Dataspace4Health - Sustainability Perspective

Open access article

Project Overview 

DS4H is an open healthcare data exchange ecosystem, focusing on innovation in medical treatments built on secure data sharing. It is led by NTT DATA Luxembourg and co-financed by the Luxembourg Ministry of Economy, as part of the national strategy based on EU regulations. It allows us to leverage AI for healthcare and research and addresses both business/patient needs by exploring the potential of data to develop new treatment options. 

Dataspace4Health is a project led by NTT Ltd Luxembourg (now NTT DATA Luxembourg) that is financed by the Ministry of Economy of Luxembourg as part of Luxembourg’s national Gaia-X strategy. DS4H aims to transform the future of health and to define the future of data exchange for Luxembourg based on European Regulation. DS4H leverages European Regulation in regards to data spaces and Gaia-X to build the technical foundation for regulated Health Data Exchange.

Our collaboration system is an open ecosystem of partners [CB1] representing key domains of the Luxembourg healthcare sector. It includes hospitals (Hôpitaux Robert Schuman), a public biomedical research organisation (Luxembourg Institute of Health), Luxembourg’s national eHealth competence centre (Agence eSanté), an economic interest group created by the Luxembourg Government (Luxembourg National Data Service), an university (University of Luxembourg, represented by its ""SnT, the Interdisciplinary Centre for Security, Reliability and Trust), an innovation agency and economic Interest Group supported by the Luxembourg Government (Luxinnovation),  and a multinational IT company NTT Luxembourg .

Circumstances that lead to collaboration:

The project is motivated by the need for a new approach to share data for research and innovation in healthcare with the longer term aim to improve patient's outcome while ensuring data protection and compliance to EU regulations.

Currently health data is often siloed, fragmented and underutilized, which limits the potential for innovation and research. Based on the EU strategy for data, this project will explore how health data spaces can be utilized while ensuring data protection, security and interoperability. It aims to demonstrate the benefits of data-driven innovation and AI for healthcare and research, such as improving diagnosis, treatment, and prevention of diseases, enhancing patient outcomes and quality of life, and advancing scientific knowledge and discovery.

As a context, following the first wave of COVID-19 the Government of Luxembourg, the Luxembourg Institute of Health and Laboratoires Réunis worked together to create a mass testing system to reduce the future impact of the pandemic. Together with Laboratoires Réunis, NTT DATA Luxembourg created a fully digital system to manage the testing process. The multicloud solution ensured that clinical information was securely stored on Laboratoires Réunis’s private cloud with the AWS cloud providing the scalability needed for the rest of the solution, in a secure manner. By leveraging our multicloud expertise they processed 20,000 tests per day with full visibility into the status of every test.

On top, in another project, NTT DATA Luxembourg partnered with Hôpitaux Robert Schuman, to leverage the speed and security of 5G to connect patients to doctors and health-related Internet of Things devices for faster diagnosis and treatment. NTT's digital health platform model also allowed the hospital to receive and share patient information securely to diagnose and treat patients and improve health outcomes. NTT built the digital health platform for Hôpitaux Robert Schuman on Microsoft Cloud for Healthcare. It connected apps, services and health-related IoT devices to exchange sensitive data and content securely and reliably. Functional tests were carried out without the usage of real patient data, due to regulation, enabling them to explore the opportunities presented by delivering hospital level services outside the hospital.

To ensure that these solutions can seamlessly meet all future compliance requirements, especially in the area of healthcare data exchange, the next step is our actual project DS4H, with the creation of a health data exchange platform that can be deployed both in Luxembourg and across Europe, with the potential to revolutionize patient outcomes and experiences. This project is further strengthened by two use cases focusing on major diseases, namely Diabetes and Oncology.

Role of each partner:

Hôpitaux Robert Schuman: provides a harmonized view and strategy between all the partners (regulation, compliancy, technically) about how to bring the Health Data Spaces to Luxembourg and is both active in the research of Diabetes use case, as well as being involved in setting-up the technical infrastructure for the Oncology use case.

