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

实时测量 NICU 护士从业人员的工作量，以提高护理质量和患者安全

• 批准号: 10736277
• 负责人: DANIEL Joseph FRANCE
• 金额: $ 68.95万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10736277
• 关键词: Academic Medical Centers; Address; Affect; COVID-19 pandemic; Caring; Collaborations; Communication; Complex; Critical Illness; Data; Data Element; Development; Diagnostic; Dimensions; Dose; Electronic Health Record; Engineering; Environmental Risk Factor; Evaluation Studies; Event; Focus Groups; Foundations; Funding; Future; Growth; Health system; Healthcare; Hospitals; Hour; Human; Human Engineering; Iatrogenesis; Incidence; Interruption; Intervention; Interview; Job Satisfaction; Learning; Maps; Measurement; Measures; Mechanical ventilation; Medication Errors; Modeling; National Institute of Child Health and Human Development; Neonatal; Neonatal Intensive Care Units; Neonatal Nursing; Nosocomial Infections; Nurse Practitioners; Nurses; Observational Study; Occupations; Organ; Patient Care; Patient Self-Report; Patient-Focused Outcomes; Patients; Performance; Perioperative; Personal Satisfaction; Physiology; Play; Process; Provider; Psychological Factors; Public Health; Quality of Care; Recommendation; Research; Research Personnel; Resource Allocation; Risk; Role; Safety; Severities; Shapes; Structure; Surveys; System; Time; Universities; Weight; Work; Workload; clinical decision support; clinical practice; design; environmental stressor; experience; health information technology; human centered design; improved; innovation; microsystems; mortality; multidisciplinary; multilevel analysis; neonatal care; neonatal patient; neonate; patient safety; professional atmosphere; prospective; safety outcomes; support tools; tool; validation studies

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).

项目摘要 高提供者工作量是对护理质量，患者安全和提供者的福祉和工作的威胁 满意。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造 因素。管理高工作量的重要性无比在新生儿重症监护室中更多的证据 单位（NICUS）。重症新生儿由于其不成熟而高度容易受到息护物事件的影响 脆弱性和高临床工作量已与不良新生儿的增加直接相关 安全结果。 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。常规的工作负载管理工具主要是测量 并使用单位级（例如人员配备比）或患者级（例如，敏锐度）数据而不是数据来预测工作量 在人为因素工程师（HFES）推荐的四个级别的工作量中收集 - 单位，工作， 病人和情况。结果，当前工具估计了提供商所经历的工作量，并且是 并非旨在识别可突出的微型系统因素，这对提供商的工作量最大。 工作量研究的有希望的发展是越来越强调衡量情况 工作量最能解释由于医疗保健微系统设计而导致的临床医生所经历的工作量。 情境工作负载最受当地的性能障碍（即延迟，中断等）影响最大 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 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护士从业人员工作负载的新型多层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NICU提供商的实时工作量，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 三个具体目的是：目标1。进行基于HFE的NICU提供商的全面分析 （即新生儿护士从业者）工作量；目标2。设计和开发实时多变量 工作负载模型和目标3。验证VUMC（a）的实时工作负载模型 确定模型在外部医院（B）的普遍性。