Case 3: Data Space for Federated Prediction of Acute Heart Failure Risk

In the context of cardiovascular research, it is essential to be able to analyze real clinical data without compromising patient privacy.

This use case allows sharing data that have been validated in a federated network through the execution of a predictive risk model for patients with acute heart failure.

Targets

Comply with the governance defined within the data space ecosystem.

Analyze and manage the data according to the common data model (CDM). Within the framework of the DataTools4Heart project, the dataset is converted into a fast, interoperable format for healthcare (FHIR).

Ensure the quality of the generated data so that it can be shared within the data space.

Publish the data in the data space component catalog so that potential users can explore and use them.

Data consumers

Healthcare professionals: will have access to both the data and the predictive model to optimize workflows and hospital organization.

Researchers from the VHIR Cardiology Department: will be responsible for developing and validating the model. They will also be able to use the same dataset in the future to address new challenges and improve patient care within the cardiology department.

Researchers: will benefit from both the use of data and the predictive models generated. The federated network developed in DataTools4Heart will also be used in two other European projects: AI4HF (Grant Agreement ID: 101080430) and DVPS (recently funded under the HORIZON-CL4-2024-HUMAN-03 call).

Companies and developers: will be able to validate their solutions using a high-quality dataset generated in a secure and interoperable environment.

Case 1: Health Outcomes and European Health Data Space

This case demonstrates how patient-provided data can be used to deliver more personalized and effective care. The goal is to make better decisions, tailor care to each individual’s needs, and share information securely between hospitals and healthcare centers.

More information
Dues persones revisant dades a l'ordinador

Case 2: Sharing Synthetic Data Using AI

This case demonstrates how artificial data can be created to mimic real patient data for training and testing health algorithms, ensuring privacy and facilitating collaboration between hospitals and researchers.

More information

Subscribe to our newsletters and be a part of Vall d'Hebron Campus

CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

The acceptance of these terms implies that you give your consent to the processing of your personal data for the provision of the services you request through this portal and, if applicable, to carry out the necessary procedures with the administrations or public entities involved in the processing. You may exercise the mentioned rights by writing to web@vallhebron.cat, clearly indicating in the subject line “Exercise of LOPD rights”.
Responsible entity: Vall d’Hebron University Hospital (Catalan Institute of Health).
Purpose: Subscription to the Vall d’Hebron Barcelona Hospital Campus newsletter, where you will receive news, activities, and relevant information.
Legal basis: Consent of the data subject.
Data sharing: If applicable, with VHIR. No other data transfers are foreseen. No international transfer of personal data is foreseen.
Rights: Access, rectification, deletion, and data portability, as well as restriction and objection to its processing. The user may revoke their consent at any time.
Source: The data subject.
Additional information: Additional information can be found at https://hospital.vallhebron.com/es/politica-de-proteccion-de-datos.