IDENTIFICATION OF CARDIOGENIC SHOCK IN EMERGENCY TRIAGE NURSING

The lack of a standardized process for early identification and differentiation of cardiogenic shock (CGS) leads to a delay in the initiation of targeted treatment, increasing patient mortality risk. The seven-step Iowa model was used as the framework for this quality improvement project. The project resulted in an algorithm to assist in the early identification of CGS during triage in the Emergency Department (ED). It included clinical criteria for shock, nurse-initiated orders, and process steps for identifying and classifying patients in the triage process. CGS is difficult to differentiate from other forms of shock; however, differentiation is vital to treatment as CGS requires a different treatment. CGS is a complex, life-threatening condition with high mortality rates exceeding 50%. Evidence supports using algorithms and protocols to facilitate early identification and treatment to improve patient outcomes. The developed algorithm provided direction for the triage nurse in the initial evaluation and recognition of CGS. An easy-to-follow algorithm assists the triage nurse in the initial assessment and rapid recognition of CGS, allowing for vital and timely targeted treatment initiation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-09
DOI
https://doi.org/10.5281/zenodo.13737711
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

IDENTIFICATION OF CARDIOGENIC SHOCK IN EMERGENCY TRIAGE NURSING

Zenodo (CERN European Organization for Nuclear Research)
Sepsis Diagnosis and Treatment
article

IDENTIFICATION OF CARDIOGENIC SHOCK IN EMERGENCY TRIAGE NURSING

article en

Abstract

The lack of a standardized process for early identification and differentiation of cardiogenic shock (CGS) leads to a delay in the initiation of targeted treatment, increasing patient mortality risk. The seven-step Iowa model was used as the framework for this quality improvement project. The project resulted in an algorithm to assist in the early identification of CGS during triage in the Emergency Department (ED). It included clinical criteria for shock, nurse-initiated orders, and process steps for identifying and classifying patients in the triage process. CGS is difficult to differentiate from other forms of shock; however, differentiation is vital to treatment as CGS requires a different treatment. CGS is a complex, life-threatening condition with high mortality rates exceeding 50%. Evidence supports using algorithms and protocols to facilitate early identification and treatment to improve patient outcomes. The developed algorithm provided direction for the triage nurse in the initial evaluation and recognition of CGS. An easy-to-follow algorithm assists the triage nurse in the initial assessment and rapid recognition of CGS, allowing for vital and timely targeted treatment initiation.

Zenodo (CERN European Organization for Nuclear Research)
Columbia Southern University (US), Clinical Research Consortium (US)
Good health and well-being
Openalex Percentile: Top 56%
Sepsis Diagnosis and Treatment
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