"Data, artificial intelligence and collaboration are key to moving towards a more efficient healthcare system"
Keys to drive effective digital health: data, artificial intelligence and collaboration
The digital transformation of the healthcare system is being driven by a combination of technologies, collaborative models and new value-focused approaches. In this context, healthcare is evolving towards a more intelligent, connected and results-oriented model, in which data and artificial intelligence play a key role.
Expert analysis of the healthcare, technological and industrial ecosystem identifies three key levers to accelerate this transition:
- Data spaces.
- Applied artificial intelligence.
- And open innovation ecosystems.
A study that has been published in the eBook "Digital Transformation of Health". In addition to the TECNALIA team (experts in Health and Digital), leading organisations and professionals, such as Julio Mayol (Scientific Director of IdISSC); Pedro Carrascal (Patient Organisations Platform); Izabel Alfany (CEO EIT Health Spain); Roberto Bilbao (BIOEF); María Luaces (San Carlos Clinical Hospital); Javier Elola, Mª Luz López-Carrasco and Ignacio Ayerdi (IMAS Foundation); Pablo Díez Villanueva (La Princesa University Hospital); Julián Pérez Villacastín (San Carlos Clinical Hospital); Ion Arocena (ASEBIO) and Pablo Crespo (FENIN), have participated in this study.
From data to value generation in health
One of today’s main challenges is how to turn the increased volume of data available in the healthcare system into useful, reliable and actionable decisions. Although there are large amounts of information, there are still barriers, such as fragmentation, lack of interoperability or difficulty in integrating clinical and research data.
- Overcoming these limitations will make it possible to move towards personalised health models, in which data is not only managed, but transformed into knowledge that improves care processes and clinical outcomes.
- Likewise, the development of national and European health data spaces is positioned as a key element to share information securely and efficiently, facilitating research and the development of new solutions.
Artificial intelligence and digital twins: new capabilities for the healthcare system
Artificial intelligence is consolidating its position as one of the main levers of transformation, not only in areas such as diagnostics and monitoring, but also in the development of organisational and biological digital twins, capable of simulating scenarios and optimising decision-making.
These technologies address the complexity of healthcare systems, characterised by their non-linear nature and the influence of the human factor, by providing tools that help optimise planning, efficiency and quality of care.
However, their adoption requires key issues to be addressed, such as the explainability of the models, the robustness of the systems and their validation in real environments, which are essential in order to build trust among healthcare professionals.
Trust and integration, critical elements for adoption
The effective integration of digital solutions in clinical practice requires these tools to be useful, intuitive and aligned with care flows, avoiding additional burden on professionals.
- In this respect, the involvement of clinicians and end-users from the early stages of development is identified as a key factor in order to ensure that the solutions address real needs and are effectively integrated into the system.
- Furthermore, the explainability of artificial intelligence emerges as a critical element to overcome the perception of a "black box" and facilitate adoption, enabling users to understand how and why certain recommendations or decisions are generated.
Open innovation and collaboration to scale solutions
The transformation of the healthcare system also requires an approach based on the collaboration of all agents in the ecosystem: technology centres, industry, hospitals, administrations and patient associations. This open innovation model enables solutions with real impact to be generated, combining skills and knowledge to address complex challenges and move forward in the development of technologies with practical applications.
One of the challenges identified is the need to overcome fragmentation and knowledge "silos", fostering more cross-cutting environments that facilitate the transfer and scaling up of innovation.
From innovation to impact: the challenge of scalability
Beyond technological development, one of the main challenges is getting innovative solutions implemented and scaled up in the healthcare system.
To do so, it is essential to:
- Clearly define the value of the solutions in terms of health outcomes, efficiency and patient experience.
- Ensure their integration into care processes.
- Promote models that facilitate their adoption, including value-based purchasing mechanisms.
It is also important to avoid creating additional complexity, opting for solutions that integrate naturally and provide measurable benefits from an early stage.
Towards a more sustainable, smarter and patient-centred health system
The move towards digital health involves not only the incorporation of new technologies, but also a cultural and organisational change to take full advantage of their potential.
The aim is to evolve towards a system that is capable of:
- Anticipating the needs of patients
- Offering a more personalised and efficient service
- Increasing the sustainability of the healthcare system
In this scenario, the combination of data, artificial intelligence and collaboration is positioned as the driving force to build a new generation of technological solutions with a real impact on society.
Download the eBook of the sector and discover the existing challenges of digital transformation in the healthcare sector.