Research shows more lives can be saved if ambulance staff receive AI support

Story by Mia Halleröd Palmgren

Assessing how seriously injured a person is, involves weighing up lots of different parameters fast. If health care professionals could get support making fast-paced, life-critical decisions from an AI tool, more lives could be saved. This has been shown by research from Chalmers University of Technology in Sweden, along with the University of Gothenburg and the University of Borås.

“If severely injured people are transported directly to a university hospital, the chances of survival increase, as there are resources to take care of all types of injuries. Therefore, we need to be able to better say who is severely injured, and who is not, so that everyone receives the right care and that resources are used in the best way,” says Anna Bakidou, doctoral student in the research group Care@Distance—Remote and Prehospital Digital Health at the Department of Electrical Engineering at Chalmers University of Technology.

In a study published in BMC Medical Informatics and Decision Making, Anna Bakidou and her co-authors have developed five different mathematical models based on the data of adults who came into contact with ambulance care between 2013 and 2020.

This data is from over 47,000 real events, retrieved from the Swedish Trauma Registry, which also showed where the people had been transported. By weighing up a number of complex variables, such as respiratory rate, injury type, blood pressure, age and gender, it turned out that all AI models could perform better than the clinical outcome—which were the transport decisions made by the ambulance staff at the time of the incident.

Full Article: Research shows more lives can be saved if ambulance staff receive AI support (msn.com)