Alternate Level of Care (ALC) patients are patients that stay in the acute care setting while waiting to be transferred to an ALC facility. They are not receiving the appropriate type of care and are occupying acute care resources. ALC patients occupy 5,200 patient beds everyday in Canada, and 12 percent of these ALC patients die during their waiting period. This study evaluates Toronto General Hospital's (TGH) discharge policy in the General Surgery and General Internal Medicine (GIM) departments using a discrete-event simulation. For long-term care ALC patients, it was found that applying to one extra application or maximizing the number of short waiting list facilities in their total number of applications significantly reduces the number of ALC days and the number of died in hospital patients. Knowing if discharge policies can decrease ALC days is not only significant to TGH but also to other health care institutions.

Alternate Level of Care (ALC) patients are patients that stay in the acute care setting while waiting to be transferred to an ALC facility. They are not receiving the appropriate type of care and are occupying acute care resources. ALC patients occupy 5,200 patient beds everyday in Canada, and 12 percent of these ALC patients die during their waiting period. This study evaluates Toronto General Hospital's (TGH) discharge policy in the General Surgery and General Internal Medicine (GIM) departments using a discrete-event simulation. For long-term care ALC patients, it was found that applying to one extra application or maximizing the number of short waiting list facilities in their total number of applications significantly reduces the number of ALC days and the number of died in hospital patients. Knowing if discharge policies can decrease ALC days is not only significant to TGH but also to other health care institutions.

No description available.

This thesis investigates the causes of the long wait-time for patients in Emergency department (ED) of Victoria General Hospital, and suggests changes for improvements. Two prominent simulation techniques have been used to replicate the ED in a simulation model. These are Discrete-event simulation (DES) and Agent-based modeling (ABM). While DES provides the basic modeling framework ABM has been used to incorporate human behaviour in the ED. The patient flow in the ED has been divided into 3 phases: input, throughput, and output. Model results show that there could be multiple interventions to reduce time taken to be seen by the doctor for the first time (also called WTBS) either in the output phase or in the input phase. The model is able to predict that a reduction in the output phase would cause reduction in the WTBS but it is not equipped to suggest how this reduction can be achieved. To reduce WTBS by making interventions in the input phase this research proposes a strategy called fast-track treatment (FTT). This strategy helps the model to dynamically re-allocate resources if needed to alleviate high WTBS. Results show that FTT can reduce WTBS times by up-to 40%.

The move towards integrating products and services has increased significantly. As a result, some business models, such as Product Service Systems (PSS) have been developed. PSS emphasises the sale of use of the product rather than the sale of the product itself. In this case, product ownership lies with the manufacturers/suppliers. Customers will be provided with a capable and available product for their use. In PSS, manufacturers/suppliers are penalised for any down time of their product according to the PSS contract. This has formed a pressure on the service providers (maintenance teams) to assure the availability of their products in use. This pressure increases as the products are scattered in remote places (customer locations). Authors have urged that different product monitoring levels are applied to enable service providers to monitor their products remotely allowing maintenance to be performed accordingly. They claim that by adopting these monitoring levels, the product performance will increase. Their claim is based on reasoning, not on experimental/empirical methods. Therefore, further experimental research is required to observe the effect of such monitoring levels on complex maintenance operations systems as a whole which includes e.g. product location, different types of failure, labour and their skills and locations, travel times, spare part inventory, etc. In the literature, monitoring levels have been classified as Reactive, Diagnostics, and Prognostics. This research aims to better understand and evaluate the complex maintenance operations of a product in use with different levels of product monitoring strategies using a Discrete Event Simulation (DES) approach. A discussion of the suitability of DES over other techniques has been provided. DES has proven its suitability to give a better understanding of the product monitoring levels on the wider maintenance system. The requirements for simulating a complex maintenance operation have been identified and documented. Two approaches are applied to gather these generic requirements. The first is to identify those requirements of modelling complex maintenance operations in a literature review. This is followed by conducting interviews with academics and industrial practitioners to find out more requirements that were not captured in the literature. As a result, a generic conceptual model is assimilated. A simulation module is built through the Witness software package to represent different product monitoring levels (Reactive, Diagnostics, and Prognostics). These modules are then linked with resources (e.g. labour, tools, and spare parts). To ensure the ease of use and rapid build of such a complex maintenance system through these modules, an Excel interface is developed and named as Product Monitoring Levels Simulation (PMLS). The developed PMLS tool needed to be demonstrated and tested for tool validation purposes. Three industrial case studies are presented and different experimentations are carried out to better understand the effect of different product monitoring levels on the complex maintenance operations. Face to face validation with case companies is conducted followed by an expert validation workshop. This work presents a novel Discrete Event Simulation (DES) approach which is developed to support maintenance operations decision makers in selecting the appropriate product monitoring level for their particular operation. This unique approach provides numerical evidence and proved that the higher product monitoring level does not always guarantee higher product availability.

