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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’s emergency department.Study DesignRepresentative randomized sample of 1,443 adult patients triaged ESI levels 4–5. 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 Findings70.6 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.ConclusionsInterventions 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.

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.

This study aims to assess the vulnerability of populations to storm surge flooding in 12 coastal localities of Virginia, USA. Population vulnerability is assessed by way of 3 physical factors (elevation, slope, and storm surge category), 3 built-up components (road availability, access to hospitals, and access to shelters), and 3 household conditions (storm preparedness, financial constraints to recovering from severe weather events, and health fragility). Fuzzy analysis is used to generate maps illustrating variation in several types of population vulnerability across the region. When considering physical factors and household conditions, the most vulnerable neighborhoods to sea level rise and storm surge flooding are largely found in urban areas. However, when considering access to critical infrastructure, we find rural residents to be more vulnerable than nonrural residents. These detailed assessments can inform both local and state governments in catastrophic planning. In addition, the methodology may be generalized to assess vulnerability in other coastal corridors and communities. The originality is highlighted by evaluating socioeconomic conditions at refined scale, incorporating a broader range of human perceptions and predispositions, and employing a geoinformatics approach combining physical, built-up, and socioeconomic conditions for population vulnerability assessment. Integr Environ Assess Manag 2016;12:500-509. © 2015 SETAC