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Real World Evidence (RWE) 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data

RWE 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data

 

The CNIL (Commission Nationale de l’Informatique et des Libertés) is the French data protection authority. CNIL has issued various “Reference Methodologies” (Méthodologies de Référence or MRs) which are guidelines/frameworks for compliance with data protection regulations in specific areas e.g., MR-001 (interventional research) and MR-003 (non-interventional research) which cover research involving direct interactions with people (RIPH), or MR-004 for research involving secondary use of existing personal healthcare data i.e., research not involving direct interaction with people (RNIPH).

By declaring conformity to the applicable reference methodology to the CNIL, research sponsors do not need to seek individual authorisation for each research project that involves non-anonymous data, making this an efficient and effective form of self-regulation.

Key features of MR-004 conformity include:

  1. Data Minimisation: Only collect the data that is strictly necessary for the research or healthcare activity.
  2. Purpose Limitation: Use the data only for the specified, explicit, and legitimate purposes for which it was collected.
  3. Consent: Access to and use (re-use) of existing patient health data is subject to informing the affected patients (patient information).
  4. Security: Guidelines for data storage, encryption, and access control, in line with GDPR requirements.
  5. Data Subject Rights: Details about how to facilitate data subjects’ rights like access, rectification, deletion, and data portability.
  6. Data Retention: Sets time limits on how long the data can be stored and provides guidance on secure deletion practices.
  7. Accountability and Governance: Stresses the importance of record-keeping, conducting impact assessments, and potentially appointing a Data Protection Officer (DPO).
  8. Data Sharing: Provides guidelines for sharing data with third parties, including cross-border data transfers.
  9. Legal Compliance: Ensures that the data processing activities are compliant with other relevant laws and ethical considerations.

By adhering to MR-004 or similar CNIL Reference Methodologies (as applicable), healthcare organizations and researchers can use real-world data while fulfilling their legal obligations and ethical responsibilities for data protection (GDPR). Note that these guidelines are subject to change, so it’s crucial to consult the most current version and seek legal advice for complex scenarios.

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Real World Evidence (RWE) 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data2023-09-03T18:11:56+00:00

Real World Evidence (RWE) 201 – France – Health Data Hub: Facilitating Access to Real World Data

RWE 201 – France – Health Data Hub: Facilitating Access to Real World Data

 

The purpose of France’s Health Data Hub (HDH) is to facilitate the sharing of health data to support research and innovation. Launched in December 2019, the HDH is a health data platform established by the French government to combine existing health databases and make them more accessible for research and development purposes [1].

The platform allows public interest project leaders to access large volumes of data and utilize the platform’s computing power to run complex research algorithms [2].

The reuse of health data has significant potential for enhancing healthcare quality and patient support through research. This includes [3]:

  • Evaluating the effectiveness of treatments for rare pathologies like sarcoma by combining patient and insurance data.
  • Enhancing prescription alert systems to help healthcare professionals make better decisions in complex clinical scenarios.
  • Developing early warning tools for conditions like heart failure by correlating pacemaker and hospitalization data.
  • Predicting disease progression, as in Parkinson’s disease, and improving preventive measures using patient cohort data.
  • Streamlining the reporting and analysis of adverse drug reactions to improve healthcare system transparency.
  • Utilizing AI to improve early cancer screening, thus reducing false positives and negatives, and saving medical time.
  • Gathering data on long-term effects of medications, particularly in cases of organ transplantation, to optimize therapeutic strategies.

Researchers interested in accessing real-world data (RWD) and generating real-world evidence (RWE) can benefit from the HDH in several ways:

  1. Data Accessibility: The HDH provides a single gateway for health data in France, making it easier for researchers to access various data sources [4].
  2. Data Catalogue: The platform includes a data catalogue with one of the world’s largest healthcare claims databases, offering researchers a rich source of information for their studies [4].
  3. Collaboration: The HDH brings together 56 stakeholders, including the largest French public organization for scientific research, CNRS, fostering collaboration between government, producers of health data, and users of public and private health data [1].
  4. Support for Projects: The HDH provides researchers with the necessary resources and infrastructure to carry out their studies [4].
  5. Data Security: The platform ensures the protection of health data through a data access approval process, maintaining the privacy and security of sensitive information [4].

By providing researchers with easier access to health data and the necessary resources to analyse and process this data, the HDH can help generate valuable insights and contribute to advancements in the health sector [4].

 

References:

[1] Everything you need to know about Health Data Hub – Implicity

Link: https://www.implicity.com/everything-you-need-to-know-about-health-data-hub/

[2] The Health Data Hub publishes its roadmap for 2022 – French Healthcare (30 May 2022)

Link: https://frenchhealthcare.fr/the-health-data-hub-publishes-its-roadmap-for-2022/

[3] Health Data Hub – FAQ in English

Link: https://www.health-data-hub.fr/page/faq-english

[4] Health Data Hub – Multi-stakeholder workshop RWD quality and RWE use (26 June 2023)

Link: https://www.ema.europa.eu/en/documents/presentation/presentation-rwd-data-quality-experience-france-e-bacry-health-data-hub_en.pdf

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Real World Evidence (RWE) 201 – France – Health Data Hub: Facilitating Access to Real World Data2023-09-03T17:41:34+00:00

Real World Evidence (RWE) 101 – Verifying the Source of Data (Not to be Confused with Source Data Verification…Yup! Confusing!)

