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The purpose of this study is to investigate and compare the views of doctors, nursing staff and hospitalized patients on the level of information they provide and receive respectively in public hospitals, focusing on the factors that affect their communication.

The study used a cross-sectional survey with a sample of 426 participants from two general hospitals in Greece–Pella and KAT Attica. Data were collected through a questionnaire in March–May 2020 and was analyzed with mean comparisons and correlations.

The results showed discrepancy in the satisfaction rate, with 67.3% satisfied patients from doctors' communication vs. 83.7% satisfied doctors. Improvements in hospital staff – patient communication are required especially on alternative therapies' discussion and time spent on communication. All respondents agreed that staff shortage is a deterrent factor for effective communication. Seamless for all respondents' groups, the factors that affect the communication satisfaction level are the duration of communication, time allowed for expressing questions and interest in patients' personal situation.

Strengthening the communication skills of medical staff and providing clear guidelines on when and how to inform patients are essential.

This study contributes to the growing body of research on doctor–patient communication. Its originality lies on the fact that communication satisfaction level was examined simultaneously for doctors, nurses and patients. The study provides additional evidence supporting the link among satisfaction and duration of communication and personalized relationship. The study's findings are important in the training of medical staff and the management of patients' expectations.

The purpose of this paper is to investigate the viability of using distributed simulation to execute large and complex healthcare simulation models which help government take informed decisions.

The paper compares the execution time of a standalone healthcare supply chain simulation with its distributed counterpart. Both the standalone and the distributed models are built using a commercial simulation package (CSP).

The results show that the execution time of the standalone healthcare supply chain simulation increases exponentially as the size and complexity of the system being modelled increases. On the other hand, using distributed simulation approach decreases the run time for large and complex models.

The distributed approach of executing different parts of a single simulation model over different computers is only viable when the model: can be divided into logical parts and the exchange of information between these parts occurs at constant simulated time intervals; is sufficiently large and complicated, such that executing the model over a single processor is very time consuming.

Based on a feasibility study of the UK National Blood Service we demonstrate the effectiveness of distributed simulation and argue that it is a vital technique in healthcare informatics with respect to supporting decision making in large healthcare systems.

To the best of the knowledge, this is the first feasibility study in healthcare which shows the outcome of modelling and executing a distributed simulation using unmodified CSPs and a software/middleware for distributed simulation.

The purpose of this paper is to provide a framework for analysing and modelling detailed workflow of image‐guided interventions to facilitate simulation and the re‐engineering process for the development of new procedures in multi‐modal imaging environments.

The methodology presented includes a literature review on workflow simulation in surgery, focussing on radiology environments, an assessment of simulation tools, a data gathering and management framework and research on methods for conceptual modelling of the processes.

The literature review reveals that few authors attempted to analyse the phases within image‐guided interventions, and those that did, only did so partially. The framework developed for this work intends to fill the gap found in the survey. It allows the maintenance and management of large amounts of data, one of the most critical factors when modelling detailed workflow. In addition, selecting the appropriate simulation software plays an important role, saving time in later stages of the project.

The framework presented for endovascular interventions can be extended to other types of image‐guided interventions. Moreover, modelling the workflow processes in a modular way facilitates the re‐engineering process when integrating different imaging modalities during the same procedure.

The purpose of this paper is to evaluate the impact on customer service of amalgamating two production/distribution facilities in a blood distribution network, located in the Maritime region of Canada, into a single production facility and a satellite distribution facility.

Simulation models of the existing distribution network and the future distribution network were built. Experiments were conducted, using the two models, to compare the performance of each.

Results indicate that there is no evidence to suggest a decrease in customer service resulting from the consolidation of the two facilities. Furthermore, results indicate that this conclusion is robust with respect to lower inventory levels at the satellite and up to three road closures per annum.

The results are based on specific operational assumptions regarding the number of hospitals supplied by the satellite facility and the methods used to transport blood products between locations.

The results of this study have important implications for how vital blood products are distributed to patients in the Maritime provinces of Canada.

This paper is a case study describing a unique application of simulation methods to an important area of application. It will be of interest to readers interested in the management of blood supply chains and to researchers applying simulation methods.