Centre Hospitalier de Luxembourg: supports the Oncology use case from a medical side[CB2] [CB3] 

Luxembourg Institute of Health: leads the Oncology use case (with focus on colorectal- and lung cancer), and has an active research role in the Diabetes use case.

Agence Esanté: provides the national patient record

Luxembourg National Data Service: trusted 3rd party authority which is regulating access to the data for research

Laboratoire National de Santé: molecular genetics data provider for the Oncology use case

University of Luxembourg: research role for the Diabetes use case

Luxinnovation: supports innovative projects with resources

Luxembourg National Cancer Institute and National Center for Translational Cancer Research: support the research for the Oncology use case.

NTT DATA Luxembourg: Project Lead including the Technology, Business, Legal and Dissemination Streams leadership with a global project responsibility and 24 months business consulting engagement. Our company is accountable for the data compliancy framework, architecture, blueprint, and templates, integrating patient record into platform, integrating end-to-end solution, testing and dissemination of the project results.

The importance and significance of this project.

DS4H aims to demonstrate the benefits of data exchange and the subsequent usage of AI for healthcare and research, such as improving diagnosis/treatment/prevention of diseases, enhancing patient outcomes and quality of life, and advancing scientific knowledge and discovery.

1. Enhancing patient care

One of the key benefits aimed for is continuously enhancing patient care due to continuous collaboration between research, clinicians and care, with the ultimate goal to improve diagnoses and treatments, come to a better understanding of diseases, and effective preventive measures.

Additionally, the platform will foster research and innovation by providing secure access to health data, enabling research that will ultimately lead to improved healthcare outcomes.

Diabetes use case example: Diabetes affects millions – projected 783 million by 2045 – and, if not managed well, can lead to serious complications. This use case of the project is about building an AI-powered decision support system that uses a “digital twin” – a virtual replica of a patient’s health profile – with the aim to in the future help doctors prevent these complications.

Here is how it works:

· Dynamic Health Snapshot: The system gathers routine patient data—like lab tests, glucose readings, and treatment details—to keep an up-to-date virtual copy of each patient’s health status. This digital twin gives clinicians a real-time snapshot of how a patient is doing.

· Smart Treatment Simulations: Using the digital twin, doctors can simulate changes such as adjusting medication doses or tweaking lifestyle factors like diet and exercise. This helps forecast improvements in blood sugar control and overall health before any real-world changes are made.

· Continuous Learning: Patients also have the option to allow their (anonymized) data to be continuously added to the system. This helps improve the AI’s predictions over time, making it smarter and more accurate for everyone.

· Clinician-Focused Conversational AI: Our system includes a cutting-edge conversational AI tool designed exclusively for clinicians. This smart assistant helps doctors navigate complex digital twin data and treatment simulations using natural, intuitive language. By translating advanced analytics into clear, actionable insights, this conversational AI revolutionizes the use of digital twins in healthcare, making data-driven decision-making more efficient and accessible.

In simple terms, our system will give doctors a powerful tool—a digital mirror of a patient’s health—that not only can guide treatment decisions but also continuously refines its predictive capabilities. With the addition of a clinician-focused conversational AI, our approach transforms how digital twins may be used in healthcare, with the objective of making personalized diabetes care smarter and more efficient than ever.

This AI-based diabetes complications decision support tool is a joint effort by clinical experts from Hôpitaux Robert Schuman, data scientists from the University of Luxembourg, and specialists from LIH. Together, they are working to create a reliable tool that would allow personalized diabetes care and reduces the risk of complications.

Oncology use case example: Cancer is the second leading cause of death in many countries, after cardiovascular diseases. Every year, cancer affects tens of millions of people worldwide, and more than half of them die from it. While hospitals are in charge of diagnosis and therapy, researchers bring novel solutions, treatments, and insights on disease mechanisms to the oncology field. The goal of this use case is to create a  technical infrastructure based on a federated data architecture that enables better data interoperability and exchange between different healthcare providers and research institutions, to in future work towards a precision oncology program.

