FOCUSING ON CENTRALITY MEASURE IN EMERGENCY MEDICAL SERVICES

Emergency Medical Services (EMS) attracted many researchers because the demand of EMS was increasing over time. One of the major concerns of EMS is the response time and ambulance despatching is one of the vital factors which affects the response time. This paper focuses on the problem of ambulance despatching when many emergency calls emerge in a short time, which exists under the condition of catastrophic natural or manmade disasters. We modify a new method for ambulance despatching by centrality measure, this method constructs a nearest-neighbor coupled emergency call network and then prioritize those calls by the score of fitness, where the score of fitness considers two factors: centralized measure a call by the emergency call network and the closest policy which means despatching to the closest call site. This method is testified by a series of simulation experiments on the real topology road network of Hong Kong Island which contains 8 hospitals. These analyses demonstrate the real situation and proof the potential of centrality measure in reducing response time of EMS

A Framework for Implementing IT Service Management in the Field of Pre-hospital Emergency Management with an Integrated Approach COBIT Maturity Model and ITIL Framework

Introduction: The purpose of this research is to provide an appropriate framework forimplementing IT management services in the field of pre-hospital emergencies with anintegrated approach of COBIT maturity model and ITIL framework.Methods: In a qualitative part, experts familiar with the field of pre-hospital emergency andinformation technology were purposefully selected. In the quantitative phase of the statisticalcommunity, we included experts in the field of information technology management whoare also experts in the field of emergency, as well as university professors who workedin the field of emergency and senior and middle managers in the field of pre-hospitalemergency entered the community. Considering the limitations of the community and thepurposefulness of the selection of individuals to enter the community, 915 individuals wereselected as a sample. To select a sample in the quantitative section, Morgan table was used.They were selected by simple random method using software. To collect information, wefirst reviewed the texts and articles in the field of ITIL and COBIT and then the extractedcodes in this category were reviewed and an overview of the research was obtained; then,in the qualitative part the interview method and in the quantitative part the researchermadequestionnaire were used. To analyze the data in the qualitative section, we used MAXQDA software to review and categorize the information. Then, in the quantitative section,the researcher-made questionnaire was collected and finally the model was fitted usingconfirmatory factor analysis.Results: In the end, it was concluded that the main components such as management,organization, processes, eyes, size, goals of the organization, staff, monitoring and evaluation,support, organization, information architecture and service delivery and their subcomponentswere the main factors that should be paid special attention in the field of prehospitalemergency management.Conclusion: To be more successful in implementing the organization’s framework, it mustidentify the most important problems and then create a controllable domain to implementservice support processes in the organization. The selected processes should be strongly andclearly supported by the general management of the organization. A codified and specificplan for implementation should be developed. A coordinated and planned approach fordesign, implementation should be specified and after the implementation of the mentionedprocesses. After expressing the output measurement indicators of the processes, the outputsshould be measured and based on the changes that exist, these changes should be consideredand returned to the planning stage to re-formulate the steps

Solving a Location, Allocation, and Capacity Planning Problem with Dynamic Demand and Response Time Service Level

Logistic systems with uncertain demand, travel time, and on-site processing time are studied here where sequential trip travel is allowed. The relationship between three levels of decisions: facility location, demand allocation, and resource capacity (number of service units), satisfying the response time requirement, is analysed. The problem is formulated as a stochastic mixed integer program. A simulation-based hybrid heuristic is developed to solve the dynamic problem under different response time service level. An initial solution is obtained from solving static location-allocation models, followed by iterative improvement of the three levels of decisions by ejection, reinsertion procedure with memory of feasible and infeasible service regions. Results indicate that a higher response time service level could be achieved by allocating a given resource under an appropriate decentralized policy. Given a response time requirement, the general trend is that the minimum total capacity initially decreases with more facilities. During this stage, variability in travel time has more impact on capacity than variability in demand arrivals. Thereafter, the total capacity remains stable and then gradually increases. When service level requirement is high, the dynamic dispatch based on first-come-first-serve rule requires smaller capacity than the one by nearest-neighbour rule

