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Supervised by a National Commission for Information Technology and Civil Liberties (CNIL) standard since 2021, the creation of a Healthcare Data Warehouse (HDW) faces a double challenge: new means of sharing, storing, and processing information on the one hand, and constantly changing regulations applicable to producers and users on the other. Indeed, the massive digitization of these sensitive data reveals the multidimensional complexity of Big Data processing in the health sector, while the challenges of pooling and storing this information are deeply impacted by the development of digital technologies.

The healthcare data warehouse solution 

Authorized since 2017, HDWs are, this year, the subject of a government call for projects designed to accompany and financially support their creation, as part of the “France Relance” eHealth acceleration strategy for 2030.

Whether public or private, HDWs remove the barriers to the exploitation of medical data by allowing the collection and integration of massive health data from various medical administrative and clinical information sources (patient data relating to management, data from previous research, socio-demographic data, etc.).

The common information system thus created and validated by the CNIL, promotes the sharing and use of health data for analysis and research purposes, within a legal and protective framework for individuals.

The challenges or Artificial Intelligence (AI)

In this context, AI is necessary to make sense of the large amount of data collected. By enabling predictive analysis and forecasting to develop and train machine learning models, algorithms are revolutionizing the cross-functionality of studies, research, and analysis by providing high standard guarantees on both the quality and safety of medical devices.

The benefits of a common asset for patients, healthcare professionals, and public health

The pool of data collected by the HDWs constitutes an asset to be built to value the data. The benefits are legion:more studies and research, access to massive data through the integration of new data sources (SNDS matching, cohort studies, data lakes, etc.), broader perspectives and the emergence of new use cases.

The projects, thus defined on a legal and official basis, benefit from the standardization of the elements of governance, security, and compliance, which enhances their value, durability and legitimacy from the outset.

Finally, interoperability with other HDWs authorized by the CNIL promotes medical management with increased autonomy to improve patient care.

Risk management and compliance of sensitive data 

HDWs define rules for hosting, accessing, and protecting health data, within the framework of the GDPR. When required, AI technologies appear promising for anonymizing unstructured data.

The protection of health data must be ensured by relying on systems recommended by the CNIL, whose standard No 2 of 17/11/2021relating to warehouses makes it possible to guarantee appropriate technical and organizational measures, to standardize the risk analysis and to set up a security policy.

Finally, a prior Data Protection Impact Assessment(DPIA) is mandatory.

Great opportunities for innovation 

HDWs promotes the development of Artificial Intelligence (AI) algorithms and the deployment of opportunities including for industrials partners. Examples are significant of this contribution to the revolution of the sector, whether it is a question of reducing the time to identify a drug candidate, setting the price of health products or even their re-evaluation. Accelerating medical research, improving patient information aspart of their care pathway, and providing healthcare professionals with tools to support their activity: the societal challenges are major in this trajectory, which aims to ensure the monitoring and continuous improvement of the healthcare system.

Toward a health data revolution? 

The advent of “medicine 4.0” is already bringing together new players and new expertise, particularly related to HDWs.Confidentiality and security, data sciences, patient applications, the density of the ecosystem now requires experienced legal support like that offered by Iliomad, in order to address the regulatory constraints of the issues. As a specialist in regulatory compliance for health data processing in the context of medical research, Iliomad has already supported the creation of three public and private HDWs.


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