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

实时测量 NICU 护士的工作量，以改善工作量管理和患者安全

• 批准号: 10611477
• 负责人: DANIEL Joseph FRANCE
• 金额: $ 39.91万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10611477
• 关键词: Realtime; Measurement; Situational; Workload; NICU

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).

项目摘要 高护士工作量是对护理质量，患者安全以及护士的福祉和工作满意度的威胁。 工作量 - 缺乏普遍接受的定义 - 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。 管理高工作量的重要性无比新生儿重症监护病房（NICUS）更多的证据。 重病的新生儿由于不成熟和脆弱而高度容易受到医源事件的影响，并且很高 工作量与不良新生儿安全结果的增加直接相关。 尽管有证据和需求，但患者安全研究人员开发多层次模型的缓慢， 可扩展的工作量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。传统护士工作量管理工具主要是 使用单位级别（例如人员比率）或患者级别（例如，敏锐度）数据测量和预测工作量 比在人为因素工程师（HFES）建议的四个工作负载级别收集的数据 - 工作，耐心和情况。结果，当前的工具无法避免护士和 并非旨在识别可造成护士工作量最大的可变微系统因素。 护士工作量研究的有希望的发展是越来越强调衡量 情境工作量最能解释护士由于医疗保健微系统所经历的工作量 设计。情境工作负载最受绩效障碍（即延迟，中断等）影响 本地工作环境，可以在部门，工作或患者级别应用。最重要的是，它是诊断 基本的促成因素，因此可用于改进。迄今为止，情境工作量有 使用正在工作的主观调查来测量，因此很难将其整合到实践中。 范德比尔特大学医学中心（VUMC），合作约翰·霍普金斯大学（JHU）， 将采用以人为中心的系统设计过程来设计，开发和验证 NICU护士工作负载的新型多层次模型来自易于访问的电子健康 记录（EHR）数据。经过验证的模型将是未来基于EHR的临床的基础 决策支持（CD）工具将跟踪注册护士的实时工作量，预测接近 定期未来的单位工作量，并指导减少工作量和平衡干预措施。项目的 三个具体的目标是：目标1。对NICU护士进行全面的基于HFE的分析 工作量；目标2。设计和开发实时多变量工作负载模型并瞄准3。 验证VUMC（a）的实时工作负载模型，并确定 外部医院的模型（b）。