3,662 research outputs found

    A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

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    Existing approaches to conceptual modelling (CM) in discrete-event simulation (DES) do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The framework incorporates two facilitated workshops. It consists of a package including: three key stages and sub-stages; activities and guidance; tools and prescribed outputs. The CM framework is tested in a real case study of an obesity system. The benefits of using this framework in healthcare studies and more widely in simulation are discussed. The paper also considers how the framework meets the conceptual modeling requirements

    A Facilitation Workshop for the Implementation Stage: A Case Study in health care

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    Research on facilitation in discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. Most of the research has focussed on facilitation in the initial stages of the simulation modelling process. In this paper we focus on one of the postmodel coding stages. More specifically we focus on the implementation stage, the final stage in the modelling process. The primary contributions of this paper are the description of the process followed and the introduction of tools that can be used during this stage to support workshop activities. A real case study is provided describing the sequence of the interactions undertaken in the workshop. Extracts from the transcripts are also included, with the view to bringing evidence of the stakeholders’ involvement and their mood during the workshop. The paper concludes with a discussion on the process followed and the importance of using tools in this stage

    A facilitation workshop for the implementation stage: A case study in health care

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    Research on facilitation in discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. Most of the research has focussed on facilitation in the initial stages of the simulation modelling process. In this paper we focus on one of the postmodel coding stages. More specifically we focus on the implementation stage, the final stage in the modelling process. The primary contributions of this paper are the description of the process followed and the introduction of tools that can be used during this stage to support workshop activities. A real case study is provided describing the sequence of the interactions undertaken in the workshop. Extracts from the transcripts are also included, with the view to bringing evidence of the stakeholders’ involvement and their mood during the workshop. The paper concludes with a discussion on the process followed and the importance of using tools in this stage

    Facilitated post-model coding in discrete event simulation (DES): a case study in healthcare

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    Research on facilitated discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. This paper is part of a line of research on the methodology of facilitated DES. In this paper we explain in more detail the facilitation process and the tools used to support the experimentation and implementation stages in a DES study involving workshops with a group of stakeholders, after an initial simulation model has been coded on the computer. A real case study is used to describe the process followed and the interactions at the workshops. Extracts from the transcripts are also included, with the view to providing evidence of the stakeholders’ involvement and their mood during the workshops. We conclude with a discussion on the process and tools used to support the facilitation process. Future research directions are also put forward

    Choice and judgement in developing models for health technology assessment; a qualitative study

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    Introduction: The role of models in supporting health policy decisions is reliant on model credibility. Credibility is fundamentally determined by the choices and judgements that people make in the process of developing a model. However, the method of uncovering choices and making judgements in model development is largely unreported and is not addressed by modelling methods guidance. Methods: This qualitative study was part of a project examining errors in health technology assessment models. In-depth interviews with academic and commercial modellers were used to obtain descriptions of the model development process. Data were analysed using framework analysis and interpreted in the context of the methodological literature. Results: The activities involved in developing models were characterised according to the themes; understanding the decision problem, conceptual modelling, model implementation, model checking, and engaging with the decision maker. Finding and using evidence was frequently mentioned across these themes. There was marked variation between practitioners in the extent to which conceptual modelling was recognised as an activity distinct from model implementation. Discussion: Methodological approaches to addressing model credibility described in the wider modelling literature highlight the necessity to disentangle the conceptual modelling and implementation activities. Whilst interviewees talked of judgements and choice making throughout model development, discussion indicated that these were based upon skills and experience with no discussion of formal approaches. Methods are required that provide for a systematic approach to uncovering choices, to generating a shared view of consensus and divergence, and for making judgements and choices in model development

    Participative Foresight for Smarter Cities: From Vision-Seeds to the Development of Scenarios

