Prioritizing Patients for Emergency Evacuation From a Healthcare Facility

The success of a healthcare facility evacuation depends on communication and decision-making at all levels of the organization, from the coordinators at incident command to the clinical staff who actually carry out the evacuation. One key decision is the order in which each patient is chosen for evacuation. While the typical planning assumption is that all patients are to be evacuated, there may not always be adequate time or resources available to move all patients. In these cases, prioritizing or ordering patients for evacuation becomes an extremely difficult decision to make. These decisions should be based on the current state of the facility, but without knowledge of the current patient roster or available resources, these decisions may not be as beneficial as possible. Healthcare facilities usually consider evacuation a last-resort measure, and there are often system redundancies in place to protect against having to completely evacuate all patients from a facility. Perhaps this is why there is not a great deal of research dedicated to improving patient transfers. In addition, the question of patient prioritization is a highly ethical one. Based on a literature review of 1) suggested patient prioritization strategies for evacuation planning as well as 2) the actual priorities given in actual facility evacuations indicates there is a lack of consensus as to whether critical or non-critical care patients should be moved away from a facility first in the event of a complete emergency evacuation. In addition, these policies are \u27all-or-nothing\u27 policies, implying that once a patient group is given priority, this entire group will be completely evacuated before any patients from the other group are transferred. That is, if critical care patients are given priority, all critical care patients will be transferred away from the facility before any non-critical care patient. The goal of this research is to develop a decision framework for prioritizing patient evacuations, where unique classifications of patient health, rates of evacuation, and survivability all impact the choice. First, I provide several scenarios (both in terms of physical processing estimates as well as competing, ethically-motivated objectives) and offer insights and observations into the creation of a prioritization policy via dynamic programming. Dynamic programming is a problem-solving technique to recursively optimize a series of decisions. The results of the dynamic programming provide optimal prioritization policies, and these are tested with simulation analysis to observe system performance under many of the same scenarios. Because the dynamic programming decisions are based on the state of the system, simulation also allows the testing of time-based decisions. The results from the dynamic programming and simulation, as well as the structural properties of the simulation are used to create assumptions about how evacuations could be improved. The question is not whether patient priorities should be assigned - but how patient priorities should be assigned. Associated with assigning value to patients are a variety of ethical dilemmas. In this research, I attempt to address patient prioritization from an ethical perspective by discussing the basic principles and the potential dilemmas associated with such decisions. The results indicate that an all-or-nothing, or a \u27greedy\u27 policy as discussed in the literature may not always be optimal for patient evacuations. In some cases, a switching policy may occur. Switching policies begin by evacuating patients from one classification and then switch to begin evacuations from the second patient class. A switch can only be made once; after a switch is made, all remaining patients from the new group should be evacuated. When there are no more patients of that group remaining in the system, the remaining patients from the class that was initially given priority should be evacuated. In the case of critical and non-critical care patients, switching policies first give priority to non-critical care patients. When the costs of holding patients in the system are not included in the models - and the decisions are just based on maximizing the number of saved lives - the switching policies may perform as good or better than the greedy policies suggested in the literature. In addition, when holding costs are not included, it is easier to predict whether the optimal policy is a greedy policy or a switching policy. Prioritization policies can change based on the utility achieved from evacuating individual patients from each class, as well as for other competing objective functions. This research examines a variety of scenarios - maximizing saved lives, minimizing costs, etc. - and provides insights on how the selection of an objective impacts the choice. Another insight of this research is how multiple evacuation teams should be allocated to patients. In the event that there is more than one evacuation team dedicated to moving a group of patients, the two teams should be allocated to the same patient group instead of being split between the multiple patient groups

