Improving the chances of surviving an out-of-hospital cardiac arrest by using AI to support ambulance service call centre staff.
People who suffer out-of-hospital cardiac arrest have very high mortality. The number of deaths could be reduced if cardiopulmonary resuscitation could be given within three to five minutes of the onset of the cardiac arrest. Every minute of delay reduces the chances of survival by 10%. It is crucial, therefore, that ambulance service call centre staff recognise out-of-hospital cardiac arrest so that they can dispatch an ambulance quickly and provide instructions over the telephone to bystanders. However, the evidence suggests that at least 25% of out-of-hospital cardiac arrests are not recognised. The introduction of an artificial intelligence (AI) solution could improve recognition and reduce premature mortality.
The project team will adapt an existing Corti AI platform, which has been piloted in Copenhagen, for use within the Welsh Ambulance Service (WAST). The assurance activities will contribute to the development of a real-world Body of Knowledge for assurance cases of AI in critical sectors.
The team has started work on understanding and specifying the operating environment for the Corti AI system and determining safety assurance requirements at the clinical system level. For this they are interviewing healthcare staff and will analyse the data from these interviews to report on the definition of the operational design domain and clinical system level safety assurance requirements.
Data collection requirements are also being outlined, along with technical details of transferring this data to the Corti system. The team has also identified opportunities to engage with key stakeholders in order to contribute to standardisation and best practice for the safety assurance and regulation of AI products.
Papers and presentations
- EURO and UK NAVIGATOR (2020) International Academies of Emergency Dispatch peer-reviewed oral conference presentation: Assuring safe AI in ambulance response.
- ASSIST included in an oral presentation at REASON (2021) UKRI Trustworthy Autonomous Systems Node in Resilience, online workshop with project partners: Pre-hospital and ambulance services experiences and opportunities with autonomous systems.