Spain Unveils National AI Strategy for Healthcare Transformation

In addition to the issue of cancer screenings, the extraordinary plenary session of the Interterritorial Council of the National Health System (CISNS) addressed in its meeting this Wednesday an essential issue for the development of the entire healthcare system, namely the Artificial Intelligence (AI) Strategy for the National Health System (eIASNS).

The new AI strategy is a roadmap aimed at the digital transformation of the healthcare system, ultimately oriented towards providing greater equity , quality, and efficiency.

The AI Strategy, developed jointly by the Ministry and the Autonomous Communities, is based on five objectives. The first is to establish a common and homogeneous vision of the role of artificial intelligence in the National Health System (NHS), which will serve as a framework for its implementation at the national and regional levels.

It also plans to develop unique and shared procedures for identifying AI solutions, proceeding with their technical, clinical, and ethical validation before their integration into the system.

The AI strategy will also create new structures and services to manage artificial intelligence in each autonomous community, as well as at the national level, under a collaborative governance model.

For healthcare professionals, the AI Strategy will be the tool for promoting specialized training and the acquisition of skills in artificial intelligence.

Finally, it will also be the system for coordinating the implementation of specific high-value use cases for the NHS, fostering mutual learning and interoperability between health services

The strategic objectives are structured around four guiding principles: reliability, which ensures that AI tools are safe, accurate, and transparent; utility, aimed at generating clinical, organizational, and social value; humanization, which guarantees a people-centered implementation; and universality, designed so that the benefits of artificial intelligence reach all citizens under equitable conditions.

Real-world applications of the AI Strategy

The AI Strategy for the National Health System recognizes the significant progress of AI-based technologies in the healthcare sector, both internationally and within the NHS itself.

It highlights that some applications are already well-established in routine use, while others are in emerging phases with great development potential.

Among the most mature is image-assisted diagnosis, whose algorithms allow for the highly accurate detection of diseases such as breast or lung cancer, in some cases surpassing the average diagnostic capacity of experts. In Europe, there are more than 180 AI algorithms in this area with CE marking obtained through a notified body, and in the USA, more than 500 AI algorithms in healthcare have been approved, reflecting their increasing reliability

Virtual assistants and medical chatbots have also become widespread, facilitating appointment management and bringing the healthcare system closer to its users, as well as voice recognition for clinical transcriptions, reducing the administrative burden. Furthermore, AI in hospital management improves efficiency in shift planning, bed allocation, and admission prediction, with increases exceeding 30% in some centers.

The AI Strategy also envisions even more disruptive developments in the medium and long term

On the other hand, the AI Strategy identifies a set of emerging applications ofgreat strategic value, whose consolidation is considered a priority in the coming years. These include: personalized medicine; robotic surgical assistants; early detection systems for chronic diseases; real-time remote monitoring; and the use of human digital twins (a virtual replica that is updated in real time with data from the physical world).

The AI Strategy also envisions even more disruptive developments in the medium and long term, such as voice-guided diagnosis using digital biomarkers, the creation of AI-managed hospitals, and the full integration of AI into healthcare planning and public health crisis response

The governance model is based on collaborative leadership, coordinated by the NHS Digital Health Commission and supported by a network of regional technical and clinical experts. This structure aims to ensure consistent implementation, the exchange of best practices, and the joint development of pilot projects and common tools.

The creation of specific AI governance units within health services is planned, with multidisciplinary teams (clinical, technological, ethical, and legal) responsible for evaluating and monitoring solutions, as well as ethics committees specializing in artificial intelligence applied to health, as already exist in some Autonomous Communities that have served as a model

The framework includes shared assessment and validation tools to classify algorithms according to their risk, clinical utility, organizational impact, and regulatory compliance, in line with European AI regulations and the NHS ethical principles.

In addition, the development of common technological infrastructures—secure data platforms, testing environments, algorithm registries, and interoperable repositories—will be promoted to facilitate the integration of AI into health information systems.

Finally, a system of indicators and continuous monitoring will be established to measure implementation, healthcare impact, economic efficiency, and territorial equity.

In the area of ​​training, priority will be given to the continuous and specialized training of all NHS staff—clinical, managerial, and administrative—through regulated and non-regulated programs, in collaboration with universities and professional bodies. These will address AI fundamentals, ethical and legal aspects, algorithm assessment and interpretation, and communication with patients in AI-assisted contexts.

All solutions must respect principles such as equity, transparency, explainability, non-discrimination, patient autonomy, and accountability in decision-making decisions. Regulatory oversight will also be strengthened regarding data protection, device security , and prior assessment of technologies, with a prominent role for the Spanish Agency for the Supervision of Artificial Intelligence (AESIA) and other regulatory bodies.

Finally, the active participation of patients, professionals, researchers, managers, developers, and the public in the design, validation, and implementation of AI solutions is promoted, thus fostering a collaborative approach. Taken together, these measures seek not only to boost technological innovation but also to consolidate a cultural shift in which AI is integrated as an ally of medical humanism and the social commitment of the healthcare system.

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(Featured image by Igor Omilaev via Unsplash)

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First published in diariofarma. A third-party contributor translated and adapted the article from the original. In case of discrepancy, the original will prevail.

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