Advancing tools to promote health equity across European Union regions : The EURO-HEALTHY project

Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement. Under the EURO-HEALTHY project, tools combining the technical elements of multi-criteria value models and the social elements of participatory processes were developed to measure health in multiple dimensions and to inform policies. The flagship tool is the Population Health Index (PHI), a multidimensional measure that evaluates health from the lens of equity in health determinants and health outcomes, further divided into sub-indices. Foresight tools for policy analysis were also developed, namely: (1) scenarios of future patterns of population health in Europe in 2030, combining group elicitation with the Extreme-World method and (2) a multi-criteria evaluation framework informing policy appraisal (case study of Lisbon). Finally, a WebGIS was built to map and communicate the results to wider audiences. The Population Health Index was applied to all European Union (EU) regions, indicating which regions are lagging behind and where investments are most needed to close the health gap. Three scenarios for 2030 were produced - (1) the 'Failing Europe' scenario (worst case/increasing inequalities), (2) the 'Sustainable Prosperity' scenario (best case/decreasing inequalities) and (3) the 'Being Stuck' scenario (the EU and Member States maintain the status quo). Finally, the policy appraisal exercise conducted in Lisbon illustrates which policies have higher potential to improve health and how their feasibility can change according to different scenarios. The article makes a theoretical and practical contribution to the field of population health. Theoretically, it contributes to the conceptualisation of health in a broader sense by advancing a model able to integrate multiple aspects of health, including health outcomes and multisectoral determinants. Empirically, the model and tools are closely tied to what is measurable when using the EU context but offering opportunities to be upscaled to other settings

Anwendungsgebiete und Limitierungen der amtlichen Statistik für die regionale Versorgungsforschung. Ein Diskussionsbeitrag der AOK Nordost am Beispiel der koronaren Herzkrankheit.

Regionale Analysen chronischer Erkrankungen in Abrechnungsdaten von Krankenkassen können einen entscheidenden Beitrag dazu leisten, zukünftige Versorgungsstrukturen bedarfsgerecht zu planen. Hierbei sind neben den Abrechnungsdaten selbst auch die Daten der amtlichen Statistik von zentraler Bedeutung: Erst die Analyse des Zusammenhangs zwischen Erkrankungslast und der demografischen und sozio-ökonomischen Zusammensetzung des Wohnortes erlaubt Rückschlüsse darüber, wie sich die Erkrankungslast in Zukunft entwickeln wird. Derzeit können die Daten der amtlichen Statistik allerdings aufgrund der maximalen räumlichen Gliederungstiefe bis zur Gemeindeebene nicht ihr volles Potenzial entfalten. Dieser Beitrag verfolgt mehrere Ziele: (i) Am Beispiel der koronaren Herzkrankheit unter den Versicherten der AOK Nordost in den Ländern Berlin, Brandenburg und Mecklenburg- Vorpommern soll die Verwendung von Daten der amtlichen Statistik beispielhaft vorgestellt werden, (ii) die daraus entstehenden Implikationen für die zukünftige Bedarfsplanung sollen erläutert werden und (iii) die derzeitigen Limitierungen von Daten der amtlichen Statistik sollen diskutiert und Anforderungen an diese Daten aus Sicht der Versorgungsforschung vorgestellt werden

Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany

Abstract Background Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost. Methods To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag–York–Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics. Results The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45–64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations. Conclusion Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation