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Published on: November 9, 2016
Nursing Perceptions of the Emergency Severity Index as a Triage Tool in the United Arab Emirates: A Qualitative
Binoy Mistry1, Kamna S Balhara1, Jeremiah S Hinson1
1Baltimore, MD; San Antonio, TX; Abu Dhabi, United Arab Emirates.
Introduction:
With emergency department crowding becoming an increasing problem across the globe, nursing triage to prioritize patients receiving care is ever more important. ESI is the most common triage system used in the United States and is increasingly used worldwide. This qualitative study that explores emergency nursing perceptions of the ESI identifies strengths, weaknesses, and barriers to implementation of the ESI internationally.
Methods:
We conducted a cross-sectional qualitative analysis using semistructured interviews of 27 emergency triage nurses. Content analysis was performed by 2 independent coders, using NVivo software to identify and analyze important themes.
Results:
Interview coding revealed 7 core themes related to use of the ESI (frequencies indicated in parentheses): ease of use (90), speed and efficiency (135), patient safety (12), accuracy and reliability (30), challenging patient characteristics (123), subjectivity and variability (173), and effect of triage system on team dynamics (100). Intercoder agreement was excellent (Cohen's unweighted kappa = 0.84). Subjectivity and variability in ESI score assignment consistently emerged in all interviews and included variability in number and use of resources, definition of "high risk," nursing experience, and subjectivity in pain assessment.
Discussion:
Although emergency nurses perceive the ESI as easy to use, there are concerns about the subjectivity and variability inherent in the ESI that can lead to a functional lack of triage and a burden of undifferentiated ESI level 3 patients. These limitations in separating critically ill patients and in stratifying patients based on anticipated required resources points to the need for improvement in the ESI algorithm or a more objective triage system that can predict patient outcomes.
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