Volume 27, Issue 153 (10-2017)                   J Mazandaran Univ Med Sci 2017, 27(153): 84-94 | Back to browse issues page

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Aramesh Z, Mazloum R, Aghebati N, Mashhadi Nejad H. Comparing the Efficacy of Nursing Care based on ESI Triage and Roy Adaptation Model in Predicting the Need for ICU or Ward Admission among Head Trauma Patients . J Mazandaran Univ Med Sci 2017; 27 (153) :84-94
URL: http://jmums.mazums.ac.ir/article-1-9513-en.html
Abstract:   (6845 Views)
Background and purpose: Head trauma is amongst the major causes of death and morbidity caused by traumatic injuries. Assessment of trauma patients is an active process which includes initial (triage) and secondary assessments. Various triage tools are designed and used, but, so far no specific and accurate tool has been introduced for triage of head trauma. This study compared the effectiveness of ESI triage tool and nursing triage approach based on Roy Adaptation Model to predict the need for ICU admission in patients with head trauma.
Materials and methods: A clinical trial was done in 400 patients with head trauma in Emergency Department, Mashhad Shahid Kamyab Hospital, 2016. Patients were selected using block randomization and based on the day of admission. They were allocated into receiving nursing care either through ESI triage or Roy Adaptation Model. Twelve hours after triage, patients' outcome were followed based on keeping them in ICU or ward admission. Finally, the margin of error was calculated and compared between the two instruments.
Results: Kappa test did not show any significant difference between the ESI and Roy Adaptation Model triage in prediction for ICU admission at first place (P= 0.123). But, the Roy Adaptation Model was associated with significantly less errors in keeping the patient in ICU or ward admission (P = 0.012 ).
Conclusion: Compared with ESI triage, Roy Adaptation Model could result in fewer errors in predicting the consequences of head trauma patients.
 
 
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Type of Study: Research(Original) | Subject: Emergency Medicine

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