Using Open AI (OAI) technologies in healthcare seamlessly aligns with the OAD concept. Open healthcare datasets, as a crucial component of this concept, enable the training of adaptable AI models within secure environments. This not only enhances prediction accuracy but also fosters transparency in algorithms, collaboration, and equitable healthcare provision. The OAD concept promotes the open exchange of information, and in the context of healthcare, it ensures that the benefits of AI-driven improvements in diagnosis, personalized treatment, and clinical predictions are accessible to all while safeguarding the confidentiality of sensitive medical data.

Committing to OAD principles, exemplified by the concept, establishes a critical foundation for advancing healthcare through transparent information exchange. This philosophy finds resonance in the transformative landscape shaped by open health data initiatives. Notable international examples include Medical Information Mart for Intensive Care (MIMIC-IV),2 OpenEHR,3 Health Data Research UK (HDR UK),4 and the Cancer Genome Atlas (TCGA).5 MIMIC-III is a vast repository of de-identified critical care records from Beth Israel Deaconess Medical Center, facilitating the development of healthcare machine learning algorithms. If we put the focus on Europe, the European Health Data Space (EHDS)6 serves as a crucial initiative within the European Union, designed to enable secure cross-border sharing of health data, enhance healthcare quality, promote medical research and innovation, facilitate cross-border healthcare services, and empower patients with greater control over their health information. Its impact on open data in the health context promises to be substantial, as it fosters collaboration, research, and innovation while ensuring data privacy and security, ultimately advancing healthcare outcomes across Europe.

Open health data globally fosters collaboration, research, and innovation while ensuring data privacy. Spain's initiatives notably embody this commitment, shaping substantial advancements in healthcare outcomes. Spain's National Health System is creating a data platform and services, aligning with Digital Europe Programme and European Health Data Space goals to build a cohesive European data space for AI assimilation. Notably, this initiative transcends primary utility, deliberately incorporating secondary use with the explicit aim of enhancing and fortifying open data initiatives.7 Across Spanish regions, strategic directives from Public Foundations for Health Innovation and Research actively promote biomedical big data research. Focused on areas like medical imaging and clinical data, the overarching goal is to advance personalized medicine, enhancing patient care and sustaining the public healthcare system economically. At the same time, there are several private experiences from databases such as SANITAS, HM Hospitals group and the University Hospital Clínic of Barcelona, supporting the OAD and the development of machine learning algorithms in healthcare.8 These initiatives are in consonant with the worldwide imperative to expedite research concentrating on COVID-19, driven by the European Society of Intensive Care Medicine (ESICM) Data Sharing Initiative and the Swiss Federal Institute of Technology (ETH) Zürich.

Focusing on intensive care data in Spain offers a unique opportunity. Establishing an open, collaborative repository for the intensive care medical community could unlock vast medical knowledge. Given the current circumstances, the primary aim is clear: engage regions in collaboration with national scientific associations to construct a collaborative OAD repository. The repository would accelerate state-of-the-art digital solutions, cultivating insights for critically ill patients in Spain. Its goal would be to refine diagnostic accuracy and customize treatment protocols for ICU patients, streamlining operational processes. In response to urgent imperatives, cutting-edge technologies like Big Data and Artificial Intelligence have enabled predictive models, anticipating medical responses. These technologies also would allow performance comparisons with other open databases, fostering a dynamic community centered around ICU data in various regions of Spain, advancing the overall understanding and treatment of critically ill patients.

Conclusively, integrating OAI technologies with open data principles, advanced technologies, and ethical governance in ICUs signifies a transformative initiative with broad healthcare implications. This holistic approach not only revolutionizes patient care but positions intensive care as a leader in shaping a healthier future. By embracing the potential of Big Data, Artificial Intelligence, and Open AI within a framework of responsible data management, we are poised to expedite medical insights, refine treatments, and ultimately enhance outcomes for critically ill patients. This OAD-driven transformation underscores our commitment to medical excellence and ethical considerations, calling for collective engagement to propel the field of intensive care into a new era of innovation and patient-centered care. Furthermore, these principles serve to foster a sense of community, leading to more efficient collaboration, which in turn helps eliminate biases and promotes more equitable healthcare delivery.

The authors declare that they have not received any financial support.

The authors declare that they have no conflict of interest.