Integrating artificial neural networks, simulation and optimisation techniques in improving public emergency ambulance preparedness for heterogeneous regions under stochastic environments.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.The Bulawayo Emergency Medical Services (BEMS) department continues to rely on judgemental methods with limited use of historical data for future predictions, strategic, tactical and operational level decision making. The rural to urban migration trend has seen the sprouting of new residential areas, and this has put pressure to the limited health, housing and education resources. It is expected that as population increases, there is subsequent increase in demand for public emergency services. However, public emergency ambulance demand trends has been decreasing in Bulawayo over the years. This trend is a sign of limited capacity of the service rather than demand itself. The situation demanded for consolidated efforts across all sectors including research, to restore confidence among residents, reduce health risk and loss of lives. The key objective was to develop a framework that would assist in integrating forecasting, simulation and optimisation techniques for ambulance deployment to predefined locations with heterogeneous demand patterns under stochastic environments, using multiple performance indicators. Secondary data from the Bulawayo Municipality archives from 2010 to 2018 was used for model building and validation. A combination of methods based on mathematics, statistics, operations research and computer science were used for data analysis, model building, sensitivity analysis and numerical experiments. Results indicate that feed forward neural network (FFNN) models are superior to traditional SARIMA models in predicting ambulance demand, over a short-term forecasting horizon. The FFNN model is more inclined to value estimation as compared to SARIMA model, which is directional as depicted by the linear pattern over time. An ANN model with a 7-(4)-1 architecture was selected to forecast 2019 public emergency ambulance demand (PEAD). Peak PEAD is expected in January, March, September and December whilst lower demand is expected for April, June and July 2019. Simulation models developed mimicked the prevailing levels of service for BEMS with six(6) operational ambulances. However. the average response times were well above 15 minutes, with significantly high average queuing times and number of ambulances queuing for service. These performance outcomes were highly undesirable as they pose a great threat to human based outcomes of safety and satisfaction with regards to service delivery. Optimisation for simulation was conducted by simultaneously minimising the average response time and average queuing time, while maximising throughput ratios. Increasing the number of ambulances influenced the average response time below a certain threshold, beyond this threshold, the average response time remained constant rather than decreasing gradually. Ambulance utilisation inversely varied to increase in the feet size. Numerical experiments revealed that reducing the response time results in the reduction in number of ambulances required for optimal ambulance deployment. It is imperative to simultaneously consider multiple performance indicators in ambulance deployment as it balances resource allocation and capacity utilisation, while avoiding idleness of essential equipment and human resources. Management should lobby for de-congestion and resurfacing of old and dilapidated roads to increase access and speed when responding to emergency calls. Future research should investigate the influence of varying service time on optimum deployment plans and consider operational costs, wages and other budgetary constraints that influence the allocation of critical but scarce resources such as personnel, equipment and emergency ambulance response vehicles

The Transactional Theory of Stress and Coping: Predicting Posttraumatic Distress in Telecommunicators

Telecommunicators (e.g., dispatchers and 911 operators) experience firsthand the death and suffering of friends, family, peers, and strangers in a chaotic work environment characterized by chronic stress and lack of support. Previous research has demonstrated telecommunicators are at increased risk for negative health outcomes; however, existing research does not identify predictive pathways to posttrauma symptoms in telecommunicators. In an application of the transactional theory of stress and coping, I used structural equation modeling to examine occupational antecedents, work-family conflict, negative appraising, and coping as predictors of posttraumatic stress symptoms in telecommunicators. A convenience sample of 103 telecommunicators, recruited through agencies across the United States, completed a series of PTSD, stress, and coping surveys. Results supported three theorems from the transactional theory of stress and coping: (a) Chronic antecedents are correlated with work-family conflict (r = .54, p \u3c .01), (b) work-family conflict predicted negative appraising ( β = .64, p \u3c .01), and (c) coping predicted posttraumatic stress symptoms in telecommunicators ( β = .30, p = .01). These findings contribute to the current body of occupational health literature by expanding understanding of telecommunicators occupational experiences and appraisals and provide insights into modifiable processes and policies that can enhance and protect telecommunicator long term health. Specifically, employee-focused policies directed at preserving work-home balance and reducing chronic stressors in the workplace are recommended. Additionally, further research can be initiated to evaluate effectiveness of policy changes in telecommunicator appraising, health, and wellbeing

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Emergency response model of stroke in regional medical alliances: A case study of the Western Baiyun District Stroke Alliance in Guangzhou

