한국 중환자실 간호사 대상 고위험약물 투약오류 예방 임상의사결정 프로그램 효과: 비동등 대조군 전후설계 연구

• 영문명: The effect of a clinical decision-making program for preventing high-alert medication errors among intensive care unit nurses in South Korea: a quasi-experimental study with a nonequivalent control group design
• 발행기관: 한국기초간호학회
• 저자명: 박세영 박소미 김가영 홍승아 최향옥 문선영
• 간행물 정보: 『Journal of Korean Biological Nursing Science』제27권 제3호, 366~377쪽, 전체 12쪽
• 주제분류: 의약학 > 의학일반
• 파일형태: PDF
• 발행일자: 2025.08.31

국문 초록

Purpose This study aimed to evaluate the effectiveness of a simulation based clinical decision-making program for preventing high-alert medication errors among intensive care unit nurses. Methods A nonequivalent control group pre/post-test design was employed. The study involved 40 nurses working in the intensive care unit of a tertiary general hospital. The results for an experimental group (n = 20) that participated in the simulation-based clinical decision-making program for preventing high-alert medication errors (duration 180 minutes) were compared with those of a control group (n = 20) that received lecture education (duration 90 minutes). The intervention was conducted and data were collected from June 24 to October 31, 2024. Registered with the Clinical Research Information Service (KCT0010214). Results The experimental group exhibited improved clinical decision-making ability (χ2 = 10.57, p = .005), reduced risk of high-alert medication errors (χ2 = 6.17, p = .046), and fewer experiences of near-miss medication errors (χ2 = 7.05, p = .008) compared to the control group immediately and 3 months after the intervention. Conclusion The findings suggest that the program can be effectively used to improve the clinical decision-making ability and to reduce the risk of high-alert medication errors among intensive care unit nurses, thereby contributing to ensuring medication safety in intensive care units by reducing the occurrence of medication errors.

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키워드

간호사 중환자실 투약오류 임상의사결정 시뮬레이션교육 Nurses Intensive care units Medication errors Clinical decision-making Simulation training