Faculty of Nursing and Groupe de recherche et d'intervention en promotion de la santé (GRIPSUL), Université Laval, Québec, Canada G1K 7P4. Michel.Oneill@fsi.ulaval.ca
Ever since their beginning in 1986, Healthy Cities projects all over the world have been confronted with the issue of evaluation. However, after 20 years, many key dilemmas constantly reappear, people often looking for a kind of 'magic' list of universally applicable indicators to evaluate these initiatives. In this article we address five questions, allowing to illustrate the evaluative dilemmas the Healthy Communities movement is confronted with: Why evaluate Healthy Cities? What should be evaluated? Evaluate for who? Who should undertake the evaluation? How should the evaluation be performed? We conclude by formulating three recommendations in order to stimulate exchanges and debate. Our argument is based on a recent thorough analysis of the evaluative literature pertaining to the Healthy Cities movement, as well as on two decades of reflection on and involvement with this issue locally, nationally and internationally.
INTRODUCTION: Data on the survival of all incident cases collected by population-based cancer registries make it possible to evaluate the overall performance of diagnostic and therapeutic actions on cancer in those populations. EUROCARE-3 is the third round of the EUROCARE project, the largest cancer registry population based collaborative study on survival in European cancer patients. The EUROCARE-3 study analysed the survival of cancer patients diagnosed from 1990 to 1994 and followed-up to 1999. Sixty-seven cancer registries of 22 European countries characterised by differing health systems participated in the study. This paper includes essays providing brief overviews of the state and evolution of the health systems of the considered countries and comments on the relation between cancer survival in Europe and some European macro-economic and health system indicators, in the 1990s. OVERVIEW OF THE EUROPEAN HEALTH SYSTEMS: The European health systems underwent a great deal of reorganisation in the last decade; a general tendency being to facilitate expanding involvement of the private sector in health care, a process which occurred mainly in the eastern countries (i.e. the Czech Republic, Estonia, Poland, Slovakia and Slovenia). In contrast, organisational changes in the northern European countries (i.e. Denmark, Iceland, Finland and Sweden) tended to confirm the established public sector systems. Other countries, including the UK and some southern European countries (i.e. England, Scotland, Wales, Malta and Italy) have reduced the public role while the systems remain basically public, at least at present. Our findings clearly suggest that cancer survival (all cancer combined) is related to macro-economic variables such as the gross domestic product (GDP), the total national (public and private) expenditure on health (TNEH) and the total public expenditure on health (TPEH). We found, however, that survival is related to wealth (GDP), but only up to a certain level, after which survival continues to be related to the level of health investment (both TNEH and TPEH). According to the Organisation for Economic Co-operation and Development (OECD), the TNEH increased during the 1990s in all EUROCARE-3 countries, while the ratio of TPEH to TNEH reduced in all countries except Portugal. CONCLUSIONS: Cancer survival depends on the widespread application of effective diagnosis and treatment modalities, but our enquiry suggests that the availability of these depends on macro-economic determinants, including health and public health investment. Analysis of the relationship between health system organisation and cancer outcome is complicated and requires more information than is at present available. To describe cancer and cancer management in Europe, the European Cancer Health Indicator Project (EUROCHIP) has proposed a list of indicators that have to be adopted to evaluate the effects on outcome of proposed health system modifications.
Geographic access to emergency treatment remains an important public policy concern as rural emergency medical systems respond to various pressures to centralize services. Geographical Information Systems (GIS) are effective tools to determine what proportion of a given population is adequately served by existing or proposed service distributions.
This study compares 2 GIS approaches to determining whether recent standards of emergency care access established by the British Columbia Ministry of Health Services are being met in Northern British Columbia. In particular, we compare results obtained using the more commonly used straight-line, or "as the crow flies," method with those obtained using a more sophisticated method that estimates travel time using digitally referenced road network data.
Both methods reveal that provincial standards of emergency access are not being met in Northern British Columbia.
In terms of comparing the 2 approaches, the network technique indicated a lower level of access and was more accurate in identifying populations residing inside and outside the "golden hour" of emergency care.
