Determining optimal treatment rate after a disaster
01 Jul 2014-Journal of the Operational Research Society (Taylor & Francis)-Vol. 65, Iss: 7, pp 1053-1067
TL;DR: To model medical rescue activities, a two-priority non-preemptive S-server, and a finite capacity queueing system is considered, and Pontryagin's minimum principle is used to calculate optimal treatment rates for each priority class.
Abstract: From the standpoint of medical services, a disaster is a calamitous event resulting in an unexpected number of casualties that exceeds the therapeutic capacities of medical services. In these situations, effective medical response plays a crucial role in saving life. To model medical rescue activities, a two-priority non-preemptive S-server, and a finite capacity queueing system is considered. After constructing Chapman–Kolmogorov differential equations, Pontryagin's minimum principle is used to calculate optimal treatment rates for each priority class. The performance criterion is to minimize both the expected value of the square of the difference between the number of servers and the number of patients in the system, and also the cost of serving these patients over a determined time period. The performance criterion also includes a final time cost related to deviations from the determined value of the desired queue length. The two point boundary value problem is numerically solved for different arrival rate patterns and selected parameters.
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TL;DR: The macro level "architectural blue print" of disaster management research is assessed and presented in the hope that it will attract new researchers and motivate established researchers to contribute to this important field.
Abstract: We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/logistics journals. In reviewing these studies, our objective is to assess and present the macro level "architectural blue print" of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision-making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queueing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights into disaster research. Recommendations for future research are provided.
113 citations
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TL;DR: This survey focuses on casualty management (CM), which is one of the actions taken in the response phase of a disaster, and categorizes the existing research papers and case studies in each of these steps to suggest future directions for academics and practitioners.
Abstract: Disasters are usually managed through a four-phase cycle including mitigation, preparedness, response and recovery. The first two phases happen before a disaster and the last two after it. This survey focuses on casualty management (CM), which is one of the actions taken in the response phase of a disaster. Right after a severe disaster strikes, we may be confronted with a large number of casualties in a very short period of time. These casualties are in need of urgent treatment and their survival depends on a rapid response. Therefore, managing resources in the first few hours after a disaster is critical and efficient CM can significantly increase the survival rate of casualties. Uncertainty in the location of a disaster, disruption to transportation networks, scarcity of resources and possible deaths of rescue and medical teams due to the disaster in such situations make it hard to manage casualties. In this survey, we focus on CM for disasters where the following five steps are taken, respectively: (i) Resource dispatching/search and rescue, (ii) on-site triage, (iii) on-site medical assistance, (iv) transportation to hospitals and (v) triage and comprehensive treatment. With a special focus on Operations Research (OR) techniques, we categorize the existing research papers and case studies in each of these steps. Then, by critically observing and investigating gaps, trends and the practicality of the extant research studies, we suggest future directions for academics and practitioners.
35 citations
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TL;DR: In this paper, a location-allocation model that locates alternative care facilities and considers triage and the movement of self-evacuees in devising a casualty allocation plan for catastrophic radiological events was developed.
Abstract: A radiological incident is an event whereby the release of radioactive material leads to significant consequences to people, the environment, and facilities. It has the potential of being catastrophic. We seek to analyze casualty response to such an event by addressing issues such as the creation of surge capacity, casualty prioritization, and the incorporation of self-evacuees in planning. We develop a location-allocation model that locates alternative care facilities and considers triage and the movement of self-evacuees in devising a casualty allocation plan for catastrophic radiological events. The model minimizes the total weighted transportation time of casualties and uses triage results to tactically prioritize casualties, while considering resource limitations. We apply the model to the case study of a radiological dispersal device situation in Los Angeles. With analysis of the resulting optimal plan and sensitivity analyses on the budget of alternative care facilities and on medical center triage capacities, we come up with several rules of thumb for casualty response planning. Our model aims to help central planners respond effectively to radiological incidents and better understand the response supply chain. It can thus help avert deaths and reduce suffering, especially in the current climate, where the increasing threat of terrorism is raising concerns over the next radiological attack being more in the offing than ever.
27 citations
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TL;DR: This methodology will encourage urban city planners to pre-identify CCP locations, and, in the event of a disaster, help them decide on the subset of these CCPs that could be rapidly mobilised for disaster response.
Abstract: In this paper, a Casualty Collection Points (CCPs) location problem is formulated as a two-stage robust stochastic optimization model in an uncertain environment. In this modelling approach, the network design decisions are integrated with the multi-period response operational decisions where the number of casualties with different levels of injuries coming from the affected areas is uncertain. Furthermore, the transportation capacity for the evacuation of casualties to CCPs and hospitals is also uncertain. To solve this complex problem, a robust sample average approximation method with the feasibility restoration technique is proposed, and its efficiency is examined through a statistical validation procedure. We then evaluate the proposed methodology in the backdrop of a hypothetical case of Bhopal gas tragedy (with the same hazard propagation profile) at the present day. We also report the solution robustness and model robustness of 144 instances of the case-study to show the proficiency of our proposed solution approach. Results analysis reveals that our modelling approach enables the decision makers to design a humanitarian logistic network in which not only the proximity and accessibility to CCPs are improved, but also the number of lives lost is decreased. Moreover, it is shown that the proposed robust stochastic optimization approach converges rapidly and more efficiently. We hope that our methodology will encourage urban city planners to pre-identify CCP locations, and, in the event of a disaster, help them decide on the subset of these CCPs that could be rapidly mobilised for disaster response.
14 citations
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TL;DR: This paper constructs a three-stage stochastic programming model to locate alternative care facilities and allocate casualties in response to catastrophic health events and proposes an algorithm, based on Benders decomposition, to generate good solutions fast.
