Artificial Intelligence (AI) Models Revolutionize Emergency Healthcare Decision-Making, Enhancing Patient Care
In the high-pressure realm of emergency healthcare, the ability to make swift and accurate decisions is paramount. Recent research conducted by Chalmers University of Technology, in collaboration with the University of Gothenburg and the University of Borås in Sweden, has demonstrated the potential of artificial intelligence (AI) to transform this process.
Led by Anna Bakidou, a doctoral student at Chalmers University, the study focused on improving the assessment of severely injured patients by healthcare professionals. The research, published in BMC Medical Informatics and Decision Making, involved the development of five AI models using data from over 47,000 real ambulance care incidents that occurred between 2013 and 2020.
The data utilized in the study were derived from the Swedish Trauma Registry and encompassed various complex factors such as respiratory rate, type of injury, blood pressure, age, and gender. The results of the research were astounding, as the AI models outperformed the transport decisions made by ambulance staff during the incidents.
Critically, the study revealed that 40% of severely injured patients were not promptly sent to university hospitals, which possess superior capabilities for handling serious injuries. Conversely, 45% of patients who were not severely injured were unnecessarily transported to these specialized hospitals. These findings highlight the potential for AI to significantly enhance decision-making in emergency healthcare scenarios.
Anna Bakidou envisions the AI tool acting as an extra colleague for ambulance personnel, aiding them in detecting complex connections and reconsidering decisions when confronted with challenging situations. For example, younger people involved in traffic accidents are often perceived as being more severely injured than they actually are. Conversely, older individuals, particularly in incidents such as falls, may be underestimated in terms of injury severity despite the potential for life-threatening conditions like internal bleeding.
However, integrating this technology into ambulance services presents its share of challenges. Crucial steps include devising efficient means of inputting data into the AI tool and ensuring seamless interaction between the system and its users. Issues such as hands-free operation, integration with existing protocols and routines, and updating staff advice in light of new data are all being considered in future studies and prototypes.
Before AI can be effectively incorporated into ambulance services, extensive clinical trials are imperative. Stefan Candefjord, Associate Professor at Chalmers University and co-author of the study, acknowledges the regulatory and ethical concerns surrounding the implementation of AI in healthcare. Given the potentially significant consequences of errors, all healthcare technologies necessitate thorough validation.
Notwithstanding these challenges, the promise of AI in ambulance care is undeniably exhilarating. With limited research in this field, mathematical models like those presented by Chalmers University and its collaborators could provide invaluable support tailored to the demands of emergency healthcare environments.
Ultimately, AI has the potential to facilitate more equitable care by ensuring that all patients receive the appropriate level of medical attention swiftly. The research conducted by Chalmers University and its partners represents a crucial step towards the future of emergency medical care, in which AI could save more lives by assisting in rapid and accurate decision-making.
