Articol

The French National Health Database: An opportunity to produce real-world evidence for the Early Access Program?

  • Henri Leleu, MD, PhD

  • Martin Blachier, MD, MPH

By leveraging the SNDS, France can modernize its Early Access Program framework, turning fragmented manual reporting into automated, real-time surveillance. This evolution will enhance data quality, improve efficiency, and position France as a leader in real-world evidence generation.

Leveraging SNDS for real-world data collection in early access programs

In the first two parts of this series, we explored how France’s Early Access Program (EAP) has played a crucial role in providing patients with severe or rare conditions faster access to potentially life-saving treatments.

We also examined why the Haute Autorité de Santé (HAS) has undertaken a review of EAP’s methodological framework due to key challenges: difficulties in confirming efficacy post-EAP, financial strain on the national healthcare system, and concerns surrounding the high costs and limited utility of the current data collection process.
These challenges have had tangible consequences. While the EAP maintained a success rate of 70% between 2021 and early 2024, this figure has now dropped to less than 50%, with only 16 favorable opinions out of 33 applications in 2025.

In this final installment of our three-part series, we explore the potential of the National Health Database (SNDS, Système National des données de Santé) to simplify and automate the data collection process for monitoring the EAP. We also conclude with insights from the industry on how the EAP in France can be enhanced moving forward.
 

An overly manual and burdensome data collection system

A key pillar of the EAP is the requirement to collect real-world data (RWD) through the Protocole d’Utilisation Thérapeutique et de Recueil des Données (PUT-RD). Designed to capture critical clinical and demographic information on patients benefiting from early access, the PUT-RD relies on hospital clinicians to complete the forms, with financial compensation provided by the sponsor.

The PUT-RD currently requires the collection of a wide range of variables, including patient characteristics, medical eligibility and non-eligibility criteria, and disease-related data, such as diagnosis, prior treatments, and comorbidities. Data on treatment, including dosage, concomitant treatments, and temporary or permanent treatment interruptions, are also required. Efficacy data must be adapted to the specific medication and include both objective criteria and, when applicable, patient-reported outcomes (PROs) such as quality of life or symptom assessments using standardized questionnaires. Additionally, safety and tolerance data, including adverse events and special situations, are collected throughout treatment. These data are gathered at multiple points, including treatment initiation, follow-up, and upon definitive treatment cessation.

The data collected through the PUT-RD are crucial for evaluating treatment efficacy, safety, and real-world use. They inform decisions by the HAS and the French National Agency for the Safety of Medicines and Health Products (ANSM) regarding EAP renewals, as well as decisions for reimbursement and pricing assessments by the Transparency Commission.

However, both the HAS and industry stakeholders recognize that the current system is overly manual, complex, and time-intensive. Challenges such as limited resources, fragmented systems, and reliance on hospital clinicians who often complete PUT-RD forms outside of regular working hours have contributed to an average data completeness rate of just 65%, falling significantly short of HAS’s 90% target. These shortcomings undermine the evidential value of EAP data, which are critical for ensuring patient safety and supporting reimbursement decisions.

LEEM (Les Entreprises du Médicament), the industry’s representative, composed a white paper highlighting several barriers exacerbating these issues:

  • Complex and inconsistent processes: Each industrial sponsor develops its own data capture system, resulting in duplication and confusion.
  • Opaque agreements: Lack of transparency between industry and hospitals regarding compensation and data usage creates inefficiencies.
  • Fragmented platforms: Limited interoperability discourages engagement and collaboration.
  • Shortage of trained personnel: There is a notable lack of clinical research associates and data managers, particularly outside of major university hospitals.

