Development and implementation of a geographical area categorisation method with targeted performance indicators for nationwide EMS in Finland

Abstract Background In Finland, hospital districts (HD) are required by law to determine the level and availability of Emergency Medical Services (EMS) for each 1-km2 sized area (cell) within their administrative area. The cells are currently categorised into five risk categories based on the predicted number of missions. Methodological defects and insufficient instructions have led to incomparability between EMS services. The aim of this study was to describe a new, nationwide method for categorising the cells, analyse EMS response time data and describe possible differences in mission profiles between the new risk category areas. Methods National databases of EMS missions, population and buildings were combined with an existing nationwide 1-km2 hexagon-shaped cell grid. The cells were categorised into four groups, based on the Finnish Environment Institute’s (FEI) national definition of urban and rural areas, population and historical EMS mission density within each cell. The EMS mission profiles of the cell categories were compared using risk ratios with confidence intervals in 12 mission groups. Results In total, 87.3% of the population lives and 87.5% of missions took place in core or other urban areas, which covered only 4.7% of the HDs’ surface area. Trauma mission incidence per 1000 inhabitants was higher in core urban areas (42.2) than in other urban (24.2) or dispersed settlement areas (24.6). The results were similar for non-trauma missions (134.8, 93.2 and 92.2, respectively). Each cell category had a characteristic mission profile. High-energy trauma missions and cardiac problems were more common in rural and uninhabited cells, while violence, intoxication and non-specific problems dominated in urban areas. Conclusion The proposed area categories and grid-based data collection appear to be a useful method for evaluating EMS demand and availability in different parts of the country for statistical purposes. Due to a similar rural/urban area definition, the method might also be usable for comparison between the Nordic countries.