LEVERAGING THE LIGHT AMPHIBIOUS WARSHIP AS A MASS CASUALTY EVACUATION PLATFORM IN A CONTESTED ENVIRONMENT

The Marine Corps needs more accurate models and tools to examine the capabilities of evacuating mass casualties in a dispersed and disaggregated environment. Specifically, the Marine Corps needs to determine the types of platforms required to evacuate casualties for a distributed force as well as the accompanying concepts of operations. To assist in this, Massachusetts Institute of Technology Lincoln Laboratory is developing the Expeditionary Energy Multi-Domain Model (E2M2), which applies an agent-based simulation framework called Probabilistic Investigation of Resource Allocation in Networks of Hierarchical Agents (PIRANHA). The E2M2 evaluates the performance of the Light Amphibious Warship (LAW) used for casualty evacuations. This research utilizes high-dimensional experimental design to vary factors within an Expeditionary Advanced Based Operations scenario to explore varying hospital locations, number of LAWs, LAW configurations, and LAW transportation polices in evacuating mass casualties within the Indo-Pacific region. The E2M2 assists the Marine Corps in determining how LAW is best used as a viable casualty evacuation platform for a distributed force. This research identifies the best-fitting models, methods, and tools that can be used to support analysis in this area. It also includes a demonstration of the E2M2 in support of a scenario and documentation that identifies challenges and opportunities in using the E2M2 in support of concept development activities.Captain, United States Marine CorpsApproved for public release. Distribution is unlimited

National Study on Carless and Special Needs Evacuation Planning: Case Studies

The National Study of Carless and Special Needs Evacuation Planning has constructed an essential outline for carless and special needs evacuation planning. This outline is built from planning efforts in each of the five case study cities. Each city had its strengths and weaknesses. In this study, we have combined the strengths from every city involved to build the criteria used to evaluate their planning efforts. In this sense, we have based our evaluations upon real planning efforts that can and are being done around the United States

SIMULATION AND MATHEMATICAL MODELING TO SUPPORT COMMUNITY-WIDE EVACUATION DECISIONS FOR MULTIPLE POPULATION GROUPS

Evacuating a large population from an at-risk area has been the subject of extensive research over the past few decades. In order to measure trip completion and total evacuation times accurately, most researchers have implemented some combination of simulation and optimization methods to provide vehicular flow and congestion data. While the general at-risk population comprises the majority of travelers on the road network, there are often specific groups to consider when assessing the ability to evacuate an entire population. In particular, healthcare facilities (e.g., hospitals) may require evacuation, and the trip times may become an important health issue for patients being evacuated. Emergency vehicles from these facilities will share the same roadways and exit paths that are used by the local community, and it becomes increasingly important to minimize long travel times when patient care must be provided during transport. As the size of the area to model grows larger, predicting individual vehicle performance becomes more difficult. Standard transportation-specific micro-simulation, which models vehicle interactions and driver behaviors in detail, may perform very well on road networks that are smaller in size. In this research, a novel modeling approach, based on cell transmission and a speed-flow relationship, is proposed that combines the \u27micro\u27 and \u27meso\u27 approaches of simulation modeling. The model is developed using a general purpose simulation software package. This allows for an analysis at each vehicle level in the travel network. In addition, using these method and approaches, we can carry out dynamic trip planning where evacuees decide their route according to current road and traffic conditions. By translating this concept to an actual implementation, a traffic management center could identify current best travel routes between several origins and destinations, while continuing to update this list periodically. The model could suggest routings that favor either a user-optimal or system-optimal objective. This research also extended the concept of dynamic traffic assignment while modeling evacuation traffic. This extension includes the utilization of Wardrop\u27s System Optimum theory, where flow throughout the network is controlled in order to lower the risk of traffic congestion. Within this framework traffic flow is optimized to provide a route assignment under dynamic traffic conditions. This dissertation provides a practical and effective solution for a comprehensive evacuation analysis of a large, metropolitan area and the evacuation routes extending over 100 miles. Using the methodologies in this dissertation, we were able to create evacuation input data for general as well as special needs populations. These data were fed into the tailored simulation model to determine critical evacuation start times and evacuation windows for both the community-wide evacuation. Moreover, our analysis suggested that a hospital evacuation would need to precede a community-wide evacuation if the community-wide evacuation does not begin more than 24 hours before a hurricane landfall. To provide a more proactive approach, we further suggested a routing strategy, through a dynamic traffic assignment framework, for supporting an optimal flow of traffic during an evacuation. The dynamic traffic assignment approach also provides a mechanism for recommending specific time intervals when traffic should be diverted in order to reduce traffic congestion