The focus of this thesis is on the application of decision models to the economic evaluation of health care technologies. The primary objective addresses the correct choice of modelling technique, as the attributes of the chosen technique could have a significant impact on the process, as well as the results, of an evaluation. Separate decision models, a Markov process and a discrete event simulation (DES) model are applied to a case study evaluation comparing alternative adjuvant therapies for early breast cancer. The case study models are built and analysed as stochastic models: whereby probability distributions are specified to represent the uncertainty about the true values of the model input parameters. Three secondary objectives are also specified. Firstly, the empirical application of the alternative decision models requires the specification of a 'modelling process' that is not well defined in the health economics literature. Secondly, a comparison of alternative methods for specifying probability distributions to describe the uncertainty in the model's input parameters is undertaken. The final secondary objective covers the application of methods for valuing the collection of additional information to inform the resource allocation decision. The empirical application of the two relevant modelling techniques clarifies the potential advantages derived from the increased flexibility provided by DES over Markov models. The thesis concludes that the use of DES should be strongly considered if either of the following issues appear relevant: model parameters are a function of the time spent in particular states, or the data describing the timing of events are not in the form of transition probabilities. The full description of the modelling process provides a resource for health economists wanting to use decision models. No definitive process is established, however, as there exist competing methods for various stages of the modelling process. The main conclusion from the comparison of methods for specifying probability distributions around the input parameters is that the theoretically specified distributions are most likely to provide a common baseline for comparisons between evaluations. The central question that remains to be addressed is which method is the most theoretically correct? The application of a Vol analysis provides useful insights into the methods employed and leads to the identification of particular methodological issues requiring future research in this area.

This thesis investigates the causes of the long wait-time for patients in Emergency department (ED) of Victoria General Hospital, and suggests changes for improvements. Two prominent simulation techniques have been used to replicate the ED in a simulation model. These are Discrete-event simulation (DES) and Agent-based modeling (ABM). While DES provides the basic modeling framework ABM has been used to incorporate human behaviour in the ED. The patient flow in the ED has been divided into 3 phases: input, throughput, and output. Model results show that there could be multiple interventions to reduce time taken to be seen by the doctor for the first time (also called WTBS) either in the output phase or in the input phase. The model is able to predict that a reduction in the output phase would cause reduction in the WTBS but it is not equipped to suggest how this reduction can be achieved. To reduce WTBS by making interventions in the input phase this research proposes a strategy called fast-track treatment (FTT). This strategy helps the model to dynamically re-allocate resources if needed to alleviate high WTBS. Results show that FTT can reduce WTBS times by up-to 40%.

abstract: Overcrowding of Emergency Departments (EDs) put the safety of patients at risk. Decision makers implement Ambulance Diversion (AD) as a way to relieve congestion and ensure timely treatment delivery. However, ineffective design of AD policies reduces the accessibility to emergency care and adverse events may arise. The objective of this dissertation is to propose methods to design and analyze effective AD policies that consider performance measures that are related to patient safety. First, a simulation-based methodology is proposed to evaluate the mean performance and variability of single-factor AD policies in a single hospital environment considering the trade-off between average waiting time and percentage of time spent on diversion. Regression equations are proposed to obtain parameters of AD policies that yield desired performance level. The results suggest that policies based on the total number of patients waiting are more consistent and provide a high precision in predicting policy performance. Then, a Markov Decision Process model is proposed to obtain the optimal AD policy assuming that information to start treatment in a neighboring hospital is available. The model is designed to minimize the average tardiness per patient in the long run. Tardiness is defined as the time that patients have to wait beyond a safety time threshold to start receiving treatment. Theoretical and computational analyses show that there exists an optimal policy that is of threshold type, and diversion can be a good alternative to decrease tardiness when ambulance patients cause excessive congestion in the ED. Furthermore, implementation of AD policies in a simulation model that accounts for several relaxations of the assumptions suggests that the model provides consistent policies under multiple scenarios. Finally, a genetic algorithm is combined with simulation to design effective policies for multiple hospitals simultaneously. The model has the objective of minimizing the time that patients spend in non-value added activities, including transportation, waiting and boarding in the ED. Moreover, the AD policies are combined with simple ambulance destination policies to create ambulance flow control mechanisms. Results show that effective ambulance management can significantly reduce the time that patients have to wait to receive appropriate level of care. / Dissertation/Thesis / Ph.D. Industrial Engineering 2011