Abstract: Catastrophic health events are natural or man-made incidents that create casualties in numbers that overwhelm the response capabilities of healthcare systems. Proper response planning for such even...
13 citations
References
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TL;DR: The literature is surveyed to identify potential research directions in disaster operations, discuss relevant issues, and provide a starting point for interested researchers.
Abstract: Disasters are large intractable problems that test the ability of communities and nations to effectively protect their populations and infrastructure, to reduce both human and property loss, and to rapidly recover. The seeming randomness of impacts and problems and uniqueness of incidents demand dynamic, real-time, effective and cost efficient solutions, thus making the topic very suitable for OR/MS research. While social sciences and humanities literatures enjoy an abundance of articles on disaster management, the OR/MS community is yet to produce a critical mass. In this paper, we survey the literature to identify potential research directions in disaster operations, discuss relevant issues, and provide a starting point for interested researchers.
1,271 citations
"Determining optimal treatment rate ..." refers background in this paper
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TL;DR: Using techniques of content analysis, this paper reviews optimization models utilized in emergency logistics and identifies research gaps identified and future research directions are proposed.
Abstract: Optimization modeling has become a powerful tool to tackle emergency logistics problems since its first adoption in maritime disaster situations in the 1970s. Using techniques of content analysis, this paper reviews optimization models utilized in emergency logistics. Disaster operations can be performed before or after disaster occurrence. Short-notice evacuation, facility location, and stock pre-positioning are drafted as the main pre-disaster operations, while relief distribution and casualty transportation are categorized as post-disaster operations. According to these operations, works in the literature are broken down into three parts: facility location, relief distribution and casualty transportation, and other operations. For the first two parts, the literature is structured and analyzed based on the model types, decisions, objectives, and constraints. Finally, through the content analysis framework, several research gaps are identified and future research directions are proposed.
610 citations
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TL;DR: Critical mortality was reduced by rapid advanced major incident management and seems unrelated to over-triage, and hospital surge capacity can be maintained by repeated effective triage and implementing a hospital-wide damage control philosophy.
Abstract: Summary Background The terrorist bombings in London on July 7, 2005, produced the largest mass casualty event in the UK since World War 2. The aim of this study was to analyse the prehospital and in-hospital response to the incident and identify system processes that optimise resource use and reduce critical mortality. Methods This study was a retrospective analysis of the London-wide prehospital response and the in-hospital response of one academic trauma centre. Data for injuries, outcome, triage, patient flow, and resource use were obtained by the review of emergency services and hospital records. Findings There were 775 casualties and 56 deaths, 53 at scene. 55 patients were triaged to priority dispatch and 20 patients were critically injured. Critical mortality was low at 15% and not due to poor availability of resources. Over-triage rates were reduced where advanced prehospital teams did initial scene triage. The Royal London Hospital received 194 casualties, 27 arrived as seriously injured. Maximum surge rate was 18 seriously injured patients per hour and resuscitation room capacity was reached within 15 min. 17 patients needed surgery and 264 units of blood products were used in the first 15 h, close to the hospital's routine daily blood use. Interpretation Critical mortality was reduced by rapid advanced major incident management and seems unrelated to over-triage. Hospital surge capacity can be maintained by repeated effective triage and implementing a hospital-wide damage control philosophy, keeping investigations to a minimum, and transferring patients rapidly to definitive care.
367 citations
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TL;DR: Education and training assumes major importance in the care of mass casualties from any form of disaster, in view of how different the decision-making must be if the salvage of life is to be maximized.
Abstract: The main factor that distinguishes true mass casualty disasters from the routine management of injured patients is the large number of casualties that present essentially simultaneously, which outstrip the available resources required for their optimal care. The injuries themselves tend to be similar to those normally encountered in daily trauma practice, although they may be more severe and unique in certain settings (i.e. severe soft tissue disruption, shrapnel wounds or blast lung in victims of explosive disasters, cyanide poisoning in chemical events, acute radiation syndrome in radiological events). However, the large numbers of casualties greatly impede the ability to fully evaluate and treat each injured individual in a conventional manner. A major change in the approach to medical care is therefore required in order to optimize outcome. Medical evaluation and treatment must be rapid to allow for a continuing influx, and yet must remain accurate in identifying those critically injured victims who require immediate life-saving care. The focus of medical care can no longer be on each individual, but must shift to the population as a whole. The standard goal of providing the greatest good for each individual patient must change in a mass casualty setting to the greatest good for the greatest number. This requires a rationing of the limited resources to apply them where they are most beneficial for the most casualties. These concepts are antithetical to the morality and training of health care providers, yet are necessary to salvage the greatest number of lives in these circumstances (1–3). A key component of the delivery of medical care to mass casualties is the process of triage, from the French word triagere, meaning “to sort”. This concept was introduced by Napoleon’s battlefield surgeon, Baron Dominique Jean Larrey, and has since become a cornerstone of military medical care (4, 5). It involves matching the limited resources to the needs of casualties by assigning those who are most seriously injured to receiving priority care. This requires rapid identification of the severely injured in order to apply these resources most appropriately. The greater the casualty burden, the more difficult this becomes, and the more training and expertise is required. In fact, triage is practiced only occasionally and on small scales in the routine management of individual injured patients. The abundant medical resources in developed nations allow essentially unlimited application of care and expense to each patient, which makes rationing of care unnecessary. True mass casualty events are rare. The principles of triage are not taught in many medical schools or in residency training. This is why education and training assumes major importance in the care of mass casualties from any form of disaster, in view of how different the decision-making must be if the salvage of life is to be maximized (6).
343 citations
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