Background: A hospital alliance has been established in the western part of Guangzhou, with the initial goal of optimizing the procedures of stroke care in the region and improving the efficiency of treatment services. Comparison of data reveals that the alliance proves to be effective, but there is still a gap between its performance and the objective. Methodology: Stakeholders in the stroke alliance are identified and classified through a comprehensive review of the stakeholder theory and the synergy theory. Structural equation modeling is used to quantify the synergy of healthcare alliances. A synergistic capacity model is developed to analyze the path relationships between the variables. Results: Several rounds of questionnaire survey reveal that there are 22 stakeholders in the Western Baiyun District Stroke Alliance, including six core stakeholders, eight latent stakeholders, and eight marginal stakeholders, and “hospitals at all levels” are the central members of the core stakeholders of the Western Baiyun District Stroke Alliance. Structural equation modeling has verified that the synergy of the Western Baiyun District Stroke Alliance is an organically integrated system comprised of three levels, namely, macro level synergy, meso level synergy, and micro level synergy, with a significant positive correlation between them. The macro level synergy includes cultural synergy and strategic synergy; the meso level synergy includes system synergy, innovation synergy, and information synergy; and the micro level synergy includes business synergy and process synergy. The score of synergy of the Alliance is 3.9646, still in a medium level. Conclusion: A regional stroke alliance is an organically integrated system of macro, meso and micro level synergy, with good macro synergistic capacity and average meso and micro synergistic capacity. Synergistic factors at all levels need to be taken into consideration so as to improve the overall synergy.Antecedentes: Estabelecimento de uma aliança dos hospitais ocidentais em Guangzhou, na China. A intenção da aliança é otimizar o processo de tratamento do AVC. De acordo com os dados existentes, embora a aliança tenha alcançado alguns resultados, ainda não conseguiu atingir todos os objetivos. Metodologia: Teoria dos stakeholders e teoria da sinergia, identificação e classificação dos stakeholders da aliança médica. Quantificação da sinergia na aliança médica através de um modelo de equações estruturais, estabelecimento do modelo de sinergia e análise das relações de dependência entre as variáveis. Resultados: Administração de questionários aos 22 stakeholders da aliança, incluindo os 6 stakeholders principais, 8 stakeholders potenciais e 8 stakeholders marginais. Usando o método de análise de centralidade, provou-se que o hospital é o elemento central dos stakeholders principais. Através da utilização de modelos de equações estruturais verificou-se que a capacidade colaborativa da aliança é um sistema de competências composto pelos níveis macro, meso e micro. O nível macro inclui as sinergias cultural e estratégica; O nível meso inclui a sinergia institucional, a sinergia de inovação e a sinergia de informação; O nível micro inclui a sinergia de negócios e a sinergia de processos. O resultado da capacidade colaborativa da aliança é de 3,9646, o que representa um nível médio de sinergia. Conclusões: A aliança é um sistema de capacitação composto por três níveis: nível macro, nível meso e nível micro. A capacidade de macro sinergia é muito boa, enquanto as capacidades de meso e de micro sinergia são medianas. É preciso levar em conta os fatores de sinergia em todos os níveis para melhorar de forma abrangente a capacidade geral de sinergia

Network Effects on Learning during Disasters: The Case of Australian Bushfires

Understanding factors that enhance or diminish learning levels of individuals and teams is significant for achieving both individual (low level) and organisational (high level) goals. In this study, the effect of social network factors at all levels of analysis (actor level, dyadic level and network level) on learning attitudes of emergency personnel in emergency events is investigated. Based on social network concepts of structural holes and strength of weak ties, and the social influence model of learning, a conceptual model is developed. To test and validate the model, data was collected from the transcripts of the 2009 Victorian Bushfires Royal Commission reports in conjunction with the 2008 Australian Inter-Service Incident Management System (AIIMS) survey. Secondly, network measures were applied for exploring the association with learning from a sample of people working within Incident Management Teams, combat roles and coordination centres across Australia and New Zealand. Empirical results suggest that social network factors at all levels of analysis (actor, dyadic and network levels) of emergency personnel play a crucial role in individual and team learning. The contextual implication from the quantitative and qualitative findings of this research is that when approaches for improving the emergency response at an interpersonal level are contemplated, the importance of social structure, position and relations in the networks of emergency personnel needs to be considered carefully as part of the overall individual and organisation-level goals. With this model of learning-related work activity, based on network connectedness, emergency staff members can strengthen their capacity to be flexible and adaptable. The findings of this study may be appreciated by emergency managers or administrators for developing an emergency practice culture to optimise individual and team learning and adaptability within an emergency management context