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).

项目概要 高护理工作量对护理质量、患者安全以及护士的福祉和工作满意度构成威胁。 工作负载——缺乏普遍接受的定义——是一个复杂的多维结构， 受外部任务要求以及环境、组织和心理因素的影响。 在新生儿重症监护病房 (NICU) 中，管理高工作量的重要性最为明显。 危重新生儿由于其不成熟和脆弱，极易发生医源性事件。 工作量与新生儿安全不良结局发生率增加直接相关。 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进展缓慢， 可扩展的工作量测量系统，或其他健康信息技术干预措施，以改善 主要是传统的护理工作量管理工具。 使用单位级别（例如，人员配置比率）或患者级别（例如，敏锐度）数据来测量和预测工作量 比人为因素工程师 (HFE) 建议的四个工作负载级别收集的数据 - 单位、 因此，当前的工具低估了护士和患者所经历的工作量。 并非旨在识别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保健微系统而承受的工作量 情境工作量受性能障碍（即延迟、中断等）的影响最大。 本地工作环境，可以应用于单位、工作或患者层面。最重要的是，它具有诊断性。 迄今为止，情景工作量已经得到了改善。 使用主观调查进行测量，这会干扰工作，因此难以融入实践。 范德比尔特大学医学中心 (VUMC) 与约翰霍普金斯大学 (JHU) 合作， 将采用以人为本的系统工程设计流程来设计、开发和验证 来自易于访问的电子健康的 NICU 护理工作量的新多层次模型 经验证的模型将成为未来基于 EHR 的临床的基础。 决策支持（CDS）工具将跟踪注册护士的实时工作量，预测近期的工作量 术语未来单位工作量，并指导工作量减少和平衡项目的干预措施。 三个具体目标是： 目标 1. 对 NICU 护理进行基于 HFE 的全面分析 目标 2. 设计和开发实时多变量工作负载模型，目标 3. 验证 VUMC 的实时工作负载模型 (A) 并确定该模型的普遍性 外部医院的模型 (B)。