Modelling human network behaviour using simulation and optimization tools: the need for hybridization

The inclusion of stakeholder behaviour in Operations Research / Industrial Engineering (OR/IE) models has gained much attention in recent years. Behavioural and cognitive traits of people and groups have been integrated in simulation models (mainly through agent-based approaches) as well as in optimization algorithms. However, especially the influence of relations between different actors in human networks is a broad and interdisciplinary topic that has not yet been fully investigated. This paper analyses, from an OR/IE point of view, the existing literature on behaviour-related factors in human networks. This review covers different application fields, including: supply chain management, public policies in emergency situations, and Internet-based human networks. The review reveals that the methodological approach of choice (either simulation or optimization) is highly dependent on the application area. However, an integrated approach combining simulation and optimization is rarely used. Thus, the paper proposes the hybridization of simulation with optimization as one of the best strategies to incorporate human behaviour in human networks and the resulting uncertainty, randomness, and dynamism in related OR/IE models.Peer Reviewe

Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

Location of Emergency Treatment Sites after Earthquake using Hybrid Simulation

A mass-casualty natural disaster such as an earthquake is a rare, surprising event that is usually characterized by chaos and a lack of information, resulting in an overload of casualties in hospitals. Thus, it is very important to refer minor and moderately-injured casualties, that are the majority of casualties and whose injuries are usually not life threatening, to ad hoc care facilities such as Emergency Treatment Sites (ETSs). These facilities support the efficient use of health resources and reduce the burden on permanent healthcare facilities. In our study, a hybrid simulation model, based on a combination of discrete events and an agent-based simulation, provides a solution to the uncertainty of positioning temporary treatment sites. The simulation methodology used compares between "rigid" and "flexible" operating concepts of ETSs (main vs. main+minor ETSs) and found the "flexible" concept to be more efficient in terms of the average walking distance and number of casualties treated in the disaster area

e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit

Rescue activity of a civilian helicopter emergency medical service in the western cape, South Africa: a five-year retrospective review

Introduction - Helicopter search and rescue in Africa is conducted primarily by military organizations. Since 2002 the Western Cape of South Africa has had a dedicated contracted civilian helicopter emergency medical service (HEMS) conducting air ambulance, terrestrial and aquatic rescue. This is the first description of the operations of an African helicopter rescue service. Objective - To describe the terrestrial and aquatic helicopter rescue activity of a civilian operated HEMS in the Western Cape, South Africa from 1 January 2012 – 31 December 2016. Methods - A five-year retrospective review was conducted using data from the organization's operational database, aviation documents, rescue reports and patient care records. Patient demographics and activity at time of rescue, temporal and geographical distribution, crewing compositions, patient injury, triage, clinical interventions and rescue techniques were analysed. Results – A total of 581 search and rescue missions were conducted, of which 451 were terrestrial and 130 aquatic rescues. The highest volume of rescues was conducted within the urban Cape Peninsula. Hoisting using a rescue harness was the most common rescue technique used. 644 patients were rescued. Uninjured or minorly injured persons represented 79% of the sample. Trauma (33%, 196/644) was the most common medical reason for rescue, with lower limb trauma predominant (15%, 90/644). The most common clinical interventions performed were intravenous access (108, 24%), spinal immobilization (92, 21%), splinting (76, 17%) and analgesia administration (58, 13%). Conclusions - The patient demographics and rescue activity described are similar to those described in high-income settings