Measuring NICU Nurse Practitioner Workload in Real-time to Improve Care Quality and Patient Safety

项目总结 提供者的高工作负载对护理质量、患者安全以及提供者的福祉和工作构成威胁 满足感。工作量--缺乏普遍接受的定义--是一个复杂的多维 受外部任务需求以及环境、组织和心理影响的构建 各种因素。管理高工作量的重要性在新生儿重症监护中最为明显。 单元(NICU)。危重新生儿非常容易受到医源性事件的影响，因为他们不成熟和 脆弱性和临床医生的高工作量与不良新生儿发生率的增加直接相关 安全结果。 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。传统的工作负载管理工具主要衡量 并使用单位级(例如，人员配置比率)或患者级(例如，敏锐度)数据而不是数据来预测工作量 通过人为因素工程师(HFES)建议的四个工作负荷级别收集数据--单位、工作、 有耐心，情况也不错。因此，当前的工具低估了提供商所经历的工作量，并且 不是设计用来识别对提供商工作负载贡献最大的可变微系统因素。 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，这最好地解释了临床医生由于医疗保健微系统设计而经历的工作量。 情景工作负载最受性能障碍(即延迟、中断等)的影响在当地 工作环境，并可应用于单位、工作或患者级别。最重要的是，它是诊断 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 新的多层次NICU护士工作负荷模型源自易于访问的电子产品 健康记录(EHR)数据。经过验证的模型将为未来基于eHR的临床奠定基础 决策支持(CDS)工具，将跟踪NICU提供者的实时工作负载，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提供者进行基于HFE的全面分析 (例如，新生儿护理从业者)工作量；目标2.设计和开发实时多变量 工作负荷模型和目标3.验证VUMC(A)的实时工作负荷模型并 确定模型在外部医院的普适性(B)。

PROJECT SUMMARY High provider workload is a threat to care quality, patient safety, and providers’ 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 clinician 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 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 providers and are not designed to identify mutable microsystem factors that contribute most to provider workload. A promising development in workload research is the increasing emphasis on measuring situational workload which best explains the workload experienced by clinicians 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 model of NICU nurse practitioner workload derived from readily accessible electronic health record (EHR) data. The validated model will be the foundation for a future EHR-based clinical decision support (CDS) tool that will track the real-time workload of NICU providers, 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 provider (i.e., neonatal nurse practitioner) 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).