Demand Analysis of a German Emergency Medical Service Feedback System

Keimer M, Villis M, Christoph J, Rödle W (2023)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2023

Publisher: IOS Press

Edited Volumes: German Medical Data Sciences 2023 – Science. Close to People

Series: Studies in Health Technology and Informatics

Book Volume: 307

Pages Range: 102-109

DOI: 10.3233/SHTI230700

Abstract

BACKGROUND: The number of emergency medical service (EMS) calls in Germany is continuously increasing. The initial assessment, the pre-hospital care and the choice of hospital for further care by the EMS influences the patient's outcome and are the basis for further care in hospital. However, the EMS does not receive any official feedback on its decisions. OBJECTIVES: This study evaluates the demand for a feedback system from the emergency department (ED) to the EMS, what it should contain, and how it could be integrated in the electronic clinical systems. METHODS: A semi-structured interview guideline for expert interviews with members of EMS staff (n = 6) and ED staff (n = 17) was developed. A mockup to visualise a possible implementation was designed and included in the interview. RESULTS: There is a significant demand for feedback on pre-diagnosis, pre-hospital care and handover of patients from the EMS to the ED. The EDs are very interested in improving the collaboration with the paramedic services through feedback. CONCLUSION: A feedback system is strongly desired by various EMS stakeholders and, according to them, could improve both EMS and ED collaboration and overall patient care.

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How to cite

APA:

Keimer, M., Villis, M., Christoph, J., & Rödle, W. (2023). Demand Analysis of a German Emergency Medical Service Feedback System. In Rainer Röhrig, Niels Grabe, Martin Haag, Ursula Hübner, Ulrich Sax, Carsten Oliver Schmidt, Martin Sedlmayr, Antonia Zapf (Eds.), German Medical Data Sciences 2023 – Science. Close to People. (pp. 102-109). IOS Press.

MLA:

Keimer, Marina, et al. "Demand Analysis of a German Emergency Medical Service Feedback System." German Medical Data Sciences 2023 – Science. Close to People. Ed. Rainer Röhrig, Niels Grabe, Martin Haag, Ursula Hübner, Ulrich Sax, Carsten Oliver Schmidt, Martin Sedlmayr, Antonia Zapf, IOS Press, 2023. 102-109.

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