Anrufgründe bei medizinischen Notfällen: Entwicklung eines strukturierten semantischen Modells auf Basis einer randomisierten Stichprobe medizinischer Hilfeersuchen einer integrierten Rettungsleitstelle

Emergency dispatch centres face increasing challenges due to continuously rising numbers of emergency calls. Standardised call handling systems are implemented in many locations to improve the way emergency conversations are structured and prioritised. Current developments in the field of artificial intelligence (AI) have open up new possibilities for decision support for dispatchers. The prerequisite for this is a process-based model of the emergency call dialogue.

Based on an analysis of the complex reason for emergency calls, the structural characteristics of emergency calls are derived and presented as a model.

In all, 50 randomly selected medical emergency call recordings of an integrated emergency dispatch centre from the year 2022 are transcribed, inductively coded, categorised and transferred into a processual model of the emergency call dialogue using qualitative content analysis.

The typical emergency call consists of two consecutive processes: an entry process and a query process. The initial process gathers information to assess whether the reason for the emergency call is a single main problem, a combination of several health issues, or an event before or after a health issue. The query process serves to clarify the description of the condition or problem.

Using the randomly selected emergency calls, it was possible to derive the ideal-typical course of the emergency call and illustrate it in a phase or process-like model, which can now be used as a foundation for developing AI-supported emergency call handling systems.