System dynamics modeling of emergency department and hospital crowding

描述（由申请人提供）：急诊室/医院拥挤是一个主要的公共卫生问题，导致各种情况下的过程和结局指标下降（例如，急性心脏病护理、老年人护理、肺炎、疼痛管理、儿科护理和公共卫生筛查）。 拥挤问题已显示出“政策阻力”;尽管20年来一直是一个令人关切的问题，但它仍在继续恶化，目前的许多建议的反馈意见使问题恶化，形成恶性循环。 由于其动态的复杂性，延迟反馈回路，和社会行为的组成部分，这个问题是非常适合系统动力学的方法。 例如，对拥挤的系统动力学理解将有助于：“发展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响应能力的动态和意外变化的杠杆点”确定要避免的潜在功能失调的干预措施，即可能提供短期 但最终会使整个问题变得更糟。该项目的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（艾德）和医院拥挤的问题，以告知部门，组织，区域，该项目将邀请一个由组织利益相关者和系统科学专家组成的小组，艾德/医院拥挤问题，基于一家经历过严重拥挤问题的医疗机构的数据和经验。 这些模型将侧重于普通业务，即，而不是外部灾难场景。 然后，我们将使用这些模型进行探索和实验，以确定特征行为，评估潜在的干预措施，并确定支持弹性性能的杠杆点和关键变量。 这些模型将使用急性心脏病护理和老年人护理作为特定的“示踪剂”来评估性能。 急性心脏病护理是这一角色的理想选择，因为它是严重的，依赖于高质量的急诊护理以获得最佳结果，对由于拥挤而导致的退化敏感，具有很大的公共卫生利益，是急诊护理工作者和医疗保健组织的使命的核心，并且具有良好的过程和结果测量。 另一个潜在的示踪条件是照顾老年人，他们在几个方面受到艾德/医院拥挤的不成比例的影响（例如，在拥挤的情况下，难以获得护理，在走廊或其他非标准护理空间“寄宿”，过早出院为新入院者腾出空间）。 因此，最适合由国家HLBI作为主要供资者，由国家投资局作为次要供资者。 公共卫生相关性：艾德-医院拥挤每年影响大约1.1亿美国人，并与护理质量下降和发病率和死亡率增加有关。 过去20年来，尽管作出了许多努力来控制拥挤现象，但拥挤现象仍在增加。本项目将采用一种新的方法来研究拥挤现象，通过更好地确定杠杆点，并描述潜在有用和潜在适得其反的干预措施，为管理和政策提供信息。

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.