Automatic patient demographics and treatment tracking with SNDS

The SNDS compiles health insurance claims for hospital stays and outpatient care across nearly the entire population, in addition to mortality data (including cause of death) and socio-demographic information. The database is updated continuously for outpatient claims and annually for hospital claims. All early access treatments provided by hospitals are traceable in the SNDS if they are reimbursed by National Health Insurance (i.e. when they are not provided free of charge). This opens the possibility of automatic extraction of key variables that are currently being requested in the PUT-RD, such as:

  • Patient demographics (age, sex, region, comorbidities)
  • Treatment data including previous or concomitant treatments, treatment duration, and estimated doses


While some variables (e.g. PROs or biological results) are unavailable, the SNDS still covers a substantial portion of what the HAS deems essential for contextual analysis. Furthermore, the SNDS can also be used to identify adverse events, as showcased in the work done by the public group EPI-PHARE

In short, the SNDS can automate the repetitive, descriptive part of the data collection process, freeing hospitals from a major administrative burden and improving completeness and comparability. A particularly promising use of SNDS integration is comparing patients receiving EAP drugs to those under standard care. Because SNDS records are population-wide, they allow for:

  • Matching treated patients to comparable controls
  • Evaluating real-world effectiveness relative to existing treatments
  • Assessing healthcare resource use, hospitalization rates, and cost-effectiveness

Feasibility and challenges of using SNDS for EAP

The HAS conducted a feasibility assessment on nine drugs across 16 indications, demonstrating that patient counts derived from the SNDS were largely consistent with those collected through PUT-RDs. This validation underscores the potential of the SNDS not only for administrative tracking but also for generating robust real-world evidence, aligning with broader European objectives to enhance regulatory reliance on RWD.

Despite these promising findings, the SNDS still faces significant limitations in its application for EAP analysis. A major challenge is the absence or poor quality of indication coding, particularly for drugs administered in outpatient settings and dispensed by hospital pharmacies. The HAS report indicates that hospitals frequently fail to record indication codes or rely on non-standardized coding practices, making it difficult, or even impossible, to accurately associate specific indications with individual patients, especially for drugs with multiple uses. This limitation severely impacts the interpretability of automated reports, particularly in oncology and rare disease treatments where indication-specific outcomes are critical.

Moreover, the SNDS lacks detailed clinical information, including laboratory results, imaging data, and procedural outcomes, which are essential for understanding the clinical context of prescriptions. This gap is especially problematic for complex indications, such as those requiring biomarker results or specific clinical features, further constraining the utility of the SNDS for comprehensive EAP monitoring and analysis.

Next steps: From data extraction to decision support

Building on the feasibility study, the HAS has developed a prototype automated reporting tool designed to generate structured summaries of EAP utilization using SNDS data. These reports currently include key metrics such as:

  • The number of patients treated per indication
  • Patient demographics and comorbidities
  • A description of the prescription setting

Future iterations of the tool could expand its capabilities to include dosage estimation, follow-up duration, treatment persistence, and interactive visualization dashboards for decision-makers. Automating these reports would significantly reduce feedback cycles, enabling near real-time surveillance and continuous optimization of EAP management.

Regulatory oversight could also be enhanced through shared dashboards across agencies, facilitating:

  • Monitoring of ongoing EAPs
  • Early detection of safety signals
  • Data-driven recommendations for transitioning drugs to regular reimbursement pathways

The adoption of the SNDS and the reporting tool remains under discussion. Following a public consultation in early 2025, stakeholders are still awaiting the HAS’s final conclusions on its implementation.

Industry perspective: Challenges and proposals for EAP optimization

LEEM’s report, based on extensive field feedback, makes 12 proposals for improving EAP data collection. Collectively, these measures aim to transform EAP data collection from a regulatory formality into a collaborative, learning health system process.

Short-term actions:

  1. Create a centralized, ergonomic resource portal managed by the HAS for both clinicians and patients.
  2. Institutionalize in-person consultations to ensure patients understand the objective and consent to the data collection process.
  3. Clarify regulatory objectives and expected uses of data.
  4. Evaluate how EAP data are used in HAS decision-making.
  5. Tailor data collection scope to hospital capacity and resources.
  6. Publish a directory of EAP referents at each pharmaceutical company.
  7. Audit EAP funding allocations for EAP data collection within hospitals.

Medium- to long-term proposals:

  1. Introduce training modules on EAP and RWD for clinicians and research assistants.
  2. Establish an annual stakeholder meeting to share lessons and progress.
  3. Develop a single, unified national data platform co-managed by the HAS, ANSM, and LEEM.
  4. Pilot AI-assisted data collection tools to automate entry and validation.
  5. Systematically involve patient associations and scientific societies in PUT-RD design.

