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Total quality management in the health-care context: integrating the literature and directing future research

机译:卫生保健领域的全面质量管理:整合文献并指导未来研究

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Background: Synergistic integration of predictors and elements that determine the success of total quality management (TQM) implementations in hospitals has been the bane of theoretical development in the TQM research area. Thus, this paper aims to offer a systematic literature review to provide a foundation on which research on TQM can be built and to identify the predictors of successful TQM in the health-care context. Materials and methods: A systematic literature survey was adopted in this paper, involving the review of 25 relevant researched articles found in the databases Science Direct, EBSCO, MEDLINE, CINAHL and PubMed. Result: The systematic literature survey reveals five variables to be core predictors of TQM, signifying how important these variables are in the successful implementation of TQM in the health-care context. Also, it is revealed that the identified core predictors have positive effects on an improved health-care system. However, the systematic survey of the literature reveals a dearth of studies on TQM in the health-care context. Conclusion: As TQM has become an important management approach for advancing effectiveness in the health-care sector, this kind of research is of value to researchers and managers. Stakeholders in the health sectors should introduce and implement TQM in hospitals and clinics. Nevertheless, this study has limitations, including that the databases and search engines adopted for the literature search are not exhaustive.
机译:背景:确定医院全面质量管理(TQM)实施成功的预测因素和要素的协同集成一直是TQM研究领域理论发展的祸根。因此,本文旨在提供系统的文献综述,以提供可对TQM进行研究的基础,并确定医疗保健领域成功TQM的预测因素。材料和方法:本文采用系统的文献调查方法,涉及对在Science Direct,EBSCO,MEDLINE,CINAHL和PubMed数据库中找到的25篇相关研究文章的评论。结果:系统的文献调查揭示了五个变量是TQM的核心预测指标,表明这些变量对于在卫生保健领域成功实施TQM至关重要。此外,还发现已确定的核心预测因素对改善的医疗保健系统具有积极作用。但是,对文献的系统性调查显示,在卫生保健领域,对全面质量管理的研究不足。结论:由于全面质量管理已成为提高卫生保健部门效率的重要管理方法,因此这种研究对研究人员和管理人员具有价值。卫生部门的利益相关者应在医院和诊所引入并实施全面质量管理。然而,这项研究有局限性,包括文献搜索所采用的数据库和搜索引擎并不详尽。

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