Effect of problem-based learning on severity classification agreement by triage nurses - Kyeongmin Jang; Eunmi Jo; Kyoung Jun Song (BMC, 2021)
Abstract Background Differences in the classification results among triage nurses in the emergency room can be improved by training or applying an algorithm. This study aimed to confirm whether the agreement among triage nurses could be improved through learner-led problem-based learning. Methods This study had a single-group time series design to investigate the effect of problem-based learning led by triage nurses on the agreement of Korean Triage and Acuity Scale classification results for patients who visited the emergency department. We extracted 300 patients each in May and August 2018 before learning began and 300 patients each in May and August 2019 after learning. Results After problem-based learning was applied, the self-efficacy of triage nurses for emergency patient classification increased statistically significantly compared to before learning (7.88 ± 0.96, p < .001), and the weighted kappa coefficient was also found to be almost perfectly agreement (0.835, p < .001). Conclusions In this study, problem-based learning improved the inter-rater agreement of Korean Triage and Acuity Scale classification results and self-efficacy of triage nurses. Therefore, problem-based learning can contribute to patient safety in the emergency department by enhancing the expertise of triage nurses and increasing the accuracy of triage classification.