How Europe is transforming big data into better health
Europe faces rising health challenges due to demographic changes, an increase in communicable diseases, an inefficient R&D process in the biomedical research domain and an increase in disease complexity, at least according to the Medical Sciences Committee of Science Europe.
Tackling health challenges demands an approach that requires an integration of multi-layered health information and an elaborate ecosystem. What is that approach? Big data.
In its latest report, Science Europe consolidated the outcomes of a two-day workshop co-hosted with the Italian National Institute for Nuclear Physics. Ongoing initiatives aimed at crafting a health big data ecosystem were showcased to help participants actively engage in discussions on how to develop such a health big data ecosystem in Europe.
Participants recognized that tackling Europe’s big health challenges needs a more systemic approach. Such an approach requires combining multiple health-related dimensions represented by big data from the molecular level to the integration of information related to individual environments and lifestyles.
It was also recognized that the main challenge for transformation of data into knowledge to improve health at the individual and population levels requires new analytical tools to discover novel relationships and patterns in a very heterogeneous data set.
Developing such an ecosystem in Europe relies on data sharing between multiple stakeholders, from public and private organizations involved in biomedical R&D to other disciplines (for example ICT, social sciences) that must put citizens and patients at its center.
Challenges (and solutions) for big data integration
Leveraging big data represents an opportunity to advance different fields across the biomedical sciences and health care industries including personalized medicine, systems biology, clinical research, drug discovery, drug development and public health.
Five challenges were identified from the participants:
1. Health-related data are fragmented across multiple and unconnected data sources (patient registries, bio-banks, social networks, and others).
2. There is no clear code of practice for data sharing. Data are stored in databases that belong to multiple institutions and stakeholders across the biomedical research and healthcare fields.
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3. The prevailing biomedical R&D model is segmented into basic, preclinical and clinical research silos. This ‘compartmentalization’ of the biomedical R&D and health care data chain, with value expected for the citizen/patient as a passive end-user, is a major hurdle to a data-sharing culture.
4. There is as yet no clear code of practice to ensure personal privacy while preserving openness in data sharing.
5. Current funding and career appraisal systems for biomedical researchers mainly recognize investigator-driven research. Mechanisms recognizing collaborative inter-disciplinary networks are in their infancy.
But recommendations to these challenges were offered.
Legal: Introduce appropriate legal and ethical frameworks to support data-sharing while developing appropriate security and oversight measures to reduce the risk of personal data loss (for example the European Data Protection Regulation). Big data presents other challenges with respect to ownership and liability that will need to be resolved.
Society: Increase citizen and patient involvement in the management and processing of their own health data and restore public trust in science (such as health data co-operatives).
Organization: Develop codes of conduct and research practices that define rigorous quality control mechanisms for all aspects of data handling, from collection and annotation through to storage and sharing between organizations. Develop funding opportunities for collaborative research networks and develop recognition and reward mechanisms for data sharing activities by individual researchers, especially in relation to career progression.
Investigator: Develop pilot experiments to showcase evidence-based benefits of sharing data for researchers from the public and private sectors.
The future of big data in health
Harnessing the potential of big data represents an opportunity to transform biomedical science, leading to new discoveries and better health care for the European citizen, with the attendant economic benefits that this brings.
There is already much activity in Europe within the arena that is directly or indirectly related to big data. Before proceeding further it would be sensible to map this landscape to understand what is already being done, where there are gaps, and where there are opportunities to potentially add value.
Skin Analytics wins NHSX award for AI skin cancer tool
An artificial intelligence-driven tool that identifies skin cancers has received an award from NHSX, the NHS England and Department of Health and Social Care's initiative to bring technology into the UK's national health system.
NHSX has granted the Artificial Intelligence in Health and Care Award to DERM, an AI solution that can identify 11 types of skin lesion.
Developed by Skin Analytics, DERM analyses images of skin lesions using algorithms. Within primary care, Skin Analytics will be used as an additional tool to help doctors with their decision making.
In secondary care, it enables AI telehealth hubs to support dermatologists with triage, directing patients to the right next step. This will help speed up diagnosis, and patients with benign skin lesions can be identified earlier, redirecting them away from dermatology departments that are at full capacity due to the COVID-19 backlog.
Cancer Research has called the impact of the pandemic on cancer services "devastating", with a 42% drop in the number of people starting cancer treatment after screening.
DERM is already in use at University Hospitals Birmingham and Mid and South Essex Health & Care Partnership, where it has led to a significant reduction in unnecessary referrals to hospital.
Now NHSX have granted it the Phase 4 AI in Health and Care Award, making DERM available to clinicians across the country. Overall this award makes £140 million available over four years to accelerate the use of artificial intelligence technologies which meet the aims of the NHS Long Term Plan.
Dr Lucy Thomas, Consultant Dermatologist at Chelsea & Westminster Hospital, said: “Skin Analytics’ receipt of this award is great news for the NHS and dermatology departments. It will allow us to gather real-world data to demonstrate the benefits of AI on patient pathways and workforce challenges.
"Like many services, dermatology has severe backlogs due to the COVID-19 pandemic. This award couldn't have come at a better time to aid recovery and give us more time with the patients most in need of our help.”