Conclusion: Toward a smarter, more evidence-driven EAP

EAPs remain a cornerstone of France’s policy for fostering innovation and ensuring timely access to treatments, particularly for drugs prior to marketing authorization. However, the data collection required to assess drug efficacy and safety has faced significant challenges, posing a substantial burden on clinicians and the industry alike.

The SNDS presents a transformative opportunity to streamline and scale RWD collection, replacing fragmented manual reporting with continuous, automated surveillance. By integrating clinical, administrative, and population-level data, France has the potential to lead Europe in real-world evidence–driven regulatory practices.

To realize this vision, industry and institutional stakeholders must align their efforts in governance, data infrastructure, and workforce training. Simplification, transparency, and automation are no longer optional; they are essential to preserving the credibility and efficiency of the EAP framework.

 

This article summarises Cencora’s understanding of the topic based on publicly available information at the time of writing (see listed sources) and the authors’ expertise in this area. Any recommendations provided in the article may not be applicable to all situations and do not constitute legal advice; readers should not rely on the article in making decisions related to the topics discussed.

 

Luați legătura cu echipa noastră

Echipa noastră de experți în valoare este dedicată transformării dovezilor, informațiilor privind politicile și informațiilor de piață în strategii eficiente de acces la piața globală. Permiteți-ne să vă ajutăm să navigați cu încredere prin peisajul complex al asistenței medicale din ziua de azi. Contactați-ne pentru a afla în ce mod vă putem sprijini în atingerea obiectivelor.


Sources:

  • HAS. Comprendre l’évaluation des medicaments. 2021. https://www.has-sante.fr/jcms/c_412115/fr/comprendre-l-evaluation-des-medicaments
  • HAS. Doctrine de la commission de la transparence (CT). Principes d’évaluation de la CT relatifs aux médicaments en vue de leur accès au remboursement. 2023. https://www.has-sante.fr/upload/docs/application/pdf/2021-03/doctrine_ct.pdf
  • HAS. Etude de faisabilité: Exploitation des données du SNDS pour contextualiser l’utilisation des médicaments en accès précoces. 2024. https://www.has-sante.fr/jcms/p_3552759/fr/rapport-de-faisabilite-snds-acces-precoces
  • LEEM. Accès précoce. Douze propositions pour optimiser et donner du sens au recueil de données. 2024. https://www.leem.org/index.php/publication/acces-precoce-12-propositions-pour-optimiser-et-donner-du-sens-au-recueil-de-donnees
 

Resurse conexe

Webinar

RWD potrivit scopului: O parte integrantă a planificării dovezilor

Webinar

Cum să ajungeți la clienți și să eliminați zgomotul

Articol

Cum poate inovația digitală să fundamenteze procesul decizional condus de RWE

Cencora.com furnizează traduceri automate pentru a ajuta la citirea site-ului web în alte limbi decât engleza. În aceste traduceri, s-au depus eforturi rezonabile pentru a oferi o calitate corectă. Cu toate acestea, nicio traducere automată nu este perfectă și nici nu este destinată să înlocuiască traducătorii umani. Aceste traduceri sunt furnizate ca serviciu utilizatorilor site-ului Cencora.com și sunt furnizate „ca atare”. Nu se oferă nicio garanție de niciun fel, expresă sau implicită, cu privire la acuratețea, fiabilitatea sau corectitudinea oricăreia dintre aceste traduceri efectuate din limba engleză în orice altă limbă. Este posibil ca unele conținuturi (cum ar fi imagini, videoclipuri, Flash etc.) să nu fie traduse cu acuratețe din cauza limitărilor software-ului de traducere.

Orice discrepanțe sau diferențe create în traducerea acestui conținut din limba engleză într-o altă limbă nu au caracter contractual și nu au niciun efect juridic privind conformitatea, aplicarea sau orice alt scop. Dacă sunt identificate erori, vă rugăm să ne contactați . Dacă apar întrebări legate de acuratețea informațiilor conținute în aceste traduceri, vă rugăm să consultați versiunea în limba engleză a paginii.