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 高护理工作量对护理质量、病人安全、护士的幸福感和工作满意度构成威胁。 缺乏一个普遍接受的定义，它是一个复杂的多维结构， 受外部任务要求和环境、组织和心理因素的影响。的 管理高工作量的重要性在新生儿重症监护室（NICU）中最为明显。 危重新生儿由于其不成熟和脆弱，极易发生医源性事件， 工作负荷与新生儿安全不良结局发生率的增加直接相关。 尽管有证据和需求，但患者安全研究人员在开发多层次模型方面进展缓慢， 可扩展的工作量测量系统，或其他卫生信息技术干预措施，以改善 工作量管理和患者安全。传统的护理工作量管理工具主要 使用单元级（例如，人员配备比率）或患者水平（例如，敏锐度）数据，而 比在人因工程师（HFE）推荐的四个工作量级别上收集的数据更好， 工作、病人和情况。因此，目前的工具低估了护士的工作量， 并不是设计来识别对护理工作量贡献最大的可变微系统因素。 护理工作量研究的一个有前途的发展是越来越强调测量 情境工作负荷，最好地解释了护士由于医疗微系统而经历的工作负荷 设计情境工作负荷受绩效障碍的影响最大（即，延迟、中断等）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，因此可以采取行动加以改善。到目前为止，情景工作负载 采用主观调查进行衡量，这种调查会打断工作，因此难以纳入实践。 范德比尔特大学医学中心（VUMC）与约翰霍普金斯大学（JHU）合作， 将采用以人为本的系统工程设计流程来设计、开发和验证 新的多层次模式的新生儿重症监护室护理工作量来自随时可用的电子健康 记录（EHR）数据。验证的模型将是未来基于电子病历的临床 决策支持（CDS）工具，将跟踪注册护士的实时工作量，预测近， 确定未来单位的工作量，并指导减少工作量和平衡干预措施。该项目的 三个具体目标是：目标1。对NICU护理进行基于HFE的全面分析 工作量;目标2.设计和开发实时多变量工作量模型和目标3。到 验证VUMC（A）的实时工作负载模型，并确定 外部医院的模特（B）。