structure. Pre-specify your analytical approach before querying your DTx database: define cohorts, outcomes, and statistical tests in advance.[1] This prevents “fishing expeditions” where selective analysis creates apparent DTx benefits.[6] Retrospective data mining after identifying favorable digital therapeutics results is explicitly rejected by CNEDiMTS.[4][5]
The key is establishing a protocol before making the DTx query. This approach documents that you had clear hypotheses rather than searching through data until favorable DTx patterns emerged. Many digital therapeutics developers underestimate the importance of this pre-specification, leading to DTx rejection despite having access to potentially valuable data.
4. How do we demonstrate organizational benefit for our DTx in PECAN?
Organizational benefit encompasses system-level advantages: reduced clinician time requirements for your DTx, decreased specialist consultations, improved adherence to DTx protocols, enhanced clinical data capture, or cost displacement.[1] Even purely clinical DTx produces organizational benefits through implementation efficiency.
Study how your digital therapeutics integrates into workflows, what time requirements the DTx creates, whether it reduces parallel resource usage, and whether the DTx enables different care models. This requires operational research alongside clinical evaluation of your DTx. For example, a mental health DTx might reduce clinician consultation time, enabling clinicians to serve more patients with your digital therapeutics. A chronic disease DTx might enable patient self-management, reducing required healthcare visits for digital therapeutics users. Quantify these system-level DTx impacts explicitly.
5. Can we submit DTx evidence from studies conducted in other countries?
Yes, but with critical caveats for your digital therapeutics program. CNEDiMTS accepts international DTx data if it extrapolates meaningfully to French healthcare contexts.[1] The question is whether clinical pathways, treatment decisions, and organizational constraints in your DTx study setting resemble French practice. If care strategy differs substantially, extrapolation of your digital therapeutics becomes questionable.
Provide explicit reasoning demonstrating transferability of your DTx evidence. For example, explain why US mental health system organization is comparable to French organization, or acknowledge specific differences and explain why they should not undermine your DTx evidence transfer. This reasoning, coupled with supporting evidence, allows CNEDiMTS evaluators to assess whether your international digital therapeutics findings apply to French healthcare delivery.
6. What happens if our first DTx PECAN application is rejected?
You can reapply with an improved DTx submission. An opinion is given at a specific point in time and does not prevent DTx reapplication.[1] Revise your digital therapeutics application, supplement data, and address specific methodological concerns identified in the DTx rejection. The published rejection reasoning (unlike some national systems that publish only DTx approvals) enables understanding of evaluation criteria and iterative improvement of your digital therapeutics program.
Many digital therapeutics developers view a DTx rejection as final, but it is actually an opportunity for refinement of your DTx program. CNEDiMTS provides detailed feedback on what was lacking in your digital therapeutics submission. Use this DTx feedback to strengthen your evidence package, addressing specific methodological concerns in your DTx study, expanding sample sizes, extending follow-up periods, or refining DTx outcome measurement approaches.
7. Should we engage with HAS before submitting our DTx PECAN application?
Absolutely. Early dialogue is the only mechanism to validate DTx endpoints, stress-test your methodology, and align expectations.[1] Early meetings prevent investment of substantial resources in methodologically inadequate digital therapeutics studies. HAS provides guidance on DTx study design, endpoint selection, and comparator approaches before data collection begins on your digital therapeutics program.
Early DTx engagement typically occurs at two points: (1) protocol development stage (feasibility consultation for your digital therapeutics) and (2) preliminary results stage (pre-submission consultation for your DTx). Both interactions provide invaluable feedback that improves DTx submission quality and approval probability for your digital therapeutics program.
8. What’s the difference between DTx PECAN evidence and standard reimbursement pathway evidence?
PECAN is Stage 1 of a two-stage DTx architecture.[1] PECAN evidence establishes proof-of-concept for your digital therapeutics through structured single-arm or controlled observational studies demonstrating signal detection and organizational insights. Standard reimbursement (Stage 2) requires confirmatory DTx validation through comparative designs with longer follow-up.
When designed as integrated stages, this approach creates synergies improving efficiency without compromising rigor in your DTx program. PECAN evidence establishes that a signal exists for your digital therapeutics; standard reimbursement evidence confirms the DTx signal’s magnitude and durability. Developers who design both DTx stages simultaneously can ensure data collected in Stage 1 adequately supports Stage 2 digital therapeutics study design.
9. How detailed must our statistical analysis plan be for DTx submission?
Very detailed. Pre-define all primary DTx outcomes, secondary outcomes, subgroup analyses, sensitivity tests, and statistical significance thresholds before database lock for your digital therapeutics program.[1] This specification prevents “p-hacking” and demonstrates that observed DTx findings represent genuine discovery rather than selective reporting.[4][5] Your DTx analysis plan becomes part of formal study documentation submitted with reimbursement applications.
Include specificity about: which statistical tests will be employed for your DTx, why they are appropriate for digital therapeutics, what constitutes clinically meaningful DTx change, how missing data will be handled in your digital therapeutics study, what exclusion criteria will be applied to your DTx analysis, and what thresholds for statistical significance will be used. This level of detail protects against accusations of selective DTx reporting and demonstrates scientific rigor in your digital therapeutics program.
10. Can hybrid devices (physical hardware + software DTx) qualify for PECAN?
PECAN specifically targets software DTx solutions. However, the same CNEDiMTS commission evaluates LPPR (long-term implantable devices), PECAN, PECT, and LATM applications through multiple entry points.[1] You can coordinate multiple requests covering different components through different reimbursement pathways—one LATM component, another LPPR component, and so forth—enabling comprehensive coverage strategy for your digital therapeutics device.
For hybrid digital therapeutics, work with the Ministry’s Social Security Directorate (DSS) to determine DTx eligibility determination. Once a file is deemed eligible, CNEDiMTS evaluates your digital therapeutics, provided the medical device has CE marking and medical purpose. The advantage of the coordinated commission approach is that multiple DTx requests addressing different device components can be submitted and evaluated simultaneously, accelerating overall reimbursement pathway for your digital therapeutics program.