Exploratory Study Using Queueing Theory to Improve Nurse Staffing Effectiveness

描述（由申请人提供）：证据表明护士人员配备水平和患者结局之间存在显著的正相关关系。然而，目前还没有科学的方法来确定什么水平的人员配置是最佳的，以实现优质的病人结果。需要进行研究，以确定一种方法来量化不同环境下的护理需求，并将其转化为有效的人员配置水平。该方法应该是可推广的，让任何给定的单位，以确定所需的人员配备水平，以达到质量标准的护士管理人员。将服务的可变需求与响应时间联系起来，以满足给定人员配置水平的需求，是实现这一目标的一种有前途的方法。在许多服务行业和组织中，成功地使用了模型。服务模型是服务系统的数学表示，它将需求的平均到达率和满足这些需求的平均服务时间作为输入，并根据各种性能指标通知人员配置。通过这种方式，决策模型可以告知决策者增加人员配置水平和改善响应时间之间的权衡。这项探索性研究的目的是：1）确定特定单位的时间敏感的护理干预措施（需求）和执行这些措施所需的平均时间（服务时间）; 2）确定特定单位的护理需求量和时间（到达率）; 3）制定可接受的护理延迟的绩效标准; 4）根据排队模型制定和测试注册护士人员配置计划。使用一个骨科护理单位作为测试网站，这些目标将满足使用定性和定量的方法。将以电子方式提供使用评估模型所需的许多定量数据。随着信息技术在医院的使用越来越多，这一建议是及时的，既建立了识别，收集和分析这些重要数据的框架，以及提供了第一个临床试验的使用，以指导护士的人事决策。护理人员配置的评估模型的应用是一个独特的和创新的使用现有的方法在一个新的科学领域的一个例子。此处所述的拟议工作处于早期和概念阶段，因此选择了R21机制。如果本研究的结果表明，一个成功的通知护士人员配置决策，将提出进一步的研究，以测试在多个设置的方法和一个可推广的框架将开发，以协助护士管理者使用的咨询模型在自己的设置。这项研究将是第一次临床试验的使用，指导护士的人事决策的评估方法。这项研究计划的一个长期目标是通过开发一个可推广的框架来提高床边护理服务的质量，该框架用于使用护理理论来告知各种环境中的护士人员配置需求。

DESCRIPTION (provided by applicant): Evidence indicates a significant positive relationship between nurse staffing levels and patient outcomes. Yet there is currently no scientifically based approach to determine what level of staffing is optimal to achieve quality patient outcomes. Research is needed to identify a method to quantify demands for nursing care in varying settings and translate these into effective staffing levels. The method should be generalizable to allow nurse managers for any given unit to determine the required staffing levels to achieve quality standards. Queueing theory, which relates variable demands for service to the response times to meet those demands for a given level of staffing, is a promising methodology to accomplish this goal. Queueing models have been successfully used in many service industries and organizations. A queueing model is a mathematical representation of a service system, which takes as input the average arrival rate of demands, and the average service time to meet those demands and informs staffing based on various performance metrics. In this way, queueing models can inform decision makers on the tradeoffs between increased staffing levels and improved response times. The aims of this exploratory study are to 1) identify unit-specific time-sensitive nursing care interventions (demands) and the average times required to perform them (service times); 2) determine unit-specific volume and timing (arrival rates) for nursing care demands; 3) develop performance standards for acceptable delays for nursing care; and 4) develop and test a registered nurse staffing plan based on queueing models. Using one orthopedic nursing unit as the test site, these aims will be met using qualitative and quantitative methods. Much of the quantitative data needed for the use of queueing models will be available electronically. With increased use of information technology in hospitals, this proposal is timely in both establishing the framework for identifying, collecting and analyzing these important data as well as providing the first clinical test of the use of queueing methodology to guide nurse staffing decisions. The application of queueing models to nurse staffing is an example of a unique and innovative use of an existing methodology in a new scientific area. The proposed work described here is in the early and conceptual stages and therefore, the R21 mechanism was chosen. If the results of this study demonstrate a queueing model to be successful in informing nurse staffing decisions, further research will be proposed to test the methodology in multiple settings and a generalizable framework will be developed to assist nurse managers to use queueing models within their own settings. This study will be the first clinical test of the use of queueing methodology to guide nurse staffing decisions. A long term goal of this program of research is to improve the quality of nursing services at the bedside by developing a generalizable framework for using queueing theory to inform nurse staffing needs across a variety of settings.