Analisando-se a literatura de simulação discreta pode-se observar que os autores, em geral, constroem seus modelos de simulação baseados em abordagens tradicionais e aceitas tais como orientação a eventos, orientação a mensagens, orientação a filas, etc. Mais recentemente encontram-se ambientes que afirmam utilizar o chamado paradigma de simulação orientado a objetos. No entanto não existe consenso na definição de tal paradigma e diferentes interpretações podem ser encontradas. Considerando que um modelo de simulação pertence a classe dos sistemas de software, nada mais natural do que aplicar conceitos de orientação a objetos em seu desenvolvimento. Deve ficar claro, entretanto, que existe uma grande diferença entre um paradigma de simulação, isto é, as idéias e recursos usados na construção de um modelo, e um paradigma de projeto e implementação aplicado ao desenvolvimento de sistemas de simulação. Linguagens orientadas a objetos podem ser aplicadas na implementação de sistemas de simulação que utilizam conceitos de modelagem distintos. Ainda que todos possam ser chamados de sistemas orientados a objetos, pode haver confusão quanto ao significado do termo simulação orientada a objetos. Este trabalho apresenta um esquema original de classificação para sistemas de simulação quanto a sua arquitetura de software onde são considerados aspectos tais como a maneira pela qual as entidades do modelo se comunicam e a forma pela qual se descrevem os eventos que alteram seu estado, entre outros. Conceitos fundamentais são identificados de maneira a definir um modelo de referencia onde diferentes paradigmas de simulação possam ser caracterizados e classificados. Especial atenção e dada ao relacionamento entre os paradigmas de simulação e a orientação a objetos, onde esta Ultima e vista como uma estratégia de projeto e implementação. Uma nova forma de caracterizar um paradigma de simulação e proposta. SIMOO e um "framework. ' para simulação discreta orientada a objetos que foi construído de maneira a poder validar os conceitos propostos. Composto por uma biblioteca de classes e de uma ferramenta de edição de modelos, a principal vantagem do use de SIMOO em relação a outras abordagens esta no fato de que SIMOO permite a seleção do paradigma mais adequado a descrição de cada entidade do modelo. Esta característica permite a criação de modelos que incorporam, simultaneamente, mais de um paradigma de simulação. A abstração básica da biblioteca de classes de SIMOO, a partir da qual são derivadas todas as entidades de um modelo, e o elemento autônomo. Este encapsula uma "thread" própria de execução e um sistema de comunicação por mensagens não tipadas que são a base de todos os paradigmas suportados por SIMOO. A ferramenta de edição de modelos de SIMOO e chamada de MET. MET utiliza um diagrama de classes hierárquico enriquecido com recursos adequados para a construção de modelos de simulação. Além do diagrama de classes, descreve-se também um diagrama de instâncias, onde as especificações genéricas do diagrama de classes são particularizadas. A partir da especificação dos diagramas e da descrição do comportamento das entidades, MET gera um modelo executável. Finalmente, SIMOO preocupa-se com a separação de domínios entre a descrição do modelo propriamente dito e os aspectos de visualização de resultados e interação com o usuário. Uma categoria especial de elementos autônomos chamados de monitores e provida para permitir essa separação. Além de apresentar o "framework" SIMOO em termos de especificação e implementação, este trabalho mostra aplicações através de situações exemplo e apresenta uma análise comparativa com outros ambientes descritos na literatura. / When one surveys the literature on discrete simulation. it will be noticed that, in general. authors build their simulation models usin g traditional approaches such as event-oriented. message-oriented, queue-oriented. etc. In more recent texts, frameworks can be found that allegedly use the so called object-oriented simulation paradigm. However, there is no generally accepted definition of such a paradigm. and various interpretations can be found. If we consider that a simulation system is an instance of the more general class of software systems, it is strai ghtforward to apply concepts of object orientation to develop simulation systems. Nonetheless. it is important to emphasize that there is a major difference between a simulation paradigm. i.e.. the principles and resources used to build the model, and a design and implementation paradi gm used to develop the simulation system. Object-oriented languages can be used to implement simulation systems that follow different paradigms. If we refer to all these systems as objectoriented systems, confusion about the exact meanin g of object-oriented simulation may occur. This work presents an original classification of simulation systems according to their software architectures, where different aspects are taken into account, such as the way the entities in the model communicate with each other, the way one describes events that modify the entities' state, and others. In this classification, we identify basic concepts that are used to define a reference model, with which different simulation paradigms may be characterized and classified. In particular, special attention to the relationship between simulation paradigms and object-orientation is given, the latter here being seen as a strategy to design and implement simulation systems. SIMOO is an object-oriented framework for discrete simulation. composed by a Class Library and a Model Editing Tool that has been built in order to validate the proposed concepts. The main advantage of SIMOO with respect to other frameworks is that it allows a selection of the most adequate paradigm to describe each entity in the model. As a consequence, we are able to create models that instantiate, simultaneously, more than one simulation paradigm. The basic element of the SIMOO class library, based on which the framework derives all the entities in the model, is the autonomous element. This autonomous element has its own execution thread and an untyped message-based communication system that constitute the basis of all the paradigms SIMOO supports. The SIMOO Model Editing Tool (MET) uses a hierarchical class diagram extended with resources needed to build simulation models. Along with the classe diagram, MET allows one to describe an instance diagram that details the more generic class diagram. From the diagrams and the description of the behavior of the entities, MET generates an executable model. The SIMOO framework also emphasizes the distinction between model description and aspects of visualization and user interaction. It provides a special category of autonomous elements, the monitors, that implements this separation. Besides presenting the formal specification and the implementation of the framework, in this work several examples of how to use the SIMOO are presented, along with a comparison with other existing frameworks.

