ED / hospital crowding is a major public health problem that leads to degradation in both process and outcome measures across a wide range of health conditions, including acute cardiac care, care for the elderly, pneumonia, pain management, pediatric care, and public health screening. The crowding problem is an example of complex social behavior that emerges from the interaction of individual elements (patients, providers, resources, policies, practices, health conditions, and others) of the system. The crowding problem has exhibited policy resistance: despite being a source of concern for 20 years, it continues worsen. Even more insidiously, many current proposed solutions may have feedbacks that exacerbate the problem in a vicious cycle. Because of its dynamic complexity, delayed feedback loops, and social- behavioral components, the problem seems ideally suited to a system dynamics approach. For example, a system dynamics understanding of crowding would be useful in the following ways: * Developing early warning signals of and responses to 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, i.e., that might provide short term relief but ultimately make the overall problem worse. The broad, overall objective of this project is use system dynamics modeling to study the problem of emergency department (ED) and hospital crowding in order to develop theory and inform departmental, organizational, regional, and societal policies and interventions aimed at alleviating it. A trans-disciplinary research team comprising scientists with expertise in the behavioral and social sciences as well as in computational modeling and systems thinking will use a single healthcare organization that has experienced severe crowding problems as a test site for the model development. The team will construct system dynamic models of the ED - hospital crowding problem, tightly grounded in the individual and collective behavior of people in a focal ED. These models will focus on ordinary operations, i.e., not external disaster scenarios. The models will study the ways in which crowded EDs experience perturbations to routine operations, how these perturbations occasion multi-level responses to cope and recover, and the role of resilience in the behavior of the system. The models will be used for exploration and experimentation to identify characteristic behaviors, evaluate potential interventions, and identif leverage points and critical variables supporting resilient performance. The project aims to use the system dynamics models to develop theory to inform our understanding of how the ED, in the context of the broader healthcare and emergency response system, adapts to varying demands for service and the consequences of this adaptive behavior. It would thus be most suitable for NIGMS as primary funder, with the NIMH as secondary.
ED - hospital crowding affects roughly 110 million Americans per year, and it 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 build theory and to inform management and policy by better identifying leverage points, characterizing potentially useful and potentially counterproductive interventions.
