Forecasting the Demand for Emergency Medical Services

Accurate forecast of the demand for emergency medical services (EMS) can help in providing quick and efficient medical treatment and transportation of out-of-hospital patients. The aim of this research was to develop a forecasting model and investigate which factors are relevant to include in such model. The primary data used in this study was information about ambulance calls in three Swedish counties during the years 2013 and 2014. This information was processed, assigned to spatial grid zones and complemented with population and zone characteristics. A Zero-Inflated Poisson (ZIP) regression approach was then used to select significant factors and develop the forecasting model. The model was compared to the forecasting model that is currently incorporated in the EMS information system used by the ambulance dispatchers. The results show that the proposed model performs better than the existing one

Optimal Dispatch of Volunteers to Out-of-hospital Cardiac Arrest Patients

Initiatives with mobile phone dispatched volunteers to out-of-hospital cardiac arrest (OHCA) cases, can be found today in some countries, e.g. Sweden, the Netherlands, Switzerland and Italy. When an OHCA case is reported, an alarm is sent to the registered volunteers’ phones. However, the allocation of which volunteers to send to the automatic external defibrillator (AED) and who to send directly to the patient, is today based on simple rules of thumb. In this paper, we propose a model to optimally select how many and which volunteers to send directly to the patient, and who should pick up and deliver an AED. The results show that the model can help increase the survivability of the patients, compared to simple decision rules

Disaster management from a POM perspective : mapping a new domain

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 papers 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, queuing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights in disaster research. Recommendations for future research are provided

Models for Dispatch of Volunteers in Daily Emergency Response

Sufficient emergency resources are essential for emergency services to provide timely help to affected people and to minimize damage to public and private assets and the environment. Emergency services, however, face resource shortages and increasing demand over time. As a result, their response times increase, resulting in lower survival chances of affected people and more severe damage to properties and the environment. Thus, emergency services need to utilize and effectively manage all their available resources. These can be divided into traditional resources, such as ambulances, and new and emerging resources, such as volunteers. Models and methods developed using operations research (OR) methodologies can facilitate the management of these resources. However, despite a rich literature on OR-based models and methods focusing on traditional resources, the literature on new and emerging resources, and specifically volunteers, is scarce. The aim of this thesis is to develop models and methods for task assignment and dispatch of volunteers to daily medical emergencies. This also includes forecasting models for future emergencies. The developed models and methods consider volunteer programs in Sweden and the Netherlands, employing real historical data. The aim has been addressed through three studies, one main study and two sub-studies, the results of which are presented in the six included papers. The main study focuses on the development of models, methods, and strategies for task assignment and dispatch of volunteers to out-of-hospital cardiac arrest (OHCA) cases using OR. To evaluate the survival rates of these patients, the most important health outcome of a response process, survival functions have been used in the development of these models and strategies. The results of this study are presented in Papers II–V. The first sub-study investigates different types of new and emerging resources used in daily medical emergency response, and the results are presented as an overview of the literature in Paper I. The second sub-study focuses on the forecast of medical emergency demand, and its outcomes are presented in Paper VI. The overall conclusion is that the use of OR-based models and methods can contribute to improved outcomes and increased survival probabilities compared to the strategies and techniques used in the existing systems.För att räddningsorganisationer som till exempel ambulanssjukvården och den kommunala räddningstjänsten snabbt ska kunna hjälpa drabbade människor, byggnader och miljö, krävs att de har tillräckligt med resurser. Dock ökar hela tiden antalet utryckningar, samtidigt som budgetnedskärningar och rekryteringsproblem påverkar resurstillgången. Detta leder till längre insatstider, vilket ger ökad dödlighet och ökade kostnader. Därför är det av högsta vikt att de befintliga räddningsresurserna används så effektivt som möjligt. Dessa kan delas in i traditionella resurser, som till exempel ambulanser, och nya resurser, som frivilliga personer. Matematiska modeller, som optimerings- och simuleringsmodeller, har länge använts för att stödja planeringen och resurshanteringen av traditionella räddningsresurser, men för frivilliga resurser är det ett mer outforskat område. Syftet med forskningen som presenteras i denna avhandling är att utveckla modeller och metoder för tilldelning av arbetsuppgifter och utlarmning av frivilliga insatspersoner till akuta sjukdomsfall. I detta ingår också modeller för att prognosticera dylika händelser. De utvecklade modellerna och metoderna baseras på, och är framtagna för att stödja, verkliga frivilliginitiativ i Sverige och Nederländerna. Syftet uppfylls genom tre olika studier som presenteras via sex forskningsartiklar i avhandlingen. I den första studien görs en litteraturöversikt över nya typer av räddningsresurser som används som komplement till ambulanssjukvård. Den andra studien fokuserar på utvecklingen av modeller, metoder och strategier för uppgiftstilldelning och utlarmning av frivilliga insatspersoner vid hjärtstopp. I den tredje studien presenteras en ny prognosmodell för att prediktera ambulansuppdrag. Den generella slutsatsen är att beslutsstöd baserat på matematisk modellering kan bidra till bättre utfall, och en ökad överlevnadsgrad, jämfört med de strategier för uppgiftstilldelning, utlarmning och prognostisering som används idag

