In the fast-paced world of emergency healthcare, making quick and accurate decisions is crucial.
This is where artificial intelligence (AI) could play a transformative role, as recent research from Chalmers University of Technology in Sweden, along with the University of Gothenburg and the University of Borås, has shown.
The study, led by Anna Bakidou, a doctoral student at Chalmers University, focuses on improving how healthcare professionals assess severely injured patients.
The research, published in BMC Medical Informatics and Decision Making, developed five different AI models using data from over 47,000 real ambulance care incidents between 2013 and 2020.
This data, from the Swedish Trauma Registry, included various complex factors like respiratory rate, type of injury, blood pressure, age, and gender.
The results were eye-opening. The AI models outperformed the transport decisions made by ambulance staff at the time of the incidents.
It was found that 40% of severely injured patients were not directly sent to university hospitals, which are better equipped for serious injuries.
Conversely, 45% of patients who were not severely injured were sent to these specialized hospitals unnecessarily.
Anna Bakidou envisions the AI tool acting as an ‘extra colleague’ for ambulance personnel, helping them see more complex connections and reconsider decisions in tricky situations.
For instance, younger people involved in traffic accidents are often judged to be more severely injured than they are.
Meanwhile, older people, especially in cases like fall accidents, might be underestimated in terms of injury severity, despite the risk of life-threatening conditions like internal bleeding.
However, integrating this technology into ambulance services is not without challenges. Key steps include finding ways to quickly and easily input data into the AI tool and ensuring the system can interact effectively with users.
Issues like hands-free operation, integration with existing routines and protocols, and updating staff advice with new data are all under consideration for future studies and prototype development.
Before AI can become a regular part of ambulance services, extensive clinical trials are needed. Co-author Stefan Candefjord, Associate Professor at Chalmers University, acknowledges the regulations and concerns surrounding AI in healthcare.
The potential consequences of errors are significant, and all new healthcare technologies must undergo thorough validation.
Despite these hurdles, the promise of AI in ambulance care is exciting. It’s a field with limited AI research, and these mathematical models could provide crucial support adapted to the work environment.
In the long run, AI has the potential to offer more equitable care, ensuring that all patients receive the appropriate level of medical attention as quickly as possible.
This research from Chalmers University and its collaborators represents a significant step towards the future of emergency medical care, where AI could save more lives by aiding in rapid, accurate decision-making.
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The research findings can be found in BMC Medical Informatics and Decision Making.
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