Health Data Quality Skill Gaps and Training Needs Among European Health Data Stakeholders: Cross-Sectional Survey.

backgroundThe secondary use of health data is accelerating across Europe driven by growing demand for data-enabled research, innovation, and policymaking. The European Health Data Space (EHDS) establishes a regulatory framework to support this ecosystem, including Article 78, which mandates a data quality and utility labeling mechanism for datasets intended for reuse. Implementing this framework requires that data holders, data users, and health data access bodies possess sufficient skills, training, and organizational capacity to assess, document, and communicate data quality. However, little empirical evidence exists on whether European health data stakeholders currently possess these capabilities or how their needs differ across the 3 EHDS-defined roles.

objectiveThis study aimed to identify current skill gaps, training needs, and organizational readiness related to health data quality among European health data stakeholders within the context of the EHDS.

methodsA cross-sectional online survey was conducted between March 2024 and April 2024 using convenience sampling through the QUANTUM (Quality, Utility, and Maturity Measured; Developing a Data Quality and Utility Label for the European Health Data Space) consortium network, professional mailing lists, and health data communities. The survey targeted individuals involved in the secondary use of health data who identified as data holders, data users, or health data access bodies. The survey assessed 5 domains: stakeholder roles and data interaction, individual skills and experience, perceived challenges and skill gaps, organizational support and tools, and learning needs and preferences. Overall, 64 responses were collected from participants representing 44 institutions across 18 European countries.

resultsOverall, 82.8% (53/64; 95% CI 71.8%-90.1%) of respondents interacted with health data at least weekly, and 84.4% (54/64; 95% CI 73.6%-91.3%) rated data quality as moderately to absolutely critical for their work. Despite this, 87.5% (56/64; 95% CI 77.2%-93.8%) reported that poor data quality limited their effectiveness, with missing or inconsistent data identified as the most prevalent challenge. While 79.7% (51/64; 95% CI 67.4%-88.3%) reported prior experience with data quality tasks, key skill gaps were identified in applying data quality metrics, auditing and reporting, and metadata management. At the organizational level, only 15.6% (10/64; 95% CI 8.7%-26.6%) reported clearly defined data quality roles, and 68.8% (44/64; 95% CI 56.6%-78.8%) lacked a dedicated data quality manager or team.

conclusionsThis study provides an empirical assessment of data quality skills and organizational readiness across the 3 EHDS-defined stakeholder groups. The findings highlight that practical experience alone does not ensure data quality competence and that structural deficits, particularly unclear roles and limited governance, constrain effective data quality management. The results offer a role-specific, evidence-based road map for capacity-building efforts essential to the successful implementation of the EHDS Article 78 data quality and utility labeling framework. This evidence underscores the urgent need for coordinated capacity building to ensure successful EHDS data quality implementation.