2. Building a connected system

Dataspace4Health not only focuses on two of the most important medical use cases in healthcare, it also pays attention to the legal foundation and uses European Regulation to address health data sharing in Luxembourg. The platform will help build a connected ecosystem by establishing a secure and efficient layer for data sharing across institutions, fostering collaboration and advancements.

Dataspace4Health represents a multi-million investment in the future of healthcare in Luxembourg.

This visionary project paves the way for secure and compliant health data exchange, ultimately leading to a healthier future for all." 

3. The Challenges 

The identified obstacles we face so far in this project are:

- Lack of EU regulations for secure Data Exchange:

The sensitivity nature of the health data is a great challenge to be taking into account with its lack of local, and EU regulations. The exchange of data across organizations is currently constrained by proprietary, non-transparent, non-interoperable technologies that do not provide the necessary level of trust. Therefore, aligning medical and political healthcare stakeholders to define the future of data exchange for Luxembourg based on an EU regulation will enable: use cases driven data space platform enabling easy deployment of new healthcare use cases and will provide the foundation in Luxembourg for Data Spaces in other verticals.

- Ecosystem of healthcare partners:

An obstacle encountered in promoting this project was to find the right key stakeholders that could work conjointly taking into account the legal framework of the project and to align our objective and vision. As NTT DATA Luxembourg has a great network and has been driving major innovative projects in the Healthcare sector, we capitalized on our network and knowledge of the local market to mobilize the relevant organizations, legal authorities and researchers to make this project a success.As each of the partners has its own motivation and interests, we had to build up a common objective/vision together, with the aim of revolutionizing the future of health and patient outcomes. Different backgrounds, ways of working in diverse industries and with research institutions can be challenging when it comes to the common deliverables. This challenge is intended to be mitigated by great leadership with the will to go forward together with a common vision. We use best practices of the agile way of working - regular communication, usage of the modern communication and collaboration tools, regular physical meetings in the locations of different partners. This is the good way to connect with the consortium all together, to learn from each other's experiences and strengths, fostering a deeper understanding and synergy within our collective efforts.

4. Specifically how your company's (technical) know-how contribute 

"NTT DATA Luxembourg is at the forefront of the Dataspace4Health project, aiming to transform healthcare through innovative and efficient data sharing across Europe. By enabling real-time access to critical information, we are empowering the healthcare ecosystem with the aim to enhance patient outcomes and deliver more personalized care.

With expertise in cloud-native technologies and healthcare solutions, we are building an ecosystem that has the potential to improve patient experiences and drive sustainable advancements in healthcare delivery. Our focus on innovation ensures that healthcare professionals can make data-driven decisions, resulting in smarter, faster, and more effective care. We're capitalizing on our trusted technology know-how driving the healthcare ecosystem to thrive towards a sustainable and resilient digital future. This project is in line with our Connected Economy Sustainability ambition, enabling health data to be shared in an ethical and trusted way.

We proved that we can not only provide the ICT services to our client, but also lead the business transformation of the whole industrial sectors in the country.

As leaders in DS4H, we are committed to shape the future of healthcare, where technology enhances both patient care and system sustainability." 

5. The effects brought about by this project, quantitatively 

The Social impact:

By 2050, one in four people in Europe and North America will be over the age of 65, leading to increased healthcare demands. The global economy could create 40 million new health-sector jobs by 2030, but there will still be a projected shortfall of 9.9 million physicians, nurses, and midwives globally, according to the World Health Organization. This highlights the need for significant structural changes in healthcare systems to remain sustainable and the importance of attracting, training, and retaining healthcare professionals to ensure their time is used effectively in patient care.

The integration of AI in healthcare has the potential to significantly enhance care outcomes, patient experience, and access to services by automating routine tasks and allowing professionals to focus more on patient care.