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    Recently, the smart city concepts have gained increasing importance in current energy and city planning. Various smart city projects which have been realized show that a systemic, integrative approach is crucial. However, in the projects the delineation of boundaries for integrative planning and the realization of systemic local solutions are challenging as the prevailing conventional planning tools and routines are limited. They usually propose top-down and short-term approaches with limited interactions with the stakeholders and limited interdisciplinary research (in particular involving areas of sociology). To tackle these challenges, a Swiss-Russian cooperation aims to enhance the existing planning routines by developing and testing systemic tools for multi-level stakeholder participation processes as well as for future-oriented thinking in city development. For this purpose, two Swiss and two Russian cities were selected, namely Winterthur, Zurich, Moscow and Kazan. These cities will be examined from the smart cities perspective with current and future applications at different implementation levels. Ideas and instruments will be developed to support their ongoing or planned smart city projects at district or city level by introducing participative and long term perspectives. In a series of workshops, participants’ visions, goals and interests will be elicited, compared with each other and contrasted with available data applying participative foresight methods and group model building techniques. Tools such as a GIS and a system dynamics simulation model will be developed to support the planning process, allow the integration of data and serve as a test-bed for proposed solutions. The systemic intervention and participation techniques will be continuously monitored and systematically evaluated. Moreover, a stakeholder-based scenario development process will be applied to envision future developments towards a smarter city and to distil roadmaps for the most desirable scenarios. Selected city processes in Switzerland and Russia among them Winterthur and Zurich, Moscow and Kazan which are all closely linked to the Smart City concept, will be supported by tailored vision-building, scenario development, system thinking techniques and simulation tools. In a first step, the prevalent situation concerning planning processes and instruments in the participating cities will be addressed with a specific focus on smart city objectives and current ongoing projects (e.g. stakeholder involvement, integrating smart energy concepts such as smart housing, smart grids, micro hubs in ongoing city and district planning and implementation processes). Moreover, we will analyse which planning processes and instruments are actually used to steer future energy provision and city development in participative and integrated manners, such as the interdepartemental management teams in the city of Winterthur spreading vision-seeds to come up with a variety of smart city scenarios

    Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment

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    It is often stated that involving the client in operational research studies increases conceptual learning about a system which can then be applied repeatedly to other, similar, systems. Our study provides a novel measurement approach for behavioural OR studies that aim to analyse the impact of modelling in long term problem solving and decision making. In particular, our approach is the first to operationalise the measurement of transfer of learning from modelling using the concepts of close and far transfer, and overconfidence. We investigate learning in discrete-event simulation (DES) projects through an experimental study. Participants were trained to manage queuing problems by varying the degree to which they were involved in building and using a DES model of a hospital emergency department. They were then asked to transfer learning to a set of analogous problems. Findings demonstrate that transfer of learning from a simulation study is difficult, but possible. However, this learning is only accessible when sufficient time is provided for clients to process the structural behaviour of the model. Overconfidence is also an issue when the clients who were involved in model building attempt to transfer their learning without the aid of a new model. Behavioural OR studies that aim to understand learning from modelling can ultimately improve our modelling interactions with clients; helping to ensure the benefits for a longer term; and enabling modelling efforts to become more sustainable

    Developing a conceptual model for police custody in the UK

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    The reduction of police officers in UK forces in recent years has reduced the number of staff in police custody, hence it is imperative that staff, and other resources, are utilized appropriately to optimize the custody process. This work aims to develop a simulation model that looks at resource utilisation in police custody. Resource availability can be modelled and tested using discrete event simulation. Developing an accurate conceptual model is a key stage to link the real-world problem and the simulation model. There is minimal literature presenting an accurate police custody conceptual model and hence, that is the focus of this paper. The key sources of information for constructing this model, previous literature, custody record analysis and a custody suite visit are discussed. A final conceptual model is presented with a discussion of how this will be converted into a simulation

    From Hybrid Simulation to Hybrid Systems Modelling

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    This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Hybrid Simulation (HS) is the combined application of simulation approaches like SD, DES and ABS in the model implementation stage of a simulation study. Its objective is to better represent the system under scrutiny. Hybrid Systems Modelling (HSM), on the other hand, is the combined application of simulation with methods and techniques from disciplines such as Applied Computing, Computer Science, Engineering and the wider OR. HSM can be applied to multiple stages of a simulation study. In this paper, we present a classification of HS and extend it to include HSM approaches which use simulation with other OR techniques. The paper contributes to the debate on what constitutes HS and offers a unifying conceptual representation for mixing simulation approaches with HSM methods and techniques

    Evaluating the impact of a simulation study in emergency stroke care

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    Very few discrete-event simulation studies follow up on recommendations with evaluation of whether modelled benefits have been realised and the extent to which modelling contributed to any change. This paper evaluates changes made to the emergency stroke care pathway at a UK hospital informed by a simulation modelling study. The aims of the study were to increase the proportion of people with strokes that undergo a time-sensitive treatment to breakdown a blood clot within the brain and decrease the time to treatment. Evaluation involved analysis of stroke treatment pre- and post- implementation, as well as a comparison of how the research team believed the intervention would aid implementation compared to what actually happened. Two years after the care pathway was changed, treatment rates had increased in line with expectations and the hospital was treating four times as many patients than before the intervention in half the time. There is evidence that the modelling process aided implementation, but not always in line with expectations of the research team. Despite user involvement throughout the study it proved difficult to involve a representative group of clinical stakeholders in conceptual modelling and this affected model credibility. The research team also found batch experimentation more useful than visual interactive simulation to structure debate and decision making. In particular, simple charts of results focused debates on the clinical effectiveness of drugs - an emergent barrier to change. Visual interactive simulation proved more useful for engaging different hospitals and initiating new projects
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