Driving Speeds in Urgent and Non-Urgent Ambulance Missions during Normal and Reduced Winter Speed Limit Periods—A Descriptive Study

Abstract

Objective: Most traffic research on emergency medical services (EMS) focuses on investigating the time saved with emergency response driving. Evidence regarding driving speed during non-urgent ambulance missions is lacking. In contrast, this descriptive study compared registered driving speeds to the road speed limit in urgent A-missions and non-urgent D-missions. Specifically, the study examined driving speeds during normal speed limits, periods of reduced winter speed limits, and speeding during non-urgent D-missions. Methods: Urgent A-missions and non-urgent D-missions were included. Registered ambulance locations and speed data from Pirkanmaa Hospital District, Finland between 1 January 2018 and 31 December 2018 were used. Ambulance locations were linked to OpenStreetMap digital road network data. The registered driving speed distribution was reported as quartiles by the effective road speed limit. Furthermore, the results during the normal speed limit and reduced winter speed limit periods were reported separately. Driving speeds in non-urgent missions were compared with current Finnish traffic violation legislation. Results: As expected, the urgent A-missions exceeded the speed limits during both the normal speed limit and reduced winter speed limit periods. On the smallest streets with speed limits of 30 km/h, the driving speeds in urgent missions were lower than the speed limit. The driving speeds in non-urgent D-missions were broadly similar throughout the whole year on high-speed roads, and mostly on lower speed limit roads. However, within the 30 km/h speed limits, the mean speed in non-urgent missions appeared to increase during the winter. One-fifth of the registered non-urgent D-missions were speeding. Conclusions: Speeding is common in urgent A-missions and non-urgent D-missions throughout the year. Stricter guidelines for EMS are needed to increase driving safety.

A scenario based approach to optimizing cost-effectiveness of physician-staffed Helicopter Emergency Medical Services compared to ground-based Emergency Medical Services in Finland

“…The service needs assessment forecast was developed utilizing a grid database, where Finland is divided into 1 × 1 km size squares. For each 1 km2 square, the following background variables were defined: 1) risk category classification [ 15 , 16 ], 2) location in relation to Finnish road network (road connections, length of roads in the grid, and highest speed limit 80 km/h) [ 17 ], 3) municipality, hospital district, and university hospital area, 4) permanently resident population, 5) number of EMS missions (including other than HEMS) classified by dispatch urgency and code, 6) estimated response time of a ground-unit to the grid’s center, using historical response times of missions by the same urgency, applying the Inverse Distance Weighting (IDW) interpolation method [ 18 ], 7) Driving time and distance from nearest base to closest road point to the grid center, and from this point to University hospital or large-scale emergency hospital [ 19 ], and 8) flight time and distance from bases to the grid center, and from this point to the nearest university hospital or large-scale emergency hospital by average 220 km/h airspeed based on information received from FinnHEMS. The service need forecast was evaluated for each patient group.…”

Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study

“…3 A study in Finland estimated that emergency vehicles travel 20%-25% faster than standard vehicles. 22 Although this study was conducted in a high-income country, given the lack of any other available evidence, we used the findings to guide our choice of values for the speed multiplier. We chose s = 0.6, 0.7, 0.8, 0.9 for a 40%, 30%, 20% and 10% proportion reduction in average transfer times with the ambulance, respectively.…”

Comparativo de Estratégias para Resposta a Emergências usando Redes Ad Hoc Veiculares e Computação em Névoa

“…As simulac ¸ões usam uma distribuic ¸ão normal tal que aproximadamente 95% dos veículos se mantém entre 80% e 120% do limite de velocidade. Ambulâncias andam cerca de 20 a 25% mais rápido que veículos comuns [Pappinen and Nordquist 2022]. Assim, nas simulac ¸ões, andam a aproximadamente 75 km/h quando não obstruídas.…”