To what extent has a systems thinking approach been applied to understand motor vehicle crashes involving ambulances? A systematic review of risk factors and characteristics

Abstract

Motor vehicle crashes account for the largest proportion of workplace fatalities among paramedics in developed countries. Systems thinking is one approach that is popular when seeking to understand and manage complex road safety issues; however, it has not been applied to ambulance crashes. A systematic literature review was conducted to examine factors associated with motor vehicle crashes involving ambulances, and the extent to which systems thinking has been applied in this area. Crash factors were categorised using the Accident Mapping technique (AcciMap) (based on six hierarchical levels ranging from government to the road environment) and then synthesised according to whether they were crash/injury crash risk factors or characteristics. Of the 24 included studies, most only reported factors associated with the driver and their immediate environment (n = 23). The most commonly identified factors were intersection location, emergency use of the ambulance (lights and sirens operational) and non-use of restraints (all associated with increased risk of crash or injury crash). Two-thirds of studies were at risk of bias. Given the prominence of lower-level factors associated with road users, vehicles, and the road environment, it is concluded that systems thinking approaches would be beneficial to understand ambulance crashes, particularly for higher level system factors. Further research is recommended to i) examine the potential contribution of factors and their interactions that go beyond the driver and their immediate environment and ii) validate the current findings based on the low number of studies and their lack of methodological rigour in examining driver, vehicle and environmental factors. The development of a crash data collection and reporting system in line with system thinking principles is recommended as a first step to support the identification and systemic analysis of contributory factors across the entire sociotechnical system.