Realtime Measurement of Situational Workload in NICU Nurses to Improve Workload Management and Patient Safety

项目总结 护理工作量大是对护理质量、病人安全、护士福祉和工作满意度的威胁。 工作量--缺乏一个普遍接受的定义--是一个复杂的多维结构， 受外部任务需求以及环境、组织和心理因素的影响。这个 管理高工作量的重要性在新生儿重症监护病房(NICU)中最为明显。 危重新生儿由于不成熟和脆弱，极易受到医源性事件的影响， 工作量与新生儿不良安全结局发生率的增加直接相关。 尽管有证据和需求，患者安全研究人员在开发多层次模型方面一直进展缓慢， 可扩展的工作负载测量系统或其他健康信息技术干预措施，以改进 工作量管理和患者安全。传统的护理工作量管理工具主要 而是使用单位级别(例如，人员配置比率)或患者级别(例如，敏锐度)数据来衡量和预测工作量 比人因工程师(HFES)建议的四个工作量级别收集的数据更多-单位， 工作、耐心和处境。因此，目前的工具低估了护士和 不是设计用来确定对护理工作量影响最大的可变微系统因素。 护理工作量研究的一个有希望的发展是越来越重视测量 情景工作量最能解释护士因医疗微系统而经历的工作量 设计。情景工作负载最受性能障碍(即延迟、中断等)的影响在 本地工作环境，可应用于单位、工作或患者级别。最重要的是，它具有诊断性 潜在的促成因素，因此可采取行动加以改进。到目前为止，情景工作负载已经 使用主观调查来衡量，这会干扰工作，因此很难融入实践。 范德比尔特大学医学中心(VUMC)，与约翰霍普金斯大学(JHU)合作， 将采用以人为中心的系统工程设计流程来设计、开发和验证 电子健康衍生的NICU护理工作量的多层次新模式 记录(EHR)数据。经过验证的模型将为未来基于电子病历的临床奠定基础 决策支持(CDS)工具，将跟踪注册护士的实时工作量，预测近 评估未来单位的工作量，并指导减少工作量和平衡干预。该项目的 三个具体目标是：目标1.对NICU护理进行全面的HFE分析 工作负荷；目标2。设计和开发实时多变量工作负荷模型和目标3。至 验证VUMC(A)的实时工作负载模型，并确定 外部医院的模特(B)。

PROJECT SUMMARY High nursing workload is a threat to care quality, patient safety, and nurses’ well-being and job satisfaction. Workload – which lacks a universally accepted definition - is a complex multi-dimensional construct that is affected by external task demands and environmental, organizational, and psychological factors. The importance of managing high workload is nowhere more evident than in neonatal intensive care units (NICUs). Critically ill neonates are highly vulnerable to iatrogenic events due to their immaturity and fragility, and high workload has been directly associated with increased incidence of adverse neonatal safety outcomes. Despite the evidence and need, patient safety researchers have been slow to develop multi-level models, scalable workload measurement systems, or other health information technology interventions to improve workload management and patient safety. Conventional nursing workload management tools predominantly measure and predict workload using unit-level (e.g., staffing ratios) or patient-level (e.g., acuity) data rather than data collected across the four levels of workload recommended by human factors engineers (HFEs) - unit, job, patient, and situation. As a result, current tools under-measure the workload experienced by nurses and are not designed to identify mutable microsystem factors that contribute most to nursing workload. A promising development in nursing workload research is the increasing emphasis on measuring situational workload which best explains the workload experienced by nurses due to healthcare microsystem design. Situational workload is most affected by performance obstacles (i.e., delays, interruptions, etc.) in the local work environment and can be applied at the unit, job, or patient-levels. Most importantly, it is diagnostic of underlying contributory factors and therefore actionable for improvement. To date, situational workload has been measured using subjective surveys which are work-interrupting, thus difficult to integrate into practice. Vanderbilt University Medical Center (VUMC), in collaboration Johns Hopkins University (JHU), will employ a systems engineering human-centered design process to design, develop, and validate new multi-level models of NICU nursing workload derived from readily accessible electronic health record (EHR) data. The validated models will be the foundation for a future EHR-based clinical decision support (CDS) tool that will track the real-time workload of registered nurses, predict near- term future unit workload, and guide workload reduction and balancing interventions. The project’s three Specific Aims are: Aim 1. To conduct a comprehensive HFE-based analysis of NICU nursing workload; Aim 2. To design and develop real-time multivariable workload models and Aim 3. To validate the real-time workload models at VUMC (A) and to determine the generalizability of the models at an external hospital (B).