The Economic impact

Enhanced access to health data offers significant benefits not only within the healthcare sector but also economically. According to the European Commission, the European Health Data Space (European Health Data Space) is projected to save approximately €1 billion over a decade. These savings are anticipated to be evenly split, with half resulting from improved data exchange and the other half from the more effective use of data for research and innovation purposes. Dataspace4Health will also contribute towards the goal of EHDS by providing recommendations for Luxembourgish Government to implement local health data space in Luxembourg. The EHDS is designed to improve the EU’s ability to respond to health crises and future pandemics by ensuring that health data is readily available for analysis and decision-making.

The Healthcare impact

Focus on our 2 uses cases: Diabetes and Oncology

Diabetes - use case 1

Dataspace4Health contributes to the global targets for diabetes of the World Health Organization (WHO) to be achieved by 2030. These targets aim to improve the diagnosis, treatment, and management of diabetes worldwide. Specifically, ensuring that 80% of people with diabetes are diagnosed, 80% of those diagnosed have good control of their blood sugar levels, and 80% have good control of their blood pressure. Additionally, 60% of people with diabetes aged 40 years or older should receive statins to manage cholesterol levels, and 100% of people with type 1 diabetes should have access to affordable insulin and blood glucose self-monitoring. These efforts are part of a broader initiative to reduce the risk of diabetes and ensure equitable, comprehensive, affordable, and quality treatment and care for all individuals diagnosed with diabetes (“First-Ever Global Coverage Targets for Diabetes Adopted at the 75th World Health Assembly,” n.d.).

Furthermore, dataspaces play a crucial role in managing diabetes and achieving the UN's targets for reducing premature mortality from non-communicable diseases which is “by 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being”. AI is revolutionizing diabetes management by offering personalized, efficient, and proactive solutions across various domains. It personalizes treatment plans by predicting blood glucose levels and optimizing insulin dosages, enhances diagnostic accuracy through advanced imaging technologies, and improves real-time health monitoring with continuous glucose monitors. AI also develops predictive models to forecast diabetes onset and progression, aids in public health interventions by assessing risks, and customizes lifestyle and dietary recommendations. Additionally, AI supports clinical decision-making by providing data-driven treatment options and engages patients in self-management through personalized tools. These advancements promise improved health outcomes and quality of life for diabetes patients, emphasizing the need for continued research, data security, and interdisciplinary collaboration.

Oncology - use case 2

In 2023, the European Union saw approximately 2.74 million new cancer cases, a 2.3% increase from 2020. The most common cancers were breast (380,000 cases), colorectal (356,000 cases), prostate (330,000 cases), and lung (319,000 cases). Lung cancer remained the leading cause of cancer deaths, accounting for 19.5% of all cancer fatalities, followed by colorectal (12.3%), breast (7.5%), and pancreatic cancer (7.4%).

These statistics underscore the ongoing challenge of cancer in the EU and the need for continued efforts in prevention, early detection, and treatment (“Cancer Cases and Deaths on the Rise in the EU - European Commission” 2024). Predictive Cancer Patient Digital Twins (CPDTs) are virtual models designed to predict and personalize cancer treatment. With help of high-performance computing, artificial intelligence, and multi-scale modeling to simulate patient-specific disease progression and treatment responses, CPDTs aim to revolutionize cancer care by providing personalized treatment plans and enhancing patient outcomes. Key challenges include the need for extensive patient-specific data and the integration of diverse data types. Dataspace4Health enables collection, management and sharing of such data according local and European regulations." 

6. Your outlook on how this initiative will help solve other issues in the future. 

Patient Empowerment

In the future, patient empowerment will become a cornerstone of healthcare, enabling individuals to take an active role in managing their health. Patients will be provided with comprehensive information about their medical conditions and treatment options, allowing them to make informed decisions that align with their personal preferences and values.

