The Relationship between Nurses' Knowledge about Emergencies and Code Blue Activation Decisions

Main Article Content

Hikmah Lia Basuni
Yayan Gusman
Maruli Taufandas
Apriani Susmita Sari
Corresponding Author:
Hikmah Lia Basuni | hikmahliabasuni@gmail.com



Abstract

Introduction: Code Blue is a hospital system created to overcome the high death rate due to respiratory arrest and cardiac arrest in hospitals. It involves all hospital components, including medical personnel, communication systems, transportation and facilities, and infrastructure. The initial principle of handling cardiac arrest is how nurses can recognize early signs of emergency so that the decision to activate code blue can be made. Knowledge about emergencies is a basic component that nurses must have in making blue activation code decisions. However, in its application, caring for cardiac arrest sufferers carried out by nurses is often still not appropriate.


Objective: This study aims to determine the relationship between nurses' knowledge of emergencies and the decision to activate code blue.


Methods: This research is a quantitative research with an analytical survey method using cross-sectional research. In this study, the non-parametric Spearman rank correlation test was carried out at the. Sampling used total sampling technique and obtained 70 respondents.


Results: There is a relationship between nurses' knowledge about emergencies and the decision to activate code blue at with a significant value of p= 0,000 (p < α 0.05), r = 0.601.


Conclusion: There is a relationship between nurses' knowledge about emergencies and the decision to activate code blue. Training resuscitation skills and increasing nurses' knowledge through regular training, workshops, or code blue simulations are recommended, especially for patient care units that rarely activate code blue.

Article Details

How to Cite
[1]
H. L. Basuni, Y. Gusman, M. Taufandas, and Apriani Susmita Sari, “The Relationship between Nurses’ Knowledge about Emergencies and Code Blue Activation Decisions”, Babali Nurs. Res., vol. 5, no. 1, pp. 67-75, Jan. 2024.
Section
Original Research

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