About the Health Data Hub
What is the Health Data Hub ?
In the digital era, each interaction with healthcare services enables the creation of data. All this data constitute precious and essential raw material for research. By gathering and analysing them, researchers can answer concrete questions to improve the quality of care and treatment, such as studying the side effects of prescriptions. Companies can develop new solutions, such as algorithms to detect heart failure, for example. Data heritage in France is particularly large and structured, which can be an international competitive advantage for research and innovation.
Until now, obtaining access to these data has raised many difficulties for those who wish to use them in projects of public interest:
- The data are scattered among multiple databases, little known and not easily understood by outsiders;
- The procedures for accessing health data are complex, especially because of the sensitivity of these data, and are governed by different, sometimes discretionary, rules;
- The tools and skills needed to process data securely, as required, are costly and often inaccessible to small research teams or start-ups.
As a result, some projects, which could bring real benefits to patients, take several years to get off the ground, or simply don't at all. Some French start-ups, wishing to develop new solutions, are obliged to form partnerships with foreign actors to collect data. Their innovations will not necessarily be adapted to, or even available to French patients.
Following the Villani Report on Artificial Intelligence, published on March 28, 2018, the President of the Republic affirmed his desire to make health one of the priority sectors for the development of artificial intelligence in France.
Provided for by the 24 July 2019 Law on the organisation and transformation of the healthcare system, the Health Data Hub is a public structure whose objective is to enable project coordinators to easily access non-nominative data hosted on a secure platform, in compliance with regulations and citizens' rights. They will be able to cross-reference and analyse the data in order to improve the quality of care and patient support.
To find out more about the national artificial intelligence plan for the Health Data Hub project, see the "AI for Humanity" commitments.
To find out more about the digital health strategy of the Health Data Hub project, see the roadmap "Accelerating the digital shift".
For more information on the creation of the Health Data Hub, see the prefiguration report.
To find out more about the Health Data Hub's service offering, see the brochure.
To find out more about the guarantees provided to civil society, see the Health Data Hub's commitments to civil society.
What is its legal status and governance model ?
The Health Data Hub is constituted as a public interest group, whose constituent agreement was approved by ministerial decree on 29 November 2019. The group brings together 56 stakeholders presented in the decree. It implements the major strategic orientations relating to the National Health Data System (SNDS) set by the State, in particular the Ministry of Solidarity and Health.
It is financed mainly by the public sector. Before the official creation of the public interest group, the Health Data Hub project was conducted under the direction of the Ministry of Solidarity and Health (Directorate of Research, Studies, Evaluation and Statistics (DREES)) and was selected in the first call for projects of the Fund for the Transformation of Public Action (FTAP). In this context, it was granted initial funding of 36 million euros for four years. A further 40 million euros came from the national health insurance expenditure target (ONDAM).
To find out more about the first call for projects of the Fund for the Transformation of Public Action (FTAP), see the portal for the transformation of public action.
What projects can be conducted through the Health Data Hub ?
The reuse of health data can contribute to improving the quality of care and patient support in many ways. Here are a few examples of research purposes :
- Providing answers to rare pathologies: for example, sarcoma belongs to the rare tumours for which the effectiveness of isolated clinical trials is reaching its limits. For nearly 40 years, they have been conducted without being able to decide on the relevance of chemotherapy before or after surgery. In this context, the analysis of data collected from patients as part of cohorts, combined with healthcare consumption data from the French National Health Insurance system, offers a real opportunity to evaluate treatments and their performance.
- Supporting healthcare professionals in an increasingly complex clinical context: prescription software already uses alert tools to notify healthcare professionals when different treatments taken by the same patient may reveal incompatibilities, and imply health risks. These can be improved, as these systems today generate so many alerts that they are often deactivated or ignored by healthcare professionals. Data analysis allows the development of tools to prioritize alerts and filter those that must be taken into account.
- Better patient management as a result of new organisational methods: heart failure flare-ups account for almost 5% of hospitalisations in France. By correlating data from pacemakers with hospitalization data, it is possible to design warning tools that detect weak signals early on and enable patient management as early as possible.
- Predicting individual patient trajectories and improving prevention actions: data from cohorts of patients monitored in Parkinson's expert centers, combined with data from health insurance, make it possible to study the progression of the pathology and thus improve patient monitoring. Tools could thus be developed and provided to neurologists.
- Improving the understanding and transparency of the healthcare system: in 2017, nearly 82,000 adverse drug reactions were reported for 12,000 marketed drugs. The analysis of health data makes it possible to go further in understanding by calculating reporting rates, i.e. the number of adverse reactions reported in relation to the number of patients actually exposed. This figure is strategic for the authorities, healthcare professionals and patients to appreciate the importance of each side effect. Currently carried out manually, this calculation could be automated and facilitated thanks to access to large databases by the French National Agency for Medicines and Health Products Safety (ANSM).
- Save medical time, improve screening and reduce diagnosis times: with an estimated 11,883 deaths in 2017, breast cancer kills more women than any other cancer in France. Early detection reduces mortality by 21%. The use of artificial intelligence could further improve organized breast cancer screening by reducing the rate of false positives and false negatives.
- Offering patients the best long-term treatments: information concerning the links between taking drugs and their long-term effects is currently very incomplete, both in general and in organ transplantation cases. In the context of lifelong treatment, knowledge of these relationships is essential for optimising therapeutic strategies, the choice of doses and also the formulas of these drugs.
All the research projects that will be carried out on the Health Data Hub's technological platform will be described in the project directory, which lists all the projects using health data, including when they are not carried out on the Health Data Hub's technological infrastructures.
For more information on the Health Data Hub projects, see the list of laureate pilot projects from the first Health Data Hub call for projects and the list of institutional projects.