Considerando o grande volume de obras, a necessidade de gerenciar inúmeras equipes, prazos reduzidos, alta repetitividade e a pequena margem de lucro de empreendimentos habitacionais de interesse social, tem crescido a importância projetar e simular os sistemas de produção de forma antecipada. A simulação de eventos discretos tem sido empregada como ferramenta de gestão para a análise de cenários alternativos em empreendimentos de construção, principalmente em trabalhos de cunho acadêmico. Entretanto, seu emprego tende a ser pouco explorado no projeto do sistema de produção de empreendimentos reais, principalmente devido à dificuldade de interpretação dos dados e da pouca experiência dos tomadores de decisão com essa ferramenta. Por esse motivo, a literatura tem recomendado o uso de ferramentas que auxiliem, de forma visual e espacial, a compreensão dos resultados. O objetivo desta pesquisa é propor um método para a elaboração do projeto do sistema de produção utilizando a modelagem BIM-4D e simulação de eventos discretos de forma integrada, na tomada de decisão de empreendimento habitacionais de interesse social. Foi escolhida a abordagem metodológica da design science research para a realização da pesquisa, a qual consiste na criação de um artefato, a ser utilizado para resolver classes de problemas, seguida da avaliação da sua utilidade. Este método foi desenvolvido através de três estudos empíricos nos quais o mesmo foi concebido e aplicado. Entre as principais contribuições deste trabalho, destaca-se uma proposta de integração entre a simulação de eventos discretos e modelagem BIM-4D no projeto do sistema de produção de empreendimentos habitacionais de interesse social, e uma discussão do papel de ferramentas gráficas como auxílio na tomada de decisão. / Considering the large scale of work, the need to manage a large number of teams, tight deadlines, highly repetitive operations, and limited profit margin of low-income housing projects, the need to design and simulate production systems in advance has increased. Discrete event simulation has been used as a management tool for the analysis of alternative scenarios in construction projects, mostly in academic studies. However, the use of simulation has not been fully explored in the design of the production system in real projects, mainly due to the difficulty of interpreting data, as well as the lack of experience of decision makers in using this tool. Therefore, the use of visual and spatial tools that support the interpretation of simulation data has been suggested in the literature. The aim of this research work is to propose a method for production system design using BIM-4D modeling and discrete event simulation in an integrated way for supporting decision making in low-income housing projects. The methodological approach adopted in this investigation was design science research, which consists of the creation of an artifact for solving classes of problems, and the evaluation of its utility. This method was developed along three empirical studies in which it was conceived and applied. The main contributions of this research work are concerned with a proposal for the integration of discrete event simulation and BIM-4D modeling in the production system design of low-income housing projects, and a discussion on the use of graphical tools to support decision-making.