Centre for Quality and Patient Safety Research - Monash Health Partnership, School of Nursing and Midwifery, Institute for Health Transformation, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia.
Applied Artificial Intelligence Institute, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia.
Int J Nurs Stud. 2022 Mar;127:104178. doi: 10.1016/j.ijnurstu.2022.104178. Epub 2022 Jan 16.
Harm prevention research has seldom considered the complex demands on nurses negotiating multiple interrelated factors that contribute to preventable harms common in hospitalized patients. Best practice guidelines are available for individual risk factors, but few consider multiple factors that contribute to risk. As a consequence, duplication, contradiction, gaps, and volume of information limit harm prevention guideline use by nurses in daily practice.
To systematically synthesise best-evidence recommendations from clinical practice guidelines to support nurses to deliver comprehensive harm prevention during acute hospitalization.
An integrative review process was used to systematically identify, examine, evaluate and synthesise clinical nursing guidelines to prevent harm to hospitalized patients.
The search strategy developed with an expert librarian used a combination of targeted searching for guidelines published on websites, and forward and backward citation searching. Guidelines included were those most recently published, relevant to the international nursing context, and addressing one or more of eight factors contributing to preventable harms. The AGREE-REX (Appraisal of Guidelines Research and Evaluation-Recommendations Excellence) tool was used for critical appraisal of guidelines regarding appropriateness to target users (i.e., nurses), trustworthiness, and implementable in acute hospitals. EndNote and NVIVO 12 were used to manage the high volume of extracted data and facilitate analysis. Analyses involved using the framework method to code data for relevance to an eight-factor harm prevention framework; steps for inductive thematic analyses were used for synthesis. Iterations of the thematic model were refined by sharing with hospital patient safety experts, who endorsed the final model.
154 guidelines met inclusion criteria, providing 7,429 recommendations. Synthesis involved mapping of recommendations across the eight-factor framework that informed a hierarchy of risk for harm prevention activity. Six themes represented nursing care strategies across the eight-factors that could be integrated into local practice contexts. The themes are framed into a model for nurse comprehensive harm prevention.
The complexity and volume of guidance for comprehensive harm prevention necessitates contemporaneous, integrated, and accessible guidance to support nurses' decision-making in their daily care provision. This research provides an integrated model to assist nurses to identify patients most vulnerable to multiple preventable harms during hospitalization and guide a comprehensive harm prevention strategy to keep them safe in hospital.
Review of nursing guidelines generates integrated model to help identify patients most vulnerable to multiple preventable harms during hospitalization.
伤害预防研究很少考虑到护士在协商导致住院患者可预防伤害的多种相互关联因素时所面临的复杂需求。针对个别风险因素已有最佳实践指南,但很少考虑导致风险的多种因素。因此,重复、矛盾、差距和信息量限制了护士在日常实践中使用伤害预防指南。
系统综合临床实践指南中的最佳证据建议,以支持护士在急性住院期间提供全面的伤害预防。
使用综合审查过程系统地识别、检查、评估和综合预防住院患者伤害的临床护理指南。
与专家图书馆员共同制定的搜索策略结合了针对已发布在网站上的指南的有针对性搜索,以及向前和向后引用搜索。纳入的指南是最近发布的、与国际护理背景相关的、并针对导致可预防伤害的八个因素之一或多个因素的指南。使用 AGREE-REX(评估指南研究和评估-推荐卓越)工具对指南进行批判性评估,以确定其对目标用户(即护士)的适当性、可信度和在急性医院中的可实施性。使用 EndNote 和 NVIVO 12 来管理提取数据的高量,并促进分析。分析涉及使用框架方法对与八项伤害预防框架相关的数据进行编码;使用归纳主题分析步骤进行综合。通过与医院患者安全专家分享主题模型的迭代版本来完善主题模型,这些专家认可了最终模型。
154 项指南符合纳入标准,提供了 7429 条建议。综合分析涉及将建议映射到八个因素框架上,为伤害预防活动的风险分层提供信息。六个主题代表了跨越八个因素的护理策略,可以整合到当地的实践环境中。这些主题被构建成一个护士全面伤害预防模型。
全面伤害预防的复杂性和信息量需要同时提供综合且易于获取的指导,以支持护士在日常护理提供中的决策。这项研究提供了一个综合模型,帮助护士识别在住院期间最容易受到多种可预防伤害的患者,并指导全面的伤害预防策略,以确保患者在住院期间的安全。
审查护理指南生成了一个综合模型,以帮助识别在住院期间最容易受到多种可预防伤害的患者。