This empowerment will extend beyond knowledge, fostering a sense of self-efficacy and confidence in their ability to influence healthy outcomes. Additionally, patients will be equipped with the necessary skills for self-monitoring and effective communication with healthcare providers, enhancing their ability to manage their health proactively. A supportive environment that respects patient rights and encourages participation in healthcare decisions will further strengthen this empowerment, leading to better adherence to treatment plans and improved health outcomes. Studies have shown that empowered patients are more likely to adhere to treatment plans, resulting in better health outcomes and higher satisfaction with care. 

Timely Access for Physicians and Care Homes

Timely access to patient data will be essential for healthcare providers to deliver effective and efficient care. Physicians and care homes will have immediate access to comprehensive patient histories, allowing them to prepare more thoroughly for consultations and ensure they are well-informed about the patient's medical background. This access will also facilitate early diagnosis of diseases, as healthcare providers will be able to identify patterns and symptoms more quickly, leading to timely interventions and better treatment outcomes.

Moreover, efficient data access will aid in the management of hospital resources, such as scheduling and bed allocation, optimizing the use of available resources and reducing wait times for patients. Overall, timely access to patient data will enhance the quality of care and improve patient satisfaction. For instance, nearly 93% of rural community health centers offer timely appointments, significantly improving access to care.

Enhanced Research Capabilities

Access to extensive healthcare data will significantly enhance research capabilities, driving innovation and improvements in patient care. Researchers will be able to analyze large datasets to uncover new insights, identify disease trends, and develop innovative treatments. This data-driven approach will support the development of evidence-based practices, ensuring that healthcare interventions are grounded in robust scientific evidence.

Enhanced data access will also facilitate collaboration among researchers, enabling more comprehensive studies and accelerating the pace of medical advancements. By leveraging vast amounts of healthcare data, researchers will discover biomarkers, develop new treatments, and ultimately improve patient outcomes. Building research capacity in healthcare will be essential for continuous improvement and innovation, ensuring that the healthcare system evolves to meet the changing needs of patients. For example, integrated models of research capacity building have shown significant improvements in research outcomes and collaboration.

Easy onboarding of new use cases

Once the data space is implemented, the onboarding of new use cases could be done very fast. The current dataspace ecosystem has the potential to be incredibly beneficial for a variety of diseases, including cardiovascular diseases and Parkinson. By leveraging large datasets, advanced analytics, and machine learning, we can gain deeper insights into these conditions, improve diagnostics, and personalize treatment plans.

For cardiovascular diseases, data from wearables, electronic health records, and genetic information can help in early detection and monitoring. For Parkinson’s, data from patient monitoring and clinical trials can aid in understanding disease progression and developing new therapies.

7. The current progress and local improvements. 

The project started at the end of February 2024 and is foreseen to last 2 years starting from then. During the last 7 months we have established our unique way of working with healthcare, research and policy-maker representatives.

We described and reviewed the existing processes for diabetic patients treated at Hôpitaux Robert Schuman and identified areas where (and how) the predictive model based on the digital twin in the future can help. We have initiated a clinical study, in order to be able to share retrospectively collected, anonymized data to the research partner to further train the predictive model.

Furthermore, we made inventory of healthcare data available by our partners and assessed the possibilities and challenges in sharing them. We are reviewing different regulations like GDPR, AI Act, Medical device regulation, Data act, Data Governance act etc. and drafting the minimal legal framework helping to define the legal base to enable us to implement this innovative approach in healthcare ecosystem in Luxembourg. Additionally, the national ethics committee process to submit clinical studies has been thoroughly reviewed and is in scope, with the aim to accelerate new clinical research in the future using data that can be shared in a secure way through the data space.

