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 提供者的高工作量对护理质量、患者安全以及提供者的福祉和工作构成威胁 满意缺乏一个普遍接受的定义，它是一个复杂的多维 受外部任务要求以及环境、组织和心理影响的结构 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 单位（NICU）危重新生儿由于其不成熟，极易发生医源性事件， 脆弱性和高临床工作量与不良新生儿 安全结果。 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。传统的工作负载管理工具主要衡量 并使用单元级（例如，人员配备比率）或患者水平（例如，敏锐度）数据而不是数据 在人因工程师（HFE）建议的四个工作量级别（单位，工作， 病人和情况。因此，目前的工具低估了提供商所经历的工作量， 未设计用于识别对提供商工作负载贡献最大的可变微系统因素。 工作负荷研究的一个很有希望的发展是越来越强调测量情境 工作负载，最好地解释了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负载。 情境工作负荷受绩效障碍的影响最大（即，延迟、中断等）在当地 工作环境，并可应用于单位，工作，或病人的水平。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过程来设计、开发和验证 新的多层次模型的NICU护士执业工作量来自容易获得的电子 健康记录（EHR）数据。验证模型将为未来基于电子病历的临床诊断奠定基础 决策支持（CDS）工具，将跟踪NICU提供者的实时工作量，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提供者进行全面的基于HFE的分析 (i.e.,新生儿护理工作量;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）的可推广性。