Artificial Intelligence AI

Artificial Intelligence & Emergency services: saving lives on the phone

Detecting out-of-hospital cardiac arrest using artificial intelligence: Report on results of EENA/Corti project now available.

Out-of-hospital cardiac arrest is one of the leading causes of death both in Europe and worldwide. When suffering a cardiac arrest, chances of survival decrease up to 10% per minute. The work of emergency call-takers and emergency respondents is thus key to ensure early recognition and life-saving intervention. As it is so crucial, how to better assist them in their job?

When faced with potential cases of cardiac arrest, time and accuracy are key, which is why Danish company Corti looked into how AI could provide real-time decision support in medical dispatch – and developed a technology that acts as a virtual assistant for call-takers.
In 2018, EENA & Corti partnered to pilot this technology in emergency response centers in France and Italy.

In the report prepared by EENA, Corti and the pilot sites, you will learn about the challenges faced during the project, including data privacy issues and the difficulties of acquiring the necessary datasets.

“The EENA-Corti project was an important learning experience for the use of AI in emergency services, demonstrating not only the potential of the technology, but also how to overcome significant challenges to pave the way for the future of emergency response”, Jerome Paris, EENA Managing Director.

Recommendations & Conclusions from the report:

• Artificial Intelligence does have the potential to assist decision-making of emergency call-takers, by increasing the accuracy of out-of-hospital cardiac arrest detections.
• The pilot project ran in France demonstrated that the AI can also speed up the detections of cardiac arrest over the phone.
• Further training of the AI is needed to keep improving the performance and optimise the models. Wider and good quality datasets play a crucial role to further improving accuracy.
• To ensure maximum efficacy, the AI should be run alongside effective protocols .
• Additional data should be considered an aid to emergency call-takers and emergency response professionals in order to save lives.
• Such data should be presented in a user-friendly manner in order to be effective.

 

Access the report here

“On top of developing preliminary AI models for Out-of-Hospital Cardiac Arrest detection in French and Italian, the results are important because they confirm – despite the challenges – the potential of AI in augmenting call-takers and dispatchers. We look forward to moving ahead and beyond the pilot phases.”, Andreas Cleve, CEO, Corti.

 

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Emergency services call for stronger cooperation with tech companies 

As tech companies are introducing safety features in their products, these well-intended advances are often developed without fully grasping the reality of emergency services.

Many wearables, connected devices and more, now count with special built-in features that can detect emergencies and also communicate with emergency services. But these same emergency services are often not involved in the development of these features, which can result in flawed communications. Data sometimes cannot be processed at emergency response centres, together with an increase of emergency alerts due to false alarms.

This lack of adequate communications is a consequence not anticipated by tech companies, which can hinder the work of emergency services. Without companies being aware of it, there is a possibility that users in danger can be expecting help that will not arrive because the information has not been processed by emergency services.

We believe in innovation and welcome all advances aiming at improving citizens’ safety. That is why we, together with signatories from all over the world, are now calling for tech companies to contact EENA to take part in this dialogue.

Find more in our position paper.