Background Health Literacy (HL) is the knowledge and competence to access, understand, appraise, and apply health information for health judgment. We analyze for the first time HL level of Catalonia’s population. Our objective was to assess HL of population in our area and to identify social determinants of HL in order to improve the strategies of the Healthcare Plan, aimed at establishing a person-centered system and reducing social inequalities in health. Methods This was a cross-sectional study based on the Health Survey for Catalonia (ESCA, Enquesta de Salut de Catalunya ), which included the 16 items of the European Health Literacy Survey Questionnaire (HLS-EU-Q16). The statements in the questionnaire cover three different health literacy domains: Health Care, Disease Prevention, and Health Promotion. HL was categorized in three levels: Sufficient, Problematic and Inadequate. Chi-square tests were performed to compare the percentages of subjects with adequate or inadequate HL across sociodemographic and health-related variables. Variables showing significant differences were included in a stepwise logistic regression to predict inadequate HL level. Results The questionnaire was administered to 2433 subjects aged between 15 and 98 years old (mean of 45.9 years, SD 18.0). Overall, 2059 subjects (84.6%) showed sufficient HL, 250 (10.3%) inadequate HL, and 124 (5.1%) problematic HL, with no significant differences between men and women ( p = 0.070). A logistic regression analysis showed that low health literacy is associated with a lower level of education (OR 2.08, CI 95% 1.32–3.28, p = 0.002), low socioeconomic status (OR 2.11, CI 95% 1.42–3.15, p <  0.001) and a physical limitation to perform everyday activities (OR 2.50, CI 95% 1.34–4.66, p = 0.004). We also found a more modest association with low physical activity, having a self-perceived chronic disorder and performing preventive activities. Conclusions Catalonia has a high percentage of subjects with sufficient HL. Education level, socioeconomic status and physical limitations were the factors with the strongest contribution to inadequate or problematic health literacy. Although these results are likely to be country-specific, the factors identified will allow policymakers of areas with similar socioeconomic profiles to identify groups with high risk of problematic or inadequate HL, which is essential for a successful patient-centered model of care.

ObjectivesPopulation-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.SettingsThe five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).ParticipantsResponsible teams for regional data management in the five ACT regions.Primary and secondary outcome measuresWe characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.ResultsThere was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.ConclusionsThe results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

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