An Operations Research Approach for Daily Emergency Management

Emergency services play a vital role in society by providing help to affected people and minimizing damage to public and private assets as well as the environment during emergencies. However, these organizations deal with problems of increasing demand uncertainty and resource shortage over time. These problems lead to the creation of many other problems, such as longer response times, lower survivability of victims and patients, and more severe damage to properties and the environment. Acquiring more information about future emergency demand, such as factors affecting this demand, can contribute to reduction of the effects of increasing demand uncertainty. The introduction of volunteers as a new type of emergency resource, which has gained attention in the past few years, can be a solution to the problem of increasing resource shortage. The aim of this thesis is to provide operations research-based models and methods that can assist medical emergency services in daily emergency management. The aim is supported by two objectives: 1) to develop a forecasting model and 2) to develop models for the dispatch of volunteers. Three separate studies with a focus on these objectives are conducted, and the results are described in three papers. In the first paper, a forecasting model for predicting the volume of ambulance calls per hour and geographic location for three counties in Sweden is presented. The model takes into consideration geographical zones with few or no population and very low call frequency. Comparative results based on the real data of ambulance calls show that the proposed model performs better than the model that is currently used in some parts of Sweden for operational and tactical planning of emergency medical services. In addition to performance improvement, the proposed model provides information about the factors affecting ambulance demand. In the second paper, the use of volunteers in response to out-of-hospital cardiac arrest (OHCA) cases is considered, and a deterministic optimization model for their dispatch is provided. The model benefits from a survival function for determining dispatch decisions. The effect of arrival times of volunteers on the survivability of patients is also considered. The results show that, in terms of achieved survivability of patient based on the applied survival function, the proposed model performs better than simple decision rules used today. The third paper presents a probabilistic method for the dispatch of volunteers to OHCA cases. This method considers the uncertainties associated with the actions of volunteers once they are assigned a task. The proposed method uses a survival function as the objective of dispatch decisions. The results of the method are compared to the static dispatch method that is currently used in an operational system in Sweden for the utilization of volunteers in OHCA cases. Comparative results based on real data show that, with respect to used survival function, the proposed method contributes to higher survivability of OHCA patients than the static dispatch method. The models and method in this thesis focus on solving real-world problems and use real data for that purpose when available. Some simplifications were considered in the development process. Nevertheless, these models and method have the potential to be beneficial for medical emergency services in practice and can be used as a base for dynamic resource management systems. Such systems can be helpful for both tactical and operational planning of emergency resources

Optimal pre-dispatch task assignment of volunteers in daily emergency response

In emergency response volunteer programs, volunteers in the vicinity of an emergency are alerted via their mobile phones to the scene of the event to perform a specific task. Tasks are usually assigned based on predetermined rules disregarding real-world uncertainties. In this paper, we consider some of these uncertainties and propose an optimization model for the dispatch of volunteers to emergencies, where all task assignments must be done before dispatch. This means that each volunteer must be given a task before knowing whether (s)he is available. The model becomes computationally demanding for large problem instances; therefore, we develop a simple greedy heuristic for the problem and ensure that it can produce high quality solutions by comparing it to the exact model. While the model is for a general emergency, we test it for the case of volunteers responding to out-of-hospital cardiac arrest (OHCA) incidents. We compare the results of the model to the dispatch strategies used in two ongoing volunteer programs in Sweden and in the Netherlands and use simulation to validate the results. The results show that the model most often outperforms the currently used strategies; however, the computational run times, even for the heuristic, are too high to be operationally useful for large problem instances. Thus, it should be possible to improve the outcome using optimization-based task assignments strategies, but a fast solution method is needed for such strategies to be practically useable.Funding: Swedish civil contingencies agency (MSB) [CARER [71]]</p

A review on initiatives for the management of daily medical emergencies prior to the arrival of emergency medical services

Emergency services worldwide face increasing cost pressure that potentially limits their existing resources. In many countries, emergency services also face the issues of staff shortage-creating extra challenges and constraints, especially during crisis times such as the COVID-19 pandemic-as well as long distances to sparsely populated areas resulting in longer response times. To overcome these issues and potentially reduce consequences of daily (medical) emergencies, several countries, such as Sweden, Germany, and the Netherlands, have started initiatives using new types of human resources as well as equipment, which have not been part of the existing emergency systems before. These resources are employed in response to medical emergency cases if they can arrive earlier than emergency medical services (EMS). A good number of studies have investigated the use of these new types of resources in EMS systems, from medical, technical, and logistical perspectives as their study domains. Several review papers in the literature exist that focus on one or several of these new types of resources. However, to the best of our knowledge, no review paper that comprehensively considers all new types of resources in emergency medical response systems exists. We try to fill this gap by presenting a broad literature review of the studies focused on the different new types of resources, which are used prior to the arrival of EMS. Our objective is to present an application-based and methodological overview of these papers, to provide insights to this important field and to bring it to the attention of researchers as well as emergency managers and administrators.Funding Agencies|Linkoping University; Swedish civil contingencies agency (MSB), through the Center for advanced research in emergency response (CARER)</p

Modeling uncertain task compliance in dispatch of volunteers to out-of-hospital cardiac arrest patients

In countries such as Sweden, Italy, Switzerland, and the Netherlands, projects in which volunteers are dispatched to out-of-hospital cardiac arrest (OHCA) patients with the use of mobile phones exist. Once an OHCA case is reported, a notification is sent to the mobile phones of registered volunteers that are in the vicinity of the patient. These projects mostly use static dispatch methods to determine which volunteers should be sent directly to the patient and which ones should pick up an automatic external defibrillator (AED). However, such schemes do not consider uncertainties associated with these task assignment decisions (e.g., if volunteers will do as instructed, or do something else). In this paper, we propose a method for optimized task assignment and dispatch of volunteers to OHCA patients that considers the uncertainty related to volunteers actions once assigned a task. We then compare the results of our method to those of a static dispatch method used in an ongoing mobile phone volunteer dispatch project in Sweden and validate them using simulation. Furthermore, we perform a sensitivity analysis on several parameters to investigate their effect on the performance of the proposed method. With the comparative results we show that the proposed method may help increase the survivability of OHCA patients.Funding Agencies|Swedish civil contingencies agency (MSB), through the research program Managing the incident site of the future (MIST)</p