Prehospital care involves care provided by the hospital before care. Ambulance care is an example of prehospital care that takes place outside the walls of a healthcare institution. The developed OSISP algorithm can help improve decisions in ambulances; especially when it comes to quickly assessing the severity of injuries. Researcher Anna Bakidou explains: “When seriously injured people are transported directly to a university hospital, their chances of survival increase. The algorithm can help healthcare professionals make important decisions with a data-driven approach.”
Improved triage methods
Analysis of more than 47,000 real incidents collected using the Swedish Trauma Registry (SweTrau) showed that 40% of seriously injured patients were not immediately transported to a university hospital. Furthermore, 45% of less seriously injured patients were sent unnecessarily to specialized hospitals. These insights show that improved triage methods in the ambulance are welcome.
Extra colleague on the ambulance
Bakidou describes the algorithm as an “extra colleague,” helping staff see more complex connections, especially in situations where injuries are difficult to assess. This is important, among other things, for young people injured in a road accident and for elderly people who have fallen. In such situations, the severity of injuries is routinely misjudged.
Integrating AI into ambulances is promising, but it also presents its share of challenges. Optimizing the algorithm and integrating it into existing workflows still raises questions. Large clinical trials and further studies are needed to refine and test AI tools in prehospital care.
AI, ambulance triage
The use of artificial intelligence in the triage process is nothing new, but it certainly has a future. For example, “family doctors in the Netherlands” have already won a professional jury award with their intelligent triage software, which optimizes patient flow management. AI is also used in triage processes at hospitals, such as the Tel Aviv Sourasky Medical Center, using a modified version of ChatGPT.
The future of artificial intelligence in ambulances is also promising, but according to researchers the road to full implementation is still long. Expanding datasets through international collaboration and integrating additional vital functions into AI models are some essential steps that still need to be taken. In particular, Bakidou highlights the importance of developing methods to quickly and easily feed more information into the AI system and communicate effectively with users.
2024-01-12 08:00:00
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