How can we optimise nursing shift patterns to balance costs, patient outcomes and staff wellbeing?

护士构成了NHS工作人员中最大的群体，大多数人在24小时环境中提供护理。这支队伍的组织，包括轮班模式的设计，对病人护理有深远的影响。轮班可以有多种方式(例如，8小时轮班与12小时轮班)，这取决于成本、患者安全和员工福利等所需的结果平衡。以往的研究已经表明了使用各种轮班模式的优点和缺点，然而，如何最好地组织护理轮班的问题还没有得到解决。在设计轮班模式模型时，通常会问两个问题：模型中应该包含哪些因素？以及“这些因素的最佳平衡是什么，才能取得好的结果？”用来回答这些问题的数据最好来自不同的来源。此外，由于因素之间的复杂关系，需要仔细的分析和模型测试。本项目拟通过四个阶段来回答这些问题并应用这些考虑。首先，将完成文献综述，以确定传统的与换班相关的因素和当前研究知识的差距。其次，将与护理人员和患者进行访谈，以了解真实世界的背景和日程安排偏好。第三，将对包含NHS工作人员/患者数据的大型数据集进行分析，以揭示班次变量和相关结果之间的重要关系。最后，从这些阶段获得的信息将与先进的建模技术相结合，最终产生一个以证据为基础并适用于实际情况的轮班模式系统。

Nurses form the largest group of NHS staff, with most providing care in 24-hour settings. Theorganisation of this workforce, which includes the designing of shift patterns, has a profound impact onpatient care. Shifts can be organised in many ways (e.g., 8-hour vs. 12-hour shifts), depending on thedesired balance of outcomes like costs, patient safety, and staff wellbeing. Previous research has shownthe benefits and drawbacks of using various shift patterns, however, the problem of how 'best' toorganise nursing shifts is not yet solved.When designing shift pattern models, two questions are usually asked: "What factors should be includedin the model?" and "What is the best balance of these factors so that good outcomes are achieved?" Thedata used to answer these questions should ideally come from diverse sources. Also, because of thecomplex relationships among factors, careful analysis and model testing is required. This projectproposes to answer these questions and apply these considerations through four phases.First, a literature review will be completed to identify conventional shift-related factors and current gapsin research knowledge. Second, interviews with nursing staff and patients will be undertaken tounderstand real-world contexts and scheduling preferences. Third, analysis of a large dataset with NHSstaff/patient data will be performed to uncover important relationships between shift variables andrelevant outcomes. Finally, the information gained from these phases will be combined with advancedmodelling techniques, ultimately resulting in a shift pattern system that is evidence-based and applicableto practical settings.