Furthermore, we are exploring technical tools to build the dataspaces incl. IOWN technology which one time will become a part of technical landscape of DS4H ecosystem. At the same time we are working with healthcare stakeholders - hospital doctors, nurses, diabetologists, pathologists [CB4] etc. and onboarding them on the project, i.e. explaining the concept and how it can help them in the future to improve the patient care. Our work helps to increase the common awareness of the healthcare and public sector in Luxembourg about advantages of using new technologies in their daily work, to understand better the laws and policies around health data exchange and how modern technology enable it in the compliant with regulations way.

In this project, it's the first time we are working not only with engineers, but with Legal and Field (Healthcare) specialists who have their own work packages in the project. It is a revolutionizing approach which can lead us to get the unique competitive advantage on the market in the future[CB5] .

And finally, we were able to get support from our Japanese, Spanish and Belgium colleagues for this project who actively participate in the events related to project presentation and promotion. Masaru Dobashi, Miki Kanno, Sara Gonzalez Grasa, Alberto Borrego Díez, Dmitry Etin, and other colleagues are supporting and contributing into our DS4H project. For example, in May 2024 we were happy to greet 14 of our colleagues from different NTT entities in Tech-X event in Luxembourg and together we won the 2nd place in the hackathon with the topic ""Gaia-X LLM Integration for Enhanced Experience"". It is a great success for the team which was organized 2 days before event and never worked together before. " 

8. Prospects for future actions.

 * about any value that could be returned to society. " 

"The data spaces ecosystem is aligned with the data economy what is the basic principle of Society 5.0 which is ""a human-centered society in which economic development and the resolution of social issues are compatible with each other through a highly integrated system of cyberspace and physical space.""

The application of data spaces extends beyond healthcare and can be effectively utilized in various other domains. Here are some examples of their use in agriculture, finance, and manufacturing.

Agriculture

In the agricultural sector, data spaces enable farmers to access comprehensive data on crops, weather conditions, and soil fertilizers. This integration of data helps farmers make informed decisions, leading to improved crop yields and sustainable farming practices. For instance, the modernization of agri-food supply chains through big data applications equips farmers with predictive capabilities necessary for optimizing water usage and maximizing crop yields. This transformation is crucial for addressing the challenges posed by climate change and demographic shifts. Data space will enable farmers to systematically access data and make more informed decisions. 

Finance

In the finance sector, data spaces will allow investors and financial institutions to access broader economic data. By sharing data across banks and financial authorities, stakeholders can gain insights into market trends, economic indicators, and investment opportunities. This enhanced data sharing fosters a more transparent and efficient financial ecosystem, enabling better risk management and investment strategies. The integration of artificial intelligence and big data in financial systems also supports the development of predictive models for market analysis and economic forecasting. Data spaces will enhance transparency in the financial making data as individual investors will also have chance to get data that is only accessible to big firms. This will enable individuals to make more informed decisions about their financial future. 

Manufacturing

In the manufacturing domain, data spaces facilitate the sharing of information among product manufacturers, suppliers, and technicians. This collaborative data environment enhances product development, quality control, and supply chain management. Technicians can access detailed data about products, leading to improved maintenance and innovation. The application of big data in manufacturing processes helps in optimizing production efficiency and reducing operational costs. This data-driven approach creates equal opportunities for all stakeholders by ensuring access to critical information and fostering innovation.

By leveraging data spaces, these sectors can significantly boost their data economies, leading to more informed decision-making and equitable opportunities for all participants. 

Conclusion

In conclusion, the Dataspace4Health (DS4H) project represents a significant step forward in transforming healthcare through innovative and secure data sharing. By leveraging AI and data-driven approaches, DS4H aims to improve patient outcomes, enhance the quality of life, and advance scientific knowledge and discovery. The project brings together a diverse ecosystem of partners, including hospitals, research organizations, and government agencies, to create a comprehensive health data exchange platform. This platform aims to facilitate better diagnosis, treatment, and prevention of diseases, particularly focusing on diabetes and cancer. Despite the challenges of data protection and regulatory compliance, DS4H is poised to revolutionize healthcare in Luxembourg and beyond, paving the way for a healthier future for all.