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Disaster Metrics: Quantitative Benchmarking of Hospital Surge Capacity in Trauma-Related Multiple Casualty Events
- Jamil D. Bayram, Shawki Zuabi, Italo Subbarao
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- Journal:
- Disaster Medicine and Public Health Preparedness / Volume 5 / Issue 2 / June 2011
- Published online by Cambridge University Press:
- 08 April 2013, pp. 117-124
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- Article
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Objectives: Hospital surge capacity in multiple casualty events (MCE) is the core of hospital medical response, and an integral part of the total medical capacity of the community affected. To date, however, there has been no consensus regarding the definition or quantification of hospital surge capacity. The first objective of this study was to quantitatively benchmark the various components of hospital surge capacity pertaining to the care of critically and moderately injured patients in trauma-related MCE. The second objective was to illustrate the applications of those quantitative parameters in local, regional, national, and international disaster planning; in the distribution of patients to various hospitals by prehospital medical services; and in the decision-making process for ambulance diversion.
Methods: A 2-step approach was adopted in the methodology of this study. First, an extensive literature search was performed, followed by mathematical modeling. Quantitative studies on hospital surge capacity for trauma injuries were used as the framework for our model. The North Atlantic Treaty Organization triage categories (T1-T4) were used in the modeling process for simplicity purposes.
Results: Hospital Acute Care Surge Capacity (HACSC) was defined as the maximum number of critical (T1) and moderate (T2) casualties a hospital can adequately care for per hour, after recruiting all possible additional medical assets. HACSC was modeled to be equal to the number of emergency department beds (#EDB), divided by the emergency department time (EDT); HACSC = #EDB/EDT. In trauma-related MCE, the EDT was quantitatively benchmarked to be 2.5 (hours). Because most of the critical and moderate casualties arrive at hospitals within a 6-hour period requiring admission (by definition), the hospital bed surge capacity must match the HACSC at 6 hours to ensure coordinated care, and it was mathematically benchmarked to be 18% of the staffed hospital bed capacity.
Conclusions: Defining and quantitatively benchmarking the different components of hospital surge capacity is vital to hospital preparedness in MCE. Prospective studies of our mathematical model are needed to verify its applicability, generalizability, and validity.
(Disaster Med Public Health Preparedness. 2011;5:117–124)
A Defining Aspect of Human Resilience in the Workplace: A Structural Modeling Approach
- George S. Everly, Jr, Jeanettte A. Davy, Kenneth J. Smith, Jeffrey M. Lating, Frederick C. Nucifora, Jr
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- Journal:
- Disaster Medicine and Public Health Preparedness / Volume 5 / Issue 2 / June 2011
- Published online by Cambridge University Press:
- 08 April 2013, pp. 98-105
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- Article
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Objectives: It has been estimated that up to 90% of the US population is exposed to at least 1 traumatic event during their lifetime. Although there is growing evidence that most people are resilient, meaning that they have the ability to adapt to or rebound from adversity, between 5% and 10% of individuals exposed to traumatic events meet criteria for posttraumatic stress disorder. Therefore, identifying the elements of resilience could lead to interventions or training programs designed to enhance resilience. In this article, we test the hypothesis that the effects of stressor conditions on outcomes such as job-related variables may be mediated through the cognitive and affective registrations of those events, conceptualized as subjective stress arousal.
Methods: The subjects were 491 individuals employed in public accounting, who were sampled from a mailing list provided by the American Institute of Certified Public Accountants. The stressors used in this study were role ambiguity, role conflict, and role overload and the outcome measures were performance, turnover intentions, job satisfaction, and burnout. Stress arousal was measured using a previously developed stress arousal scale. We conducted a series of 2 EQS structural modeling analyses to assess the impact of stress arousal. The first model examined only the direct effects from the role stressors to the outcome constructs. The second model inserted stress arousal as a mediator in the relations between the role stressors and the outcomes.
Results: The results of our investigation supported the notion that subjective stress arousal provides greater explanatory clarity by mediating the effects of stressors upon job-related outcome. Including stress arousal in the model provided a much more comprehensive understanding of the relation between stressor and outcomes, and the contribution of role ambiguity and role conflict were better explained.
Conclusions: By understanding these relations, anticipatory guidance and crisis intervention programs can be designed and implemented to enhance human resilience. These data could serve to improve training programs for these “at risk” professional groups or even the population as a whole.
(Disaster Med Public Health Preparedness. 2011;5:98–105)