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Using Ambulance Data for Violence Prevention

Technical Report

by Alex Sutherland, Lucy Strang, Martin Stepanek, Chris Giacomantonio, Adrian Boyle

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Research Questions

  1. Does ambulance data add potential value for injury surveillance, bringing new information over and above that already available?
  2. Could these data could be applied to violence prevention activities, and if so, how?

In spring 2015, the West Midlands Police received a Police Innovation Fund grant to undertake a 'proof of concept' evaluation of the utility of using ambulance data for violence prevention activities, to be conducted by RAND Europe. Similar to Emergency Department data utilised in the 'Cardiff Model' approach to violence prevention, ambulance data is thought to offer a new source of intelligence data for police and community safety/violence prevention partnerships. Such data may be able to help identify unknown patterns of violence, and from this contribute to solutions to prevent and/or reduce violence. This study investigates whether this data adds potential value for injury surveillance. That is, does it bring new information over and above that already available? Within that, there is an assessment of data quality in terms of completeness and, for example, the extent that the data sources overlap. Secondly, it scopes whether and if so, how, these data could be applied to violence prevention activities.

Key Findings

  • The study found that ambulance records contain substantial new information on violence, with between 66%-90% of ambulance incidents not found in police data. Therefore, police are not aware of the location of a substantial proportion of violent incidents.
  • The volume of ambulance call-outs for public violence, averaging 16 per day in the West Midlands, means that ambulance data can offer high volume data that is not typically recorded by the police or ED.
  • Because ambulance data is collected automatically and includes location data for each call, this data does not require substantial additional work to be collated and shared. This means that should ambulance data prove effective in reducing crime, it is easily scalable.

Table of Contents

  • Chapter One

    Summary

  • Chapter Two

    Introduction

  • Chapter Three

    Requirements for accessing ambulance data

  • Chapter Four

    Understanding the datasets

  • Chapter Five

    Process evaluation results

  • Chapter Six

    Comparing police, ambulance and ED data

  • Chapter Seven

    Conclusion

Research conducted by

The research described in this report was conducted by RAND Europe.

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