Ascensión Doñate-Martínez

The European Health Data Space (EHDS) promotes health data sharing and secondary use across Europe. The QUANTUM project focuses on labelling data quality (DQ), utility, and maturity to support EU-wide standards within this context. This study examines current DQ assessment practices in European Data Holder institutions to inform the design of a labelling tool for the EHDS. The study explored institutional practices for DQ assurance and assessment through a survey of EU-wide Data Holders and a literature search on open-source health DQ tools with potential for labelling. The survey targeted QUANTUM partners and external institutions, addressing DQ practices and tools. The literature review followed PRISMA guidelines and combined PubMed, AI-based queries, and known sources. We obtained survey responses from 27 Institutions across 13 European countries. The results showed a high variety and heterogeneity in DQ practices and tools used, including in-house developed tools, open-source tools, commercial products, and manual procedures. Most practices allowed customization of DQ dimensions and export of DQ analyses. The systematic review identified 66 DQ tools, 53% specific to data types such as electronic health records, omics or imaging, and 47% general-purpose. The diverse DQ institutional practices and tools emphasize the need for an interoperable self-assessment DQ labelling tool that guides the measurement and completion of consolidated metrics aligned with the EHDS regulations. Based on these findings, the QUANTUM project is developing this tool to support DQ labelling of Data Holders’ datasets candidate to publication at EU Health Data Access Bodies.

Background: Coherence across sites in multicenter datasets is one substantial data quality dimension for reliable health data reuse, as unexpected heterogeneity in data can lead to biases in data analyses and suboptimal generalization of results. Objective: This work aims to characterize and label the data coherence across sites in the first European multicenter dataset for cancer prevention in people and early detection among the homeless population in Europe: coadapting and implementing the health navigator model. This dataset emerged to enable research to address disparities in health challenges and health care access due to barriers such as unstable housing, limited resources, and social stigma in people experiencing homelessness. Methods: The dataset comprises 652 cases: 142 from Austria, 158 from Greece, 197 from Spain, and 155 from the United Kingdom. All participants fit classifications from the European Typology of Homelessness and Housing Exclusion. This longitudinal study collected questionnaires at baseline, after 4 weeks, and at the end of the intervention. The 180-question survey covered sociodemographic data, overall health, mental health, empowerment, and interpersonal communication. Data variability was assessed using information theory and geometric methods to analyze discrepancies in distributions and completeness across the dataset. Results: Substantial variability was observed among the 4 pilot countries, both in the overall analysis and within specific domains. In particular, measures of health care empowerment, quality of life, and interpersonal communication demonstrated the greatest discrepancies among pilot sites, with the exception of the health domain. Notably, Spain exhibited the most pronounced differences, characterized by a high number of missing values related to interpersonal communication and the use of health care services. Conclusions: Health data may be comparable across the 4 countries; however, substantial differences were observed in the other questionnaires, requiring independent, country-specific analyses. This study underscores the heterogeneity among people experiencing homelessness and the critical need for data quality assessments to inform future research and policymaking in this field.

Background: People experiencing homelessness (PEH) face major barriers to accessing healthcare, including cancer preventive services, which results in increased cancer morbidity and mortality. However, tailored integrated care interventions addressing these disparities are scarce. Methods: Using a qualitative, participatory approach, seven focus group discussions were conducted with 15 PEH and 41 health and social care professionals in Austria, Greece, Spain, and the UK. Data were thematically analysed using a framework based on ten core components of navigation interventions. Results: Collaborative discussions led to a consensus on the Health Navigator Model (HNM), designed to improve cancer prevention for PEH. This model introduces “health navigators” from health and social care backgrounds to identify health needs, raise cancer awareness, coordinate healthcare access, and provide practical support. Thematic analysis ensured consistency across countries, shaping a person-centred approach. Comprehensive training and supervision were identified as critical for the effectiveness of the HNM. Conclusion: The co-design approach allowed PEH and professionals to actively shape the intervention, addressing gaps in cancer prevention. The HNM offers a structured, internationally consistent model that could bridge access gaps in cancer care for PEH. Further research using implementation science frameworks is needed to evaluate its effectiveness in real-world settings.

