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Effect of problem-based learning on severity classification agreement by triage nurses.

Kyeongmin Jang1, Eunmi Jo2, Kyoung Jun Song3

  • 1Department of Nursing, Bucheon University, 56, Sosa-ro, Bucheon-si, Gyeonggi-do, Republic of Korea.

BMC Nursing
|December 21, 2021
PubMed
Summary

Learner-led problem-based learning significantly improved emergency department triage nurses' self-efficacy and agreement in classifying patients using the Korean Triage and Acuity Scale. This enhances accuracy and patient safety.

Keywords:
Emergency departmentLength of stayPatient safetyProblem-based learningTriage

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Area of Science:

  • Emergency Medicine
  • Nursing Education
  • Healthcare Quality Improvement

Background:

  • Triage nurse classification agreement can vary, impacting emergency department care.
  • Training and algorithmic approaches are potential methods for improving consistency.

Purpose of the Study:

  • To evaluate if learner-led problem-based learning enhances inter-rater agreement among triage nurses.
  • To assess the impact of this learning method on nurses' self-efficacy in patient classification.

Main Methods:

  • A single-group time series design was employed.
  • Data collected from 1200 emergency department patients (300 each in May/August 2018 and May/August 2019).
  • Comparison of Korean Triage and Acuity Scale (KTAS) classification agreement before and after the intervention.

Main Results:

  • Triage nurses showed a statistically significant increase in self-efficacy for patient classification post-learning (p < .001).
  • The weighted kappa coefficient indicated almost perfect agreement (0.835, p < .001) after the problem-based learning intervention.

Conclusions:

  • Problem-based learning effectively improved inter-rater agreement for KTAS classifications.
  • Enhanced nurse expertise and classification accuracy through problem-based learning contribute to improved patient safety in emergency departments.