Periodic Reporting for period 1 - QUANTUM (Quality, Utility and Maturity Measured; Developing a Data Quality and Utility Label for HealthData@EU)
Periodo di rendicontazione: 2024-01-01 al 2025-06-30
The QUANTUM project (Quality, Utility and Maturity Measured: Developing a Data Quality and Utility Label for HealthData@EU) supports the implementation of the European Health Data Space (EHDS) regulation, specifically addressing Article 78 of the EHDS Regulation proposal, which mandates data holders to label health datasets to show their quality and utility for secondary use of health data.
The QUANTUM project`s core objective is to create a common label system for Europe that guarantees the quality and utility of datasets for secondary purposes such as research, innovation, policy making and regulation.
By establishing a clear labelling specification, QUANTUM aims to create a transparent and trustworthy mechanism that enables data holders to flag the quality and usefulness of their datasets while allowing researchers, innovators, and regulators to figure out if the dataset may fit their purposes. This will foster greater confidence and openness in the cross-border exchange of health data across the EU.
The QUANTUM project`s core objective is to create a common label system for Europe that guarantees the quality and utility of datasets for secondary purposes such as research, innovation, policy making and regulation.
By establishing a clear labelling specification, QUANTUM aims to create a transparent and trustworthy mechanism that enables data holders to flag the quality and usefulness of their datasets while allowing researchers, innovators, and regulators to figure out if the dataset may fit their purposes. This will foster greater confidence and openness in the cross-border exchange of health data across the EU.
In its initial phase, the project has focused on building a shared understanding of data quality and utility (fit for use). This has involved: defining core data quality dimensions and conducting Delphi surveys and nominal group sessions to build stakeholder consensus on the metrics for each of the identified dimensions.
A maturity model for data holders has also been developed to assess organizational readiness and capability in managing health data and health data quality. Based on the previous, a labelling tool v.01 has been designed and piloted in a small-scale pilot. This tool will enable data holders to assess their datasets according to the label specification. Feedback from this small-scale pilot has informed improvements, and QUANTUM label 0.2 was delivered for a mid-scale pilot started in year 2 of the project.
To support capacity building, the project has assessed the training needs of various stakeholders. This has led to the creation of an educational curriculum (so named QUANTUM Academy), with an upcoming course designed to equip professionals with the necessary knowledge and skills to assess the data quality label and ultimately, improve datasets quality and fit for use. The course will be tested and made available in year 3 of the project.
Main achievements to date include:
-Consensus on data quality dimensions, metrics, value ranges and thresholds.
-Development of a data holder maturity model.
-Creation of an operational tool for labelling.
-Completion of an initial pilot testing of tool
-Inception and first round of the mid-scale implementation of the quality and utility label specification in QUANTUM data holders
A maturity model for data holders has also been developed to assess organizational readiness and capability in managing health data and health data quality. Based on the previous, a labelling tool v.01 has been designed and piloted in a small-scale pilot. This tool will enable data holders to assess their datasets according to the label specification. Feedback from this small-scale pilot has informed improvements, and QUANTUM label 0.2 was delivered for a mid-scale pilot started in year 2 of the project.
To support capacity building, the project has assessed the training needs of various stakeholders. This has led to the creation of an educational curriculum (so named QUANTUM Academy), with an upcoming course designed to equip professionals with the necessary knowledge and skills to assess the data quality label and ultimately, improve datasets quality and fit for use. The course will be tested and made available in year 3 of the project.
Main achievements to date include:
-Consensus on data quality dimensions, metrics, value ranges and thresholds.
-Development of a data holder maturity model.
-Creation of an operational tool for labelling.
-Completion of an initial pilot testing of tool
-Inception and first round of the mid-scale implementation of the quality and utility label specification in QUANTUM data holders
Complying with Article 78 requires the label to be able to describe the quality and utility of a wide range of datasets, including electronic medical records, population registries, biosamples, imaging data, wearable device outputs, and data from omics research or clinical trials. The label must also be technically simple to implement, ensuring accessibility even for data holders with limited infrastructure or lower organisational maturity. In addition, the regulation outlines that the label shall provide information on various elements (metadata), such as data documentation, technical quality, data quality management, coverage assessment, access and provision details, and data modifications. These elements span three conceptual dimensions: technical data quality, potential utility (fit-for-use), and organisational maturity. Integrating these diverse dimensions into a single coherent label represents both a conceptual and technical challenge.
The QUANTUM project addresses these challenges by developing a tailored specification for data quality and utility. Recognising the absence of a framework that is comprehensive across data categories and fully aligned with Article 78, QUANTUM has achieved a formal consensus with key stakeholders. Grounded in existing data quality frameworks, notably TEHDAS, EMA and EOSC, this process has resulted in a broadly accepted set of dimensions and metrics, which now forms the basis of the QUANTUM label specification.
The QUANTUM project addresses these challenges by developing a tailored specification for data quality and utility. Recognising the absence of a framework that is comprehensive across data categories and fully aligned with Article 78, QUANTUM has achieved a formal consensus with key stakeholders. Grounded in existing data quality frameworks, notably TEHDAS, EMA and EOSC, this process has resulted in a broadly accepted set of dimensions and metrics, which now forms the basis of the QUANTUM label specification.