Digitalisation is the future of healthcare

The term digital health encompasses e-health, mhealth, telehealth, electronic health records, remote monitoring, connected devices, digital therapeutics and more. It means embracing data, artificial intelligence (AI) and machine learning to improve healthcare.

Many forms of digital health proved their worth during the COVID-19 crisis, for example telehealth measures allowing health services to be maintained, disease surveillance and mechanisms supporting medicines supply chains.

However, these represent only a fraction of the potential of digital health. System-wide digitalisation will revolutionise all future healthcare – powering the integrated, people-centric, outcomes-based health systems we need.

It will help

• patients, carers and the public to engage better with health services and researchers, and to manage their own health better
• the workforce to make better and faster decisions about patient care
• payers to allocate resources more efficiently
• innovators deliver treatments that meet people’s needs and generate value across the system
• health systems monitor, learn and adapt – making them more resilient.

We strongly support digitalisation within our industry and the health sector as a whole. Together we must lay the right foundations now and we believe certain overarching principles should underpin all forms of digital health:

• It should enhance (not merely replace) healthcare. ‘Digital where possible – human when needed’ is one way to look at this
• It must be trusted by all stakeholders
• It must not widen inequities via any form of digital divide, and hence ensuring digital health literacy and enablement is vital.

Key challenges: fragmentation and incentives

Digitalisation in the health sector is held back not by a lack of data, but by its fragmentation and lack of interoperability.

In fact, health systems produce huge amounts of data from various sources, such as electronic health records (where these exist), disease registries, post-authorisation medicines surveillance systems, reimbursement systems, mobile health apps and other wearable technologies. However, most health data is not put to work – around 80% remains untapped. Where it can be used, its use is often too limited to a single purpose, hence its potential is not realised.

This is partly because of well-recognised technical issues that can be overcome, namely:

• data collection systems are often not interoperable, meaning they cannot ‘talk’ to each other. The COVID-19 pandemic starkly highlighted this, since in many cases it was not even possible to compare the number of deaths between EU countries because of differences in data collection and classification
• they vary in quality, and/or
• there is a lack of suitable infrastructure and legislative framework for sharing, especially cross-border and on an EU level.

More fundamentally, the bodies that own or control data are currently not incentivised to share these, and the relevant data-sharing regulations are ambiguous or inhibitory. For example, variable interpretations of the EU General Data Protection Regulation (GDPR) result in different regulatory environments, some that foster digital healthcare (e.g. Estonia) and others present greater barriers (e.g. Germany).

Moreover, while many systems record data on healthcare consumption and activities, there is a lack of comprehensive measurement of health outcomes that can be compared across health systems (See Outcomes).

The digital transformation needs EU-wide political leadership and collaboration between patients, the public, the health workforce and technical specialists.

EFPIA applauds the European Commission’s efforts to create an EU policy environment that unlocks the value of the digital and data economy across all sectors.

The two priorities are clear: health data has a huge potential to improve patient care, health systems and research and provides an opportunity we cannot afford to miss, but suitable infrastructures and clear governance with accountability are needed to ensure its availability for different purposes, ensuring privacy and security, as well as quality.

EU-wide priorities

 

Governance

Healthcare decisions can be critical and European citizens must feel that their data is secure and being used with a positive healthcare intent. Indeed, EU citizens generally support digital health, with 80% agreeing to share their health data if privacy and security are ensured.

Therefore, Europe needs a legal and ethical governance framework for digital health that is fit-for-purpose and trusted by all parties. It should balance safety and data protection in context with the benefits for the individual and the health system.

EFPIA is committed to working with all stakeholders to develop this, and have published specific recommendations to this end.

• The overarching principles should be people-centricity and societal benefit: if citizens own and control their own data, and health actors are incentivised to improve health outcomes, then data sharing will be normalised. The GDPR legislation already provides the governance framework, but implementation mechanisms are lacking.
• Citizens must have access to their data and remain in control of it. They must be free to choose the purposes for which their data are used; potential recipients in healthcare and research should be authorised subject to ongoing review. Data-sharing consent needs to be harmonised across the EU, based on a broad consent for reuse for scientific research purposes, with the option to opt-out.
• The governance framework should support the use of data for research and policymaking purposes (secondary uses), as well as for healthcare (primary use). Clarification and harmonisation of the rules in this regard is necessary. We also believe that data governance requirements should be proportionate to the risk associated with the intended use of the data.
• Overall we support the guiding principles underpinning the European Open Science Cloud, namely that data should be ‘as open as possible and as closed as necessary’, and be ‘FAIR’, i.e. Findable, Accessible, Interoperable, and Re-usable.

Artificial intelligence

AI can bring significant opportunities for keeping people healthy, improving care, saving lives and saving money for healthcare systems.

EFPIA fully embraces the benefits that AI-powered solutions could bring to patients, healthcare professionals and health systems. Our vision is to maximise its potential to develop novel therapies and approaches to identify, treat and care for patients more efficiently, while preserving patient safety and privacy. However, further collaboration is needed to identify and address potential or unforeseen gaps in the current existing regulations, frameworks, and best practices.

We have published principles and recommendations to guide the designing of an AI legislative framework in the EFPIA Position Paper on AI.

EFPIA and its members are committed expert partners in digital transformation, including via the following multi-stakeholder initiatives.


Europe needs a health data coalition to build public understanding of the value of health data, and enhance confidence in how data are collected and used. The European Patients Forum is leading a vital initiative called Data Saves Lives. This platform will enable dialogue between key stakeholders to promote responsible use of health data and to facilitate societal understanding and will contribute to a change in attitudes to data-sharing

Industry: partnering for digital transformation

The European Health and Evidence Data Network (EHDEN) project was launched to unlock the potential of real-world clinical data across Europe, overcoming the challenges that currently limit its use. It will develop a federated, harmonised EU-wide network for real-world data, with over 100 millon health records standardised according to a common data model. It will establish a self-sustaining open science collaboration supporting academia, industry, regulators, payers, governments and NGOs and the EHDEN Academy to train all stakeholders.

Dragon (RapiD and SecuRe AI enhAnced DiaGnosis, Precision Medicine and Patient EmpOwerment Centered Decision Support System for Coronavirus PaNdemics) will use AI and machine learning to deliver a decision support system for precise coronavirus diagnosis using computed tomography (CT) scanning. It also aims to be able to better predict the outcomes of patients, and to empower patients and citizens as partners in helping to better diagnose and treat COVID-19.

A slow walking speed is associated with greater mortality, morbidity, cognitive decline, dementia, and fall risk. As the population ages, the number of people experiencing mobility challenges is expected to rise. Mobilise-D will develop a comprehensive system to monitor and evaluate people’s gait based on digital technologies, including sensors worn on the body. The project focuses on conditions which often affect mobility, namely chronic obstructive pulmonary disease, Parkinson’s disease, multiple sclerosis, hip fracture recovery, and congestive heart failure. The results will help to improve the accurate assessment of daily life mobility, thereby contributing to improved and more personalised care.

IDEA-FAST aims to identify digital endpoints that provide reliable, objective and sensitive evaluation of fatigue, sleep, activities of daily life, disability and health-related-quality of life for people with neurodegenerative diseases (Parkinson’s disease and Huntington’s disease) or immune-mediated inflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, primary Sjögren’s syndrome or Inflammatory bowel disease).

Case studies