title: Can routinely collected ambulance data about assaults contribute to reduction in community violence?
abstract: BACKGROUND
  The 'law of spatiotemporal concentrations of events' introduced major preventative shifts in policing communities. 'Hotspots' are at the forefront of these developments yet somewhat understudied in emergency medicine. Furthermore, little is known about interagency 'data-crossover', despite some developments through the Cardiff Model. Can police-ED interagency data-sharing be used to reduce community-violence using a hotspots methodology?
  
  
  METHODS
  12-month (2012) descriptive study and analysis of spatiotemporal clusters of police and emergency calls for service using hotspots methodology and assessing the degree of incident overlap. 3775 violent crime incidents and 775 assault incidents analysed using spatiotemporal clustering with k-means++ algorithm and Spearman's rho.
  
  
  RESULTS
  Spatiotemporal location of calls for services to the police and the ambulance service are equally highly concentrated in a small number of geographical areas, primarily within intra-agency hotspots (33% and 53%, respectively) but across agencies' hotspots as well (25% and 15%, respectively). Datasets are statistically correlated with one another at the 0.57 and 0.34 levels, with 50% overlap when adjusted for the number of hotspots. At least one in every two police hotspots does not have an ambulance hotspot overlapping with it, suggesting half of assault spatiotemporal concentrations are unknown to the police. Data further suggest that more severely injured patients, as estimated by transfer to hospital, tend to be injured in the places with the highest number of police-recorded crimes.
  
  
  CONCLUSIONS
  A hotspots approach to sharing data circumvents the problem of disclosing person-identifiable data between different agencies. Practically, at least half of ambulance hotspots are unknown to the police; if causal, it suggests that data sharing leads to both reduced community violence by way of prevention (such as through anticipatory patrols or problem-oriented policing), particularly of more severe assaults, and improved efficiency of resource deployment.
authors: Institute of Criminology, University of Cambridge, Cambridge, UK Institute of Criminology, Hebrew University, Jerusalem, Israel.
authors: Barak
authors: B
authors: Ariel
authors: Institute of Criminology, University of Cambridge, Cambridge, UK.
authors: Cristobal
authors: C
authors: Weinborn
authors: Emergency Department, Addenbrooke's Hospital Cambridge University Hospitals NHS Foundation Trust, Cambridge, Cambridgeshire, UK.
authors: Adrian
authors: A
authors: Boyle
mesh_terms: D000465:Algorithms; D000552:Ambulances; D016000:Cluster Analysis; D003299:Cooperative Behavior; D003625:Data Collection / Q000379:methods*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D004739:England; D006801:Humans; D016495:Police; D014754:Violence / Q000517:prevention & control* / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000517:prevention & control*
keywords: effectiveness; emergency ambulance systems, effectiveness; emergency department; methods; violence