Publication Application of artificial intelligence (AI) systems in the emergency room
In this publication, we seek to address whether communication patterns and information request behavior indicate potential starting points in applying AI systems in emergency room. The research paper can be assessed here: https://lnkd.in/ekGQzF79.
The treatment of polytrauma patients, i.e., patients with multiple and life-threatening injuries, is carried out under great time and decision-making pressure, especially in the acute phase. In this context, verbal communication is the basic element for communication and information transfer between treating persons, both during registration, transfer from emergency medical care to the shock room team, and during treatment and transfer to the intensive care unit. It is at these interfaces in the polytrauma care chain that information loss in verbal communication is high. This is where the TraumAInterfaces project, funded by the German Federal Ministry of Health (BMG), comes in. The goal is to prototype and test an AI-based system for recording, transcribing and structuring verbal communication in polytrauma care. The project focusses on realistic testing of prototypes for the automated recording, transcription and structuring of verbal communication along the polytrauma care. In particular, the project will examine system performance, acceptance and impact in more detail. In order to improve the process in a sustainable way, different perspectives and stakeholders (algorithm, treating team as user and treatment process) will be involved and considered. Therefore, a wide variety of partners from the fields of trauma surgery, anesthesia and experts from medical education and training, AI-based language technologies, cognitive-psychological multitasking research and technology and innovation management are working together in an interdisciplinary manner. The interdisciplinarity connects science and industry and brings both sides closer together.