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Prehospital Resuscitation Decision Making: A model of ambulance personnel experiences, preparation and support.

Authors :
Anderson, Natalie E
Slark, Julia
Gott, Merryn
Source :
Emergency Medicine Australasia; Aug2021, Vol. 33 Issue 4, p697-702, 6p
Publication Year :
2021

Abstract

Objective This paper presents the first Naturalistic Decision Making model of prehospital resuscitation decision‐making, which has clear implications for education, practice and support. Methods: A mixed‐methods exploratory sequential research design consisting of interviews with ambulance personnel (study 1), focus groups with ambulance educators, managers and peer supporters (study 2), and an online survey of graduating paramedic students (study 3). This paper reports the model developed from integrated findings, across all three studies. All research was undertaken in New Zealand and underpinned by a critical realist worldview. Results: The Prehospital Resuscitation Decision Making model identifies key processes, challenges and facilitators before, during and after ambulance personnel attend a cardiac arrest event. It is the only descriptive model of resuscitation decision making which acknowledges the decision‐maker, non‐prognostic factors and the importance of adequate preparation and support. Conclusions: This research project is the first to comprehensively explore and model ambulance personnel perspectives on decisions to start, continue or stop resuscitation. The decision‐making process is complex and difficult to simply formularise. Education and supports must assist ambulance personnel in navigating this complexity. Where resuscitation is withheld or terminated, ambulance personnel need to feel confident that they can effectively provide after‐death care. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17426731
Volume :
33
Issue :
4
Database :
Complementary Index
Journal :
Emergency Medicine Australasia
Publication Type :
Academic Journal
Accession number :
151472991
Full Text :
https://doi.org/10.1111/1742-6723.13715