Linking road casualty and clinical data to assess the effectiveness of mobile safety enforcement cameras: a before and after study

OBJECTIVES To use police STATS19 road casualty data and accident and emergency and in-patient information to estimate the impact of mobile safety cameras on the cost of treating individuals injured in road traffic collisions. DESIGN A data-matching and costing exercise to link casualty and clinical information in a 'before' and 'after' study of 56 mobile safety cameras. SETTING The Northumbria Police Force area of the UK covering six local authority districts. PARTICIPANTS Slight, serious and fatal casualties involved in road traffic collisions at mobile camera sites in the case-study area between April 2001-March 2003 and April 2004-March 2006. PRIMARY AND SECONDARY OUTCOME MEASURES Changes in the number and severity of casualties at the mobile camera sites between the 'before' and 'after' period that can be attributed to mobile safety camera activity, and any impacts these changes had on the 'cost of treatment saved' by the secondary healthcare service in the case-study area. RESULTS Using tariff values for accident and emergency and In-patient Health Resource Groups, the impacts of the cameras in terms of the 'cost of treatment saved' are in the range £12 500-£15 000 per annum. However, inconsistencies between databases resulted in approximately one-third of the casualties not being matched successfully in the clinical databases. The number of closed fractures requiring investigations, treatment and follow-up care reduced considerably, although this was offset by an increase in head injury contusions and open fractures that require high-cost investigations and extensive in-patient care. CONCLUSIONS Road safety cameras could have a significant impact in terms of 'cost of treatment saved'. However, it is argued that investigating the impacts of road safety measures in the future should be based on Fully Bayesian techniques as they can produce more reliable estimates of the effects of regression to mean and general trends in casualty statistics.