Pappa Despoina, Manthou Panagiota, Ferentinou Eftychia, Giga Anna, Bourazani Maria, Chrysi Maria S, Zartaloudi Afroditi, Vathi Eleni, Varvitsioti Despoina, Mangoulia Polyxeni
Department of Nursing, Henry Dunant Hospital Center, Athens, GRC.
Department of Nursing, University of West Attica, Athens, GRC.
Cureus. 2024 Jul 22;16(7):e65070. doi: 10.7759/cureus.65070. eCollection 2024 Jul.
Nursing errors significantly impact patient safety and care quality, necessitating effective error recognition and analysis techniques. The Taxonomy of Error, Root Cause Analysis, and Practice-Responsibility (TERCAP) tool aims to systematically classify and address nursing errors, though its application and usefulness remain uncertain. This systematic review provides an overview of nursing errors using the TERCAP instrument, evaluating its applicability, strengths, and opportunities for improvement. A comprehensive literature search was conducted across databases such as PubMed, CINAHL, and Scopus to identify studies employing the TERCAP tool for nursing error analysis. Inclusion criteria encompassed peer-reviewed articles, studies with quantitative or qualitative data, and English-language publications. Data were extracted and analyzed to assess the tool's validity, reliability, impact on patient outcomes, and integration into clinical practice. The review identified a limited number of studies utilizing the TERCAP instrument, indicating its early stage of implementation. Findings suggest that the TERCAP tool provides a structured approach to error categorization and root cause analysis, potentially benefiting patient safety. However, challenges such as inconsistency in tool use, integration issues with electronic health records, and the need for further validation were noted. Additionally, nurses' perceptions of the tool and training needs emerged as crucial factors influencing its effectiveness. The TERCAP tool shows promise in improving nursing error reporting and analysis. Nonetheless, further research is essential to confirm its reliability, optimize its integration into clinical workflows, and understand its long-term impact on patient outcomes and safety culture. Addressing these gaps will be crucial in harnessing the TERCAP tool's full potential to reduce nursing errors and enhance healthcare quality.
护理差错对患者安全和护理质量有重大影响,因此需要有效的差错识别和分析技术。差错分类、根本原因分析与实践责任(TERCAP)工具旨在系统地对护理差错进行分类和处理,但其应用和效用仍不确定。本系统评价使用TERCAP工具对护理差错进行了概述,评估了其适用性、优势和改进机会。通过在PubMed、CINAHL和Scopus等数据库中进行全面的文献检索,以识别采用TERCAP工具进行护理差错分析的研究。纳入标准包括同行评审文章、具有定量或定性数据的研究以及英文出版物。提取并分析数据,以评估该工具的有效性、可靠性、对患者结局的影响以及在临床实践中的整合情况。该评价发现使用TERCAP工具的研究数量有限,表明其处于实施的早期阶段。研究结果表明,TERCAP工具为差错分类和根本原因分析提供了一种结构化方法,可能有利于患者安全。然而,也指出了一些挑战,如工具使用的不一致、与电子健康记录的整合问题以及需要进一步验证。此外,护士对该工具的看法和培训需求成为影响其有效性的关键因素。TERCAP工具在改善护理差错报告和分析方面显示出前景。尽管如此,进一步的研究对于确认其可靠性、优化其在临床工作流程中的整合以及了解其对患者结局和安全文化的长期影响至关重要。解决这些差距对于充分发挥TERCAP工具减少护理差错和提高医疗质量的全部潜力至关重要。