分析患者安全报告系统中用药错误报告的方法学方法:范围综述。

IF 2.3 Q2 HEALTH CARE SCIENCES & SERVICES
Olga Tchijevitch, Sebrina Maj-Britt Hansen, Jesper Hallas, Søren Bie Bogh, Alma Mulac, Sisse Walløe, Mette Kring Clausen, Søren Birkeland
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引用次数: 0

摘要

背景:用药错误(MEs)对患者安全构成风险,导致巨大的经济成本。为了加强病人的安全,并从事故中吸取教训,卫生保健和药物警戒组织通过报告系统系统地收集ME数据。尽管关于报告系统中的MEs的文献越来越多,但缺乏用于分析它们的方法的概述。作者旨在识别、探索和绘制用于分析报告系统中MEs的方法的现有文献。方法:采用Joanna Briggs研究所的研究方法。作者系统地检索了电子数据库Embase、Medline、CINAHL、Cochrane Central和其他来源(b谷歌Scholar、卫生保健安全和药物警戒中心的网站)。2017年1月至2023年12月发表的文献由两位独立研究人员筛选和提取。结果:在提取的59篇论文中,分析最常集中在医院发生的MEs(57.6%),包括成人和儿科患者(79.7%),并使用国家专利安全监测系统作为来源(69.5%)。我们确定了定量(39.0%)、定性(11.9%)、混合方法(37.3%)和先进的计算机化方法(11.9%)。对分类数据进行描述性定量分析是常见的;然而,不成比例分析是解决报告偏倚问题的一种较新的方法。自由文本数据通常采用内容分析方法进行管理,而混合方法同时分析分类数据和自由文本数据。此外,文本挖掘、自然语言处理和人工智能在最近的研究中得到了应用。结论:这一范围审查揭示了方法论的显著跨度和多样性。未来的研究应评估新方法的使用、适用性和有效性,如歧化分析和先进的计算机技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodological Approaches for Analyzing Medication Error Reports in Patient Safety Reporting Systems: A Scoping Review.

Background: Medication errors (MEs) pose risks to patient safety, resulting in substantial economic costs. To enhance patient safety and learning from incidents, health care and pharmacovigilance organizations systematically collect ME data through reporting systems. Despite the growing literature on MEs in reporting systems, an overview of methods used to analyze them is lacking. The authors aimed to identify, explore, and map available literature on methods used to analyze MEs in reporting systems.

Methods: The review was based on Joanna Briggs Institute's methodology. The authors systematically searched electronic databases Embase, Medline, CINAHL, Cochrane Central, and other sources (Google Scholar, health care safety and pharmacovigilance centers' websites). Literature published from January 2017 to December 2023 was screened and extracted by two independent researchers.

Results: Among the 59 extracted publications, analyses most often focused on MEs occurring in hospitals (57.6%), included both adult and pediatric patients (79.7%), and used national patent safety monitoring systems as a source (69.5%). We identified quantitative (39.0%), qualitative (11.9%), mixed methods (37.3%), and advanced computerized methods (11.9%). Descriptive quantitative analyses for categorized data were common; however, disproportionality analysis constituted a newer approach to address issues with reporting bias. Free-text data were commonly managed by content analysis, while mixed methods analyzed both categorized and free-text data. In addition, text mining, natural language processing, and artificial intelligence were used in more recent studies.

Conclusion: This scoping review uncovered a notable span and diversity in methodologies. Future research should assess the use, applicability, and effectiveness of newer methods such as disproportionality analysis and advanced computerized techniques.

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来源期刊
CiteScore
3.80
自引率
4.30%
发文量
116
审稿时长
49 days
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