System dynamics modeling of emergency department and hospital crowding

描述(由申请人提供)：急诊科/医院拥挤是一个主要的公共卫生问题，在各种情况下(例如，急性心脏护理、老年人护理、肺炎、疼痛管理、儿科护理和公共健康筛查)，导致过程和结果指标的退化。拥挤问题已显示出“政策阻力”；尽管20年来一直是一个令人担忧的问题来源，但它仍在继续恶化，目前的许多提案都存在反馈，导致问题恶化，形成恶性循环。由于其动态复杂性、延迟的反馈回路和社会行为组件，该问题非常适合系统动力学方法。例如，对拥挤的系统动力学理解将有助于：“开发潜在过度拥挤危机的早期预警能力”，确定用于管理患者需求或组织应对能力的动态和意外变化的杠杆点，确定应避免的潜在功能失调的干预措施，即，可能提供短期缓解但最终使整体问题更加严重的干预措施。该项目广泛的总体目标是使用系统科学方法，特别是系统动力学建模，研究急诊科(ED)和医院拥挤的问题，以便为旨在缓解这一问题的部门、组织、地区和社会政策和干预措施提供信息。该项目将聘请一个由组织利益相关者和系统科学专家组成的团队，根据经历过严重拥挤问题的单一医疗组织的数据和经验，构建急诊/医院拥挤问题的系统动力学模型。这些模型将侧重于普通业务，即不是外部灾难情景。然后，我们将使用模型进行探索和实验，以确定特征行为、评估潜在干预措施，并确定支持弹性绩效的杠杆点和关键变量。这些模型将使用急性心脏护理和老年人护理作为具体的“示踪器”来评估绩效。急性心脏护理是这一角色的理想之选，因为它是严重的，依赖高质量的紧急护理才能获得最佳结果，对拥挤造成的退化敏感，对公共卫生利益重大，是紧急护理人员和卫生保健组织使命的核心，并有良好的过程和结果衡量标准。另一种潜在的跟踪条件是照顾老年人，他们在几个方面受到急诊室/医院拥挤的不成比例的影响(例如，在拥挤的情况下无法获得护理，在走廊或其他非标准护理空间“寄宿”，以及提前出院为新入院腾出空间)。因此，它最适合NHLBI作为主要资助者，NIA作为次要资助者。 公共卫生相关性：急诊医院拥挤每年影响大约1.1亿美国人，并与降低护理质量、增加发病率和死亡率有关。尽管采取了许多措施来控制拥挤，但在过去的20年里，拥挤的情况一直在增加。这个项目将把一种新的方法应用于拥挤的研究，通过更好地确定杠杆点，并确定潜在有用和潜在适得其反的干预措施，为管理层和政策提供信息。

DESCRIPTION (provided by applicant): Emergency department / hospital crowding is a major public health problem that leads to degradation in both process and outcome measures in a variety of conditions (eg, acute cardiac care, care for the elderly, pneumonia, pain management, pediatric care, and public health screening). The crowding problem has shown "policy resistance"; despite being a source of concern for 20 years, it continues worsen, and many current proposals have feedbacks that exacerbate the problem in a vicious cycle. Because of its dynamic complexity, delayed feedback loops, and social-behavioral components, the problem is ideally suited to a system dynamics approach. For example, a system dynamics understanding of crowding would be useful in: " Developing early warning capabilities of a potential overcrowding crisis " Identifying leverage points for managing dynamic and unexpected changes in patient demand or organizational capacity to respond" Identifying potentially dysfunctional interventions to be avoided, ie, that might provide short term relief but ultimately make the overall problem worse. The broad, overall objective of this project is use a systems science approach, specifically system dynamics modeling, to study the problem of emergency department (ED) and hospital crowding in order to inform departmental, organizational, regional, and societal policies and interventions aimed at alleviating it. The project will engage a team of organizational stakeholders and system science experts to construct system dynamic models of the ED / hospital crowding problem, based on data and experience at a single healthcare organization that has experienced severe crowding problems. These models will focus on ordinary operations, i.e., not external disaster scenarios. We will then use the models for exploration and experimentation to identify characteristic behaviors, evaluate potential interventions, and identify leverage points and critical variables supporting resilient performance. The models will use acute cardiac care and care for the elderly as specific 'tracers' to evaluate performance. Acute cardiac care is ideal for this role, because it is serious, depends on high quality emergency care for optimal results, is sensitive to degradation due to crowding, is of great public health interest, is central to the mission of emergency care workers and health care organizations, and has good process and outcome measures. Another potential tracer condition is care for the elderly, who are disproportionately affected by ED / hospital crowding in several ways (e.g., impaired access to care in crowding situations, 'boarding' in hallways or other non-standard care spaces, and premature discharge from the hospital to make room for new admissions). It would thus be most suitable for the NHLBI as primary funder, and for the NIA as secondary. PUBLIC HEALTH RELEVANCE: ED - hospital crowding affects roughly 110 million Americans per year, and is associated with decreased quality of care and increased morbidity and mortality. Crowding has been increasing over the past 2 decades, despite many efforts to control it. This project will apply a new method to the study of crowding to inform management and policy by better identifying leverage points, and characterizing potentially useful and potentially counterproductive interventions.