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INDICATE will lay the foundations for the training and operation of an AI model implemented in intensive care units to support personalised medicine applications, data comparison between ICUs and preparedness for possible disasters.
The INDICATE project, which was launched on 2 December 2024, is a pioneering European initiative designed to improve the access to and exchange of data between intensive care units in Europe. INDICATE aims to advance patient-centred care and promote the ethical use, development and implementation of reliable AI models. In the coming years, INDICATE will collaborate with organisations in the European healthcare sector to improve patient outcomes and promote a data-driven approach to healthcare. Vall d'Hebron is one of the institutions participating in the project.
Clinical decision-making and innovation in ICUs currently face significant challenges due to data fragmentation, a lack of standardised data exchange agreements and an inadequate secure infrastructure. These barriers became evident during the early stages of the COVID-19 pandemic when even basic questions such as ‘how many patients requiring ventilator support have been admitted to the ICU?’ were difficult to answer. This situation hinders the development and implementation of AI models that are inclusive, diverse and have the potential to improve patient-centred medicine. INDICATE seeks to overcome these challenges and ensure that critical health data can be used in an ethical and responsible manner.
INDICATE aims to address these problems by establishing a secure federated infrastructure for standardised intensive care data. In this context, 'federated' means that the data analysis or AI training software sends the data directly to the intensive care unit rather than taking the data to the people doing the analysis. This ensures that patient data never leaves the hospital and that the people who use it never see the real health data, only the results they need. A federated approach is secure and, by design, promotes patient privacy.
The INDICATE project involves centres located all across Europe. Not only does this ensure that the available data reflects the diversity of patients in Europe in the short term, but it also ensures that this is reflected in the long term as the network grows. INDICATE will therefore form the basis for the training and operation of the AI model implemented in intensive care units to support personalised medicine applications, data comparison between ICUs and preparedness for possible disasters For example, INDICATE will facilitate the development of an AI model designed to predict bacterial infection in the bloodstream of newborns, which will be developed to improve the early recognition of this disease.
Dr Michel van Genderen, Erasmus MC in Rotterdam and INDICATE coordinator, explained that “with INDICATE we are building a cross-border collaboration in healthcare, where data can really make the difference in critical patient situations. We are setting a new standard in healthcare: secure access to data and the development and implementation of ethical AI as the norm. This paves the way for every ICU to benefit from the transformative power of AI and data-driven decision-making.”
Prof. Christian Jung MD of the Düsseldorf University Hospital (Germany) and co-coordinator of the INDICATE project added that “by linking data from many intensive care units in Europe, we help doctors make better decisions and contribute to a more resilient European healthcare system.”
Dr Ricard Ferrer, head of the Intensive Care Service at Vall d'Hebron University Hospital and head of the Shock, Organ Dysfunction and Resuscitation Group at Vall d'Hebron Research Institute (VHIR), stressed that “we are very pleased to form part of this consortium involving several of the main hospitals in Europe to—in a federated, anonymous and secure manner—carry out research with biomedical data to improve the treatment and prognosis of critical patients.”
More information: https://indicate-europe.eu/
The aim is to advance patient-centred care and promote the ethical use, development and implementation of reliable AI models.
Intensive Care Medicine, General Hospital
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