Developing a European urban health indicator system: results of EURO-URHIS 1.

Introduction: More than half of the world's population now live in cities, including over 70% in Europe. Cities bring opportunities but can be unhealthy places to live. The poorest urban dwellers live in the worst environments and are at the greatest risk of poor health outcomes. EURO-URHIS 1 set out to compile a cross-EU inventory of member states use of measures of urban health in order to support policymakers and improve public health policy. Following a literature review to define terms and find an appropriate model to guide urban health research, EURO-URHIS Urban Areas in all EU member states except Luxembourg, as well as Croatia, Turkey, Macedonia, Iceland and Norway, were defined and selected in collaboration with project partners. Following piloting of the survey tool, a the EURO-URHIS 45 data collection tool was sent out to contacts in all countries with identified EUA's, asking for data on 45 Urban Health Indicators (UHI) and 10 other indicators. 60 questionnaires were received from 30 countries, giving information on local health indicator availability, definitions and sources. Telephone interviews were also conducted with 14 respondents about their knowledge of sources of urban health data and barriers or problems experienced when collecting the data. Most participants had little problem identifying the sources of data, though some found that data was not always routinely recorded and was held by diverse sources or not at local level. Some participants found the data collection instrument to not be user-friendly and with UHI definitions that were sometimes unclear. However, the work has demonstrated that urban health and its measurement is of major relevance and importance for Public Health across Europe. The current study has constructed an initial system of European UHIs to meet the objectives of the project, but has also clearly demonstrated that further development work is required. The importance and value of examining UHIs has been confirmed, and the scene has been set for further studies on this topic.

Mosaic segmentation, COPD and CHF multimorbidity and hospital admission costs: a clinical linkage study.

BACKGROUND: How multimorbidity and socio-economic factors influence healthcare costs is unknown. Geo-demographic profiling system, Mosaic, which adds to socio-economic factors, provides the potential for an investigation of the relationship with multimorbidity, and their influence on healthcare costs. METHODS: Using chronic obstructive pulmonary disease (COPD) and chronic heart failure (CHF) registers from 53 general practices for a population aged 40 years and over in Stoke-on-Trent, England (N = 10,113), were linked to hospital admissions data and Healthcare Resource Groups as a measure of hospital cost (2007-09). Eleven Mosaic groups were linked on the basis of individual patients' post codes. RESULTS: The COPD and CHF multimorbid group (n = 763) had the highest proportion with at least one hospital admission in the 3-year time period (n = 550, 72%), compared with the index COPD (56%) and CHF (66%) groups. Multimorbid patients had significantly higher mean costs for hospital admission (£4896) compared with the index COPD (£2769) or CHF (£3876). The associations between multimorbid groups and hospital admission costs compared with index groups varied by different Mosaic groups. CONCLUSIONS: CHF and COPD multimorbidity is associated with high costs, and average hospital admission costs vary by Mosaic segmentation. Multimorbidity and Mosaic provide an innovative basis for developing and targeting healthcare interventions in high-hospital-cost patients.