📋 Tender Overview
Its objective is to coordinate the use of AI solutions in the healthcare system ensuring their reliability usefulness humanization and universality. To this end a model of shared governance is established between the Ministry of Health and the Autonomous Communities.
The Minister of Health Monica Gracia during the Plenary of the Interterritorial Council of the National Health System. The Plenary of the Interterritorial Council of the National Health System (CISNS) has approved the Artificial Intelligence Strategy for the National Health System (eIASNS) a roadmap that consolidates the Ministry of Healths commitment to the digital transformation of the healthcare system through advanced technologies that reinforce equity quality and efficiency. The Strategy which is part of the IASNS Action Plan of the SNS Digital Health Strategy is based on a thorough analysis of the current state of implementation of these technologies. A diagnosis was developed through structured questionnaires and bilateral meetings with the autonomous communities allowing for precise identification of the maturity level of existing AI solutions in each territory. From this analysis five major objectives have been agreed upon: Establish a common and homogeneous vision of the role of artificial intelligence in the SNS which serves as a reference framework for its implementation at the national and regional levels. Develop unique and shared procedures for the identification classification and evaluation of AI solutions ensuring their technical clinical and ethical validation before their integration into the system. Create new structures services and specific roles to manage artificial intelligence in each autonomous community as well as at the state level under a collaborative governance model. Promote specialized training and the acquisition of skills in artificial intelligence for healthcare professionals and technicians involved in its development and use. Coordinate the implementation of specific high-value use cases for the SNS favoring 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 person-centered implementation; and universality designed so that the benefits of artificial intelligence reach all citizens under equitable conditions. Real applications and technological maturity The Artificial Intelligence Strategy for the National Health System recognizes the significant advancement of AI-based technologies in the healthcare field both internationally and within the SNS itself. It highlights that some applications are already consolidated in regular use while others are in emerging phases with great development potential. Among the most mature is image-assisted diagnosis whose algorithms allow for the detection of diseases such as breast or lung cancer with high precision sometimes 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 health have been approved reflecting their growing reliability. Virtual assistants and medical chatbots have also become widespread facilitating appointment management and bringing the Health System closer to its users as well as voice recognition for clinical transcriptions reducing administrative burden. Additionally AI in hospital management improves efficiency in shift planning bed allocation and admission prediction with increases of over 30% in some centers. On the other hand the Strategy identifies a set of emerging applications of great strategic value whose consolidation is considered a priority in the coming years. Among them are: Personalized medicine Robotic surgical assistants Early detection systems for chronic diseases Real-time remote monitoring The use of human digital twins. The Strategy also contemplates even more disruptive developments in the medium and long term such as voice diagnosis using digital biomarkers the creation of AI-managed hospitals or the total integration of AI in health planning and response to public health crises. Governance and common tools The governance model is based on collaborative leadership coordinated by the SNS Digital Health Commission and supported by a network of territorial technical and clinical references. This structure seeks to ensure homogeneous implementation the exchange of best practices and the joint development of pilot projects and common tools. The creation of specific AI governance units in health services is planned with multidisciplinary teams (clinical technological ethical and legal) responsible for evaluating and supervising solutions as well as specialized ethical committees in artificial intelligence applied to health as already exist in some autonomous communities that have served as a reference. The framework includes shared evaluation and validation tools to classify algorithms according to their risk clinical utility organizational impact and regulatory compliance in accordance with European regulations on AI and the ethical principles of the SNS. Furthermore 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 care impact economic efficiency and territorial equity. Training ethics and participation The implementation of artificial intelligence in the healthcare field requires more than technological advances: its success depends on the trust of professionals patients and citizens supported by three pillars -
