Decision support for hospital evacuation and emergency response

Bish, Douglas R.; Agca, Esra; Glick, Roger

doi:10.1007/s10479-011-0943-y

Cited by 51 publications

(26 citation statements)

References 12 publications

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“…In this case, in spite of the mothers' genuine intentions, their involvement in the emergency operations made them over-react to the circumstances, at the risk of jeopardizing the well-being of their children, who needed to be evacuated in safe conditions. Time is one of the most compelling issues with emergency management in healthcare critical infrastructures, as demonstrated in a number of eminent cases reported in the literature (Bish et al, 2014;Schultz et al, 2007). The literature defines response time as the 'time required by the emergency services to reach the incident point after getting incident information' (Bandyopadhyay & Singh, 2016, p. 138).…”

Section: Implementation and Response Stagementioning

confidence: 99%

“…(Sullivant, 2007, p. 538). As a consequence, the amount of disaster planning and emergency preparation that modern hospitals are required to develop is significant (Bish, Agca, & Glick, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Planning and preparation UK healthcare emergency planning needs further integration of 'soft' and 'hard' resources. (Bish et al, 2014) All Evacuation models Implementation and response A model to evacuate critical patients in an emergency situation. (Chavez & Binder, 1996) Earthquake Treatment of mass casualties All Emergency planning in hospitals is effectively complemented by training, communication and resource allocation.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of best practices for emergency response and recovery at a large hospital: A fire emergency case study

et al. 2017

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This paper illustrates a study conducted into the managerial practices implemented to mitigate the consequences of a major fire emergency and to promptly restore normal business operations at a large pediatric hospital. Stemming from prior research on crisis response and recovery in critical infrastructures, this investigation demonstrates that factors such as the complexity of the underlying stakeholder networks, the vulnerability of the involved actors, and several temporal and spatial constraints, all contribute in hampering the intervention of crisis managers. In these situations, relying on consolidated best practices may enable more rapid response and more adequate recovery.This study adopts a qualitative approach to build a retrospective case study that highlights the crucial issues that healthcare crisis managers are requested to face when exposed to thorny work conditions: presence of numerous actors from the public and the private sector, involvement of organizations with contrasting interests, need for a balance among public health, cost containment and legitimacy, etc. The findings of the present investigation expand the theoretical knowledge on the dynamics that characterize crises occurring at critical infrastructures and provide practical recommendations for healthcare emergency managers to improve their response to, and recovery from, major fire emergencies.

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Section: Implementation and Response Stagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implementation of best practices for emergency response and recovery at a large hospital: A fire emergency case study

et al. 2017

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“…Bish et al. () presented a model to determine patient allocation strategies for transporting patient from evacuating hospitals to a set of potential receiving hospitals. They considered two objective functions, one of them aims to minimize the evacuation risk and the other one aims to minimize the sum of the cumulative threat risk for the patients who are not evacuated during the time period.…”

Section: Introductionmentioning

confidence: 99%

A robust possibilistic programming approach to multiperiod hospital evacuation planning problem under uncertainty

Rabbani

Zhalechian

Farshbaf‐Geranmayeh

2016

Int Trans Operational Res

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In this paper, a biobjective programming model is developed to address the hospital evacuation problem under uncertainty. It aims to concurrently minimize the total evacuation time and the total weighted number of unevacuated patients in each period. The presented model considers two types of patients and three transportation modes. Moreover, the evacuating hospitals are divided into two groups. In the first group, it is not possible to send vehicles to the evacuating hospitals due to the poor road condition or congestion, whereas there is no such limitation in the second group. A robust possibilistic programming approach is adopted to deal with the inherent uncertainty in the input data. To cope with the computational complexity of the problem, two well-known metaheuristic algorithms are developed to solve the large-sized problems. Finally, several computational experiments and sensitivity analyses are conducted and the results are analyzed.

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“…18 The Human Evacuation Transportation Model seeks to minimize shelter-in-place and evacuation risks by calculating optimal transportation strategies for patients that vary according to care requirements and criticality. 19 Arboleda et al developed network flow models that represent infrastructure networks' operation and restoration, as well as the ability of these infrastructures to provide power and other services to hospitals. 20 Although each of these models can provide valuable information to emergency planners and hospital administrators, key gaps still exist in this body of hospital evacuation models.…”

Section: Discussionmentioning

confidence: 99%

Modeling Evacuation of a Hospital without Electric Power

Vugrin

Verzi

Finley

et al. 2015

Prehosp. Disaster med.

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Hospital evacuations that occur during, or as a result of, infrastructure outages are complicated and demanding. Loss of infrastructure services can initiate a chain of events with corresponding management challenges. This report describes a modeling case study of the 2001 evacuation of the Memorial Hermann Hospital in Houston, Texas (USA). The study uses a model designed to track such cascading events following loss of infrastructure services and to identify the staff, resources, and operational adaptations required to sustain patient care and/or conduct an evacuation. The model is based on the assumption that a hospital's primary mission is to provide necessary medical care to all of its patients, even when critical infrastructure services to the hospital and surrounding areas are disrupted. Model logic evaluates the hospital's ability to provide an adequate level of care for all of its patients throughout a period of disruption. If hospital resources are insufficient to provide such care, the model recommends an evacuation. Model features also provide information to support evacuation and resource allocation decisions for optimizing care over the entire population of patients. This report documents the application of the model to a scenario designed to resemble the 2001 evacuation of the Memorial Hermann Hospital, demonstrating the model's ability to recreate the timeline of an actual evacuation. The model is also applied to scenarios demonstrating how its output can inform evacuation planning activities and timing.

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Decision support for hospital evacuation and emergency response

Cited by 51 publications

References 12 publications

Implementation of best practices for emergency response and recovery at a large hospital: A fire emergency case study

Implementation of best practices for emergency response and recovery at a large hospital: A fire emergency case study

A robust possibilistic programming approach to multiperiod hospital evacuation planning problem under uncertainty

Modeling Evacuation of a Hospital without Electric Power

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