The Norwegian SME Headroom LifeScience is the developer of next-generation simulation technologies. In the proposed RIA project, we will, together with European Emergency Medical Service (EMS) centres, universities and technology developing small and large enterprises, develop and demonstrate AI-based tools to support EMS telecommunicators. When a citizen calls the official European emergency number, 1-1-2, they expect prompt, professional, and accurate help. The primary job of an EMS telecommunicator is to convey an interview that ensures structured dissemination for determining ambulance responses and pre-arrival instructions, e.g. cardiopulmonary resuscitation (CPR), as quickly as possible. Often the situation is classified as critical and, due to the inherent ambiguous nature of human conversation, it might be difficult for the caller to communicate an adequately detailed timeline of events and symptoms. This in turn makes it very difficult for the telecommunicator to correctly identify time-critical incidents such as cardiac arrest, stroke or other incidents that needs urgent treatment. For every minute, where a patient is not being treated for a cardiac arrest, chances of survival decreases by 10%. Today, most EMS telecommunicators are only supported by simple tools such as tree chart-based questionnaires, where a yes/no will lead to a new question. Moreover, education and training of EMS telecommunicators differ significantly from EMS centre to EMS centre. In the proposed RIA project, the consortium will develop two AI-based tools: 1) a real-time telecommunicator decision support tool, and 2) an EMS training simulator. The development of both tools is uniquely facilitated by EMS call and output data available from the EMS consortium partners. Hence, during the project, EMS call data will be safely extracted, labelled and made available for machine learning, and thus provide the basis for the AI-based tools.
Project leader: Arne Hansson Rannestad
Institution: HEADROOM LIFE SCIENCE AS