提升護理師心電圖判讀正確率之改善專案

Improvement Project to Enhance Nurse's Clinical Judgement of Electrocardiogram

盧雅莉(Ya-Li Lu) ； 鐘婷怡(Ting-Yi Chung) ； 劉又瑛(Yu-Ying Liu) ； 莊寶玉(Pao-Yu Chuang)

《臺大護理雜誌》 16卷2期 (2020/07) Pp. 112-125

https://doi.org/10.6740/NTUHJN.202007_16(2).0011

摘要

背景：本病房心電圖判讀正確率僅49.4%，分析判讀正確率低的原因包含：護理師心電圖判讀專業知識與信心不足、缺乏練習教材、缺乏心電圖判讀在職教育及學習回饋機制。目的：護理師心電圖判讀正確率由49.4%提升為82.0%。解決方案：經添購最新書籍、在職教育、設計情境模擬心電圖學習軟體提供練習與建立回饋機制等措施。結果：護理師心電圖判讀正確率由49.4%提升為88.9%。結論：建議臨床常見護理專業知識、護理技術或病人衛教指導等，可透過多媒體程式軟體學習，以增加護理師學習動機與成效。

關鍵字

心電圖 ； 在職教育 ； 學習軟體

並列摘要

The main purpose of this project was to improve the nurse's clinical judgement of an electrocardiogram (EKG). In the past, nurses less identify the patients' abnormal EKG at early stage. The accuracy rate of EKG interpretation was only 49.4%. The reasons for the low accuracy rate were lack of confidence and knowledge about EKG, insufficient update textbook, limited in-service education, and feedback after training. The strategies were developed including purchasing the latest edition of the textbook, developing clinical-based teaching material, designing self-learnt EKG simulation software, and establishing a feedback system. The accuracy rate of EKG interpretation improved to 88.9% in 2018 and at the follow-up period, accuracy rate increased to 90.7%. Moreover, nurses accurately determined the abnormal pulse rates increased from 76.7% to 91.7% and 97.1% relatively. We conclude that using self-learnt software with simulation design can enhance nurse's accuracy rate of EKG interpretation and improve patient safety.

並列關鍵字

electrocardiogram ； in-service education ； learning software