RWE 101 – Verifying the Source of Data (Not to be Confused with Source Data Verification…Yup! Confusing!)

Verifying the source of data is critical in the context of real world evidence (RWE) because the quality and reliability of the data are essential for generating accurate and trustworthy evidence. RWE is derived from real-world data (RWD), which is often collected from a variety of sources, including electronic health records (EHRs), claims databases, patient registries, and wearable devices.

There are several reasons why it is important to verify the source of RWD used to generate RWE:

Data quality: The quality of RWD can vary depending on the source, and it is essential to ensure that the data used to generate RWE are of high quality. Verification of the data source can help ensure that the data have been collected and managed in accordance with accepted standards and best practices.

Data completeness: Ensuring that the RWD used to generate RWE are complete and accurate is critical to the validity and reliability of the evidence. Verification of the data source can help ensure that all relevant data have been captured and that there are no gaps or inconsistencies in the data.

Data relevance: RWE is generated from RWD that may come from diverse sources, and it is important to verify that the data are relevant to the research question or hypothesis being investigated. Verification of the data source can help ensure that the data used to generate RWE are appropriate for the research question being addressed.

Data bias: RWD can be subject to various types of bias, including selection bias, measurement bias, and confounding bias. Verification of the data source can help identify potential sources of bias and enable appropriate adjustments to be made to the analysis to account for any bias.

In summary, verifying the source of data used to generate RWE is critical to ensure that the evidence generated is accurate, reliable, and trustworthy. It can help ensure that the data are of high quality, complete, relevant, and free from bias, which are all essential for generating high-quality evidence that can inform clinical decision-making and healthcare policy.

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Real World Evidence (RWE) 101 – Verifying the Source of Data (Not to be Confused with Source Data Verification…Yup! Confusing!)2023-08-07T11:35:44+00:00

Real World Evidence (RWE) 101 – Is ‘Retrospective Data’ the Same as ‘Secondary Use of Existing Data’?

RWE 101 – Is ‘Retrospective Data’ the Same as ‘Secondary Use of Existing Data’?

Retrospective data generally refers to data that has already been collected for another purpose and is being used retrospectively to answer a new research question. This data can come from various sources, such as electronic health records, claims databases, or patient registries, and is often used to generate RWE.

On the other hand, secondary use of existing data refers to the practice of using existing data for a purpose other than the one for which it was originally collected. This can include using data from clinical trials for post-market surveillance or using data from a patient registry for comparative effectiveness research.

While retrospective data can be one type of existing data that is used for secondary purposes, not all secondary uses of data involve retrospective data. For example, prospective data collected for one purpose, such as routine clinical care, can be used for secondary purposes, such as generating RWE.

In summary, retrospective data and secondary use of existing data are related but not interchangeable terms in the context of RWE. Retrospective data is a type of existing data that can be used for secondary purposes, but not all secondary uses of data involve retrospective data.

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Real World Evidence (RWE) 101 – Is ‘Retrospective Data’ the Same as ‘Secondary Use of Existing Data’?2023-08-07T23:11:48+00:00

Real World Evidence (RWE) 101 – EHDS and GDPR – How does GDPR support the secondary use of existing health data for the purposes of scientific research?

RWE 101 – EHDS and GDPR – How does GDPR support the secondary use of existing health data for the purposes of scientific research?

The GDPR (General Data Protection Regulation) includes provisions that support the secondary use of existing health data for scientific research purposes, while also protecting the privacy and data protection rights of individuals.

One of the key ways that the GDPR supports the secondary use of health data for research is through the concept of “legitimate interests”. Article 6(1)(f) of the GDPR allows for the processing of personal data if it is necessary for the legitimate interests of the data controller or a third party, provided that those interests do not override the fundamental rights and freedoms of the data subject. Scientific research can be considered a legitimate interest, provided that appropriate safeguards are in place to protect individuals’ rights and freedoms.

In addition, the GDPR includes provisions that specifically address the use of health data for scientific research. For example, Article 9(2)(j) allows for the processing of special categories of personal data, such as health data, for scientific research purposes, provided that appropriate safeguards are in place.

The GDPR also requires that data controllers implement appropriate technical and organizational measures to ensure the security and confidentiality of personal data, including health data. This includes requirements for data pseudonymization and encryption, as well as procedures for data breach notification.

Overall, the GDPR strikes a balance between protecting individuals’ privacy and data protection rights, and supporting the important public interest in scientific research. By providing a framework for the responsible and transparent use of health data for research purposes, the GDPR can help to facilitate the development of new treatments and interventions that can improve public health outcomes.

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Real World Evidence (RWE) 101 – EHDS and GDPR – How does GDPR support the secondary use of existing health data for the purposes of scientific research?2023-08-07T23:09:58+00:00
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