Emergency Department Frequent Utilization for Non-Emergent Presentments: Results from a Regional Urban Trauma Center Study

ObjectivesFirst, to test a model of the drivers of frequent emergency department utilization conceptualized as falling within predisposing, enabling, and need dimensions. Second, to extend the model to include social networks and service quality as predictors of frequent utilization. Third, to illustrate the variation in thresholds that define frequent utilization in terms of the number of emergency department encounters by the predictors within the model. Data SourcePrimary data collection over an eight week period within a level-1 trauma urban hospital\u27s emergency department. Study Design Representative randomized sample of 1,443 adult patients triaged ESI levels 4\u275. Physicians and research staff interviewed patients as they received services. Relationships with the outcome variable, utilization, were tested using logistic regression to establish odds-ratios. Principal Findings 70.6 percent of patients have two or more, 48.3 percent have three or more, 25.3 percent have four or more, and 14.9 percent have five or more emergency department visits within 12 months. Factors associated with frequent utilization include gender, race, poor mental health, mental health drugs, prescription drug abuse, social networks, employment, perceptions of service quality, seriousness of condition, persistence of condition, and previous hospital admittance. Conclusions Interventions targeting associated factors will change global emergency department encounters, although the mutability varies. Policy interventions to address predisposing factors such as substance abuse or access to mental health treatment as well as interventions that speak to enabling factors such as promoting the resiliency of social networks may result in decreased frequency of emergency department utilization

Disparate Health Implications Stemming From the Propensity of Elderly and Medically Fragile Populations to Shelter in Place During Severe Storm Events

Chronic conditions, disability limitations (mobility, cognitive, and sensory), and the need for assistance with activities of daily living are characteristics of elderly and medically fragile populations. Theory suggests that households with these vulnerability attributes are more likely to suffer storm-induced adverse and prolonged health consequences and, therefore, ought to evidence an increased propensity to evacuate prior to a severe storm event. Yet despite being more sensitive to storm disruption, the elderly and medically fragile populations are only slightly more likely to evacuate in the face of impending storms. This suggests, for these groups, there may be other factors such as income, transportation, and social and familial networks that may be attenuating the propensity to evacuate. The public health significance is found in that the propensity to shelter in place, rather than evacuate, may contribute to disparate health outcomes. Data illustrating the prevalence of these conditions and the propensity to shelter in place are derived from a sampling of Hampton Roads households following the 2011 Hurricane Irene

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making

A System Dynamics Model for Simulating Ambulatory Health Care Demands

Introduction: This article demonstrates the utility of the system dynamics approach to model and simulate US demand for ambulatory health care service both for the general population and for specific cohort subpopulations over the 5-year period, from 2003 to 2008. A system dynamics approach that is shown to meaningfully project demand for services has implications for health resource planning and for generating knowledge that is critical to assessing interventions. Methods: The study uses a cohort-component method in combination with structural modeling to simulate ambulatory health care utilization. Data are drawn from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey. Results: The simulation of the total population requiring ambulatory services between 2003 and 2008 is performed to test the functionality and validate the model. Results show a close agreement between the simulated and actual data; the percent error between the two is relatively low, 1.5% on average. In addition, simulations of purposively selected population subsets are executed (men, 18–24 years of age, white, African American, Hispanic, and insurance coverage), resulting in error between simulated and actual data, which is 7.05% on average. Conclusions: The proposed model demonstrates that it is possible to represent and mimic, with reasonable accuracy, the demand for health care services by the total ambulatory population and the demand by selected population subsets. This model and its simulation demonstrate how these techniques can be used to identify disparities among population subsets and a vehicle to test the impact of health care interventions on ambulatory utilization. A system dynamics approach may be a useful tool for policy and strategic planners

Identifying Factors that Influence Terrorist Decisions and Target Selection

Currently, the U.S. Department of Homeland Security (DHS) elicits probabilistic judgements from the intelligence community on actions terrorists may take to attack the continental U.S. For example, how likely is the adversary to choose agent \u27x\u27 over \u27y\u27 or target \u27a\u27 over target \u27b\u27? Eliciting these types of judgements is difficult and time consuming. The National Academies and others have suggested that a better approach may be to elicit information on adversary\u27s preferences, perceptions, and capabilities and use this information to calculate probabilities of interest to DHS. Some terrorist groups are thinking about using weapons of mass destruction (WMD), each with its own values, perceptions of reality, and capabilities. This presentation details the findings on the factors & relationships among factors that lead to a terrorist decision to initiate an attack against the continental U.S. as well as target selection. To accomplish this, we assembled international experts in WMD, adversary modeling, political science, terrorism, psychiatry, social sciences as well as experts from national laboratories, the Commonwealth of Virginia State Fusion Center, and Hampton Roads Emergency Management. This paper provides a summary of the findings from an Adaptive Adversary Workshop. In this paper, we provide an overview of the motivation for and design of the workshop as well as 19 emerging themes. The purpose of the workshop was to illicit expert opinions on terrorist decision-making and target selections in an effort to improve our understanding of adversaries (individuals, local/regional groups, transnational groups, states) who may initiate a bioterrorism attack in the from of releasing biological agents upon U.S. interests. Furthermore, these expert opinions are intended to be used to inform Bayesian Belief Network (BBN) models of terrorist networks. These models must be informed or populated with substantive information about the intelligent and adaptive adversary who may initiate an attack. To this end, a conceptual framework, informed broadly by the social sciences community, is intended to capture the terrorists\u27 motivations, methods, and decision calculi