Google AI for Social Impact: The Use of AI to Code Ambulance Data for Suicide Prevention

  • Lubman, Dan (Primary Chief Investigator (PCI))
  • Scott, Debbie (Chief Investigator (CI))
  • Buntine, Wray (Chief Investigator (CI))
  • Matthews, Sharon (Chief Investigator (CI))

Project: Research

Project Details

Project Description

Ambulances are typically the first point of contact with someone who is suicidal. Ambulance clinical records are an important and rich data source, containing details of the nature and background to the attendance, the location of the event, and the clinical outcome. For more than 20 years and in partnership with Ambulance Victoria, Turning Point has been providing a Victorian alcohol, illicit and pharmaceutical drug surveillance system using coded paramedic clinical data. This world-first surveillance system has recently been expanded to include reporting of national data in partnership with jurisdictional ambulance services, and there is an opportunity to apply the same methodology to suicidal behaviour in these datasets.
However, the time and resources needed to code additional suicide-related attendances is prohibitive without significant ongoing funding. We propose using AI to allow us to also code national ambulance data that will establish a cost-effective model that could be adopted globally.
Effective start/end date22/07/1930/04/23


  • Suicide prevention
  • Mental health
  • alcohol and other drugs
  • artificial intelligence