Background: People experiencing homelessness (PEH) face significant health disparities and systemic barriers to healthcare, elevating their risk for cancer and other chronic diseases. To tackle PEHs’ challenges in accessing cancer preventive care, the CANCERLESS project implemented the Health Navigator Model (HNM)—a person-centered intervention that utilizes trained Health Navigators to provide tailored support and facilitate service access. Recognizing housing as a key determinant of health, this analysis assessed changes in housing status associated with participation in the HNM among CANCERLESS participants in Austria, Greece, Spain, and the UK. Methods: This was a secondary analysis of cross-national data collected during a single-arm interventional study. Of 652 enrolled PEH, 277 (42.5%) completed the HNM intervention follow-up and were included in the analysis. Changes in housing status from baseline to follow-up were categorized using the European Typology of Homelessness and Housing Exclusion (ETHOS) and treated as an ordered outcome. Descriptive statistics were complemented by a cumulative link mixed model with a participant random intercept to estimate the association between time (follow-up vs. baseline) and housing transitions among completers, adjusting for age, residence/legal status, and daily smoking. Results: Participants had a mean age of 47.4 (SD 13.8), primarily identified as male (64.1%), reported upper secondary education (33.9%), and were from Western European countries (39.7%), with varying housing situations. Among intervention completers, time (follow-up vs. baseline) was associated with higher odds of being in a higher ETHOS category (OR = 1.49, 95% CI = 1.02–2.20, p = 0.042), consistent with a modest improvement in housing status. Larger estimates were observed among migrants without legal documents (OR = 24.13, 95% CI = 6.41–90.89, p < 0.001), while daily smoking was associated with lower odds (OR = 0.33, 95% CI = 0.11–0.96, p = 0.041); other residence status categories were not statistically significant. Conclusions: Suggesting that tailored, navigation-based models, such as the HNM, may be linked to improved housing stability for PEH, these findings can inform piloting and context-aligned integration of the HNM within public health strategies as an alternative approach to address the complex, interconnected health and social needs of PEH. However, the lack of a comparison group and high attrition limit the results’ conclusiveness, and future evaluations should aim to include assessments of housing-associated contextual factors.

BACKGROUND Coherence across sites in multicenter datasets is one substantial data quality dimension for reliable health data reuse, as unexpected heterogeneity in data can lead to biases in data analyses and suboptimal generalization of results. OBJECTIVE This work aims to characterize and label the data coherence across sites in the first European multicenter dataset for cancer prevention in people and early detection among the homeless population in Europe: coadapting and implementing the health navigator model. This dataset emerged to enable research to address disparities in health challenges and health care access due to barriers such as unstable housing, limited resources, and social stigma in people experiencing homelessness. METHODS The dataset comprises 652 cases: 142 from Austria, 158 from Greece, 197 from Spain, and 155 from the United Kingdom. All participants fit classifications from the European Typology of Homelessness and Housing Exclusion. This longitudinal study collected questionnaires at baseline, after 4 weeks, and at the end of the intervention. The 180-question survey covered sociodemographic data, overall health, mental health, empowerment, and interpersonal communication. Data variability was assessed using information theory and geometric methods to analyze discrepancies in distributions and completeness across the dataset. RESULTS Substantial variability was observed among the 4 pilot countries, both in the overall analysis and within specific domains. In particular, measures of health care empowerment, quality of life, and interpersonal communication demonstrated the greatest discrepancies among pilot sites, with the exception of the health domain. Notably, Spain exhibited the most pronounced differences, characterized by a high number of missing values related to interpersonal communication and the use of health care services. CONCLUSIONS Health data may be comparable across the 4 countries; however, substantial differences were observed in the other questionnaires, requiring independent, country-specific analyses. This study underscores the heterogeneity among people experiencing homelessness and the critical need for data quality assessments to inform future research and policymaking in this field.

Background and objective People experiencing homelessness (PEH) face significant health challenges and disparities in healthcare access due to barriers such as unstable housing, limited resources, and social stigma. In response, the European Union has initiated efforts to address these disparities. The CANCERLESS project, part of this initiative, has created the first European multi-centre dataset for cancer prevention in PEH. This work aims to evaluate and describe the heterogeneity of PEH across pilot sites and to provide data quality metrics for reliable future research. Methods The dataset comprises 652 cases: 142 from Vienna, 158 from Athens and Thessaloniki, 197 from Madrid, and 155 from the United Kingdom. All participants fit classifications from the European Typology of Homelessness and Housing Exclusion. This longitudinal study collected questionnaires at baseline, four weeks, and at the end of the intervention. The 180-question survey covered socio-demographic data, overall health, mental health, empowerment, and interpersonal communication. Data variability was assessed using information theory and geometric methods to analyse discrepancies in distributions and completeness across the dataset. Results Significant variability was found among the four pilot countries, both overall and within specific sections, except for the health section. Madrid showed the largest discrepancies, with a high number of missing values related to interpersonal communication and healthcare service use. Conclusion Health data may be comparable across the four countries, but further analysis should account for location-specific differences. This study underscores the heterogeneity among PEH and the critical need for data quality assessments to inform future research and policymaking in this field.

The increasing prevalence of complex chronic diseases in the population over 65 years of age is causing a major impact on health systems. This study aims to explore the needs and preferences of the multimorbid patient and carers to improve the palliative care received. The perspective of professionals who work with this profile of patients was also taken into account. A qualitative study was conducted using semi-structured interviews with open-ended questions. Separate topic guides were developed for patients, careers and health professionals. We included 12 patients, 11 caregivers and 16 health professionals in Spain. The results showed multiple unmet needs of patients and families/caregivers, including feelings of uncertainty, a sense of fear, low awareness and knowledge about palliative care in non-malignant settings, and a desire to improve physical, psychosocial and financial status. A consistent lack of specialized psychosocial care for both patients and caregivers was expressed and professionals highlighted the need for holistic needs assessment and effective and early referral pathways to palliative care. There is a lack of institutional support for multimorbid older patients in need of palliative care and important barriers need to be addressed by health systems to face the significant increase in these patients.