The purpose of this paper is to consider a number of issues around the poor adoption of healthcare simulation models and reflect whether there has been a broad failure of academic healthcare simulation modellers to build models that reflect real healthcare problems as acknowledged by healthcare stakeholders. This paper will also review the role of healthcare planners within the health sector and propose that they are well suited to act as change agents to improve the adoption of simulation within the sector.

This paper reviewed academic evidence around poor adoption of simulation modelling in healthcare, including differences to other sectors, its size and complexity, stakeholder issues and current and future challenges to improve operational efficiency. This paper also reviewed the role of healthcare planning and its valuable links with health stakeholders, suggesting that these links could be exploited to increase simulation modelling within the healthcare sector to improve operational efficiency.

This paper highlights the strong links between healthcare planning and the healthcare stakeholders and proposes that healthcare planning can play a key role in adoption of healthcare simulation modelling to achieve operational efficiency improvements.

This paper illustrates the potential link between healthcare planning and healthcare stakeholders to achieve operational improvements within the health sector.

The purpose of this paper is to identify the existing literature on the wide range of operations research (OR) studies applied to healthcare, and to classify studies based on application type and on the OR technique employed. The scope of the review is limited to studies which have been undertaken in the UK, and to papers published since the year 2000.

In total, 142 high‐quality journal and conference papers have been identified from ISI Web of Knowledge data base for review and analysis.

The findings categorise the OR techniques employed, and analyse the application type, publication trends, funding, and software packages used in the twenty‐first century in UK healthcare. Publication trends indicate an increasing use of OR techniques in UK healthcare. The findings show that, interestingly, the distribution of the OR techniques employed is not uniform; the majority of studies focus on simulation, either as the only technique employed or as one element of a multi‐method approach.

Several studies have focused on the use of simulation in healthcare modelling, but none has methodologically reviewed the use of the full range of OR techniques. This research is likely to benefit healthcare decision makers since it will provide them with an overview of the different studies that have utilised multiple OR techniques for investigating problems in the stated domain.

Although very significant and applicable, there have been no formal justifications for the use of Monte‐Carlo models and Markov chains in evaluating hospital admission decisions or concrete data supporting their use. For these reasons, this research was designed to provide a deeper understanding of these models. The purpose of this paper is to examine the usefulness of a computerized Monte‐Carlo simulation of admission decisions under the constraints of emergency departments.

The authors construct a simple decision tree using the expected utility method to represent the complex admission decision process terms of quality adjusted life years (QALY) then show the advantages of using a Monte‐Carlo simulation in evaluating admission decisions in a cohort simulation, using a decision tree and a Markov chain.

After showing that the Monte‐Carlo simulation outperforms an expected utility method without a simulation, the authors develop a decision tree with such a model. real cohort simulation data are used to demonstrate that the integration of a Monte‐Carlo simulation shows which patients should be admitted.

This paper may encourage researchers to use Monte‐Carlo simulation in evaluating admission decision implications. The authors also propose applying the model when using a computer simulation that deals with various CVD symptoms in clinical cohorts.

Aside from demonstrating the value of a Monte‐Carlo simulation as a powerful analysis tool, the paper's findings may prompt researchers to conduct a decision analysis with a Monte‐Carlo simulation in the healthcare environment.

The purpose of this paper is to develop a generic framework for hybrid (integrated deployment of system dynamics and discrete event simulation) simulation which can be applied in the healthcare domain.

As hybrid simulation in an organisational context is a new topic with limited available data on deployment of hybrid simulation in organisational context, an inductive approach has been applied. On the basis of knowledge induced from literature, a generic conceptual framework for hybrid simulation has been developed. The proposed framework is demonstrated using an explanatory case study comprising an accident and emergency (A&E) department.

The framework provided detailed guidance for the development of a hybrid model of an A&E case study. Findings of this case study suggest that the hybrid model was more efficient in capturing behavioural impact on operational performances.

The framework is limited to only SD and DES; as agent‐based is another simulation method which is emerging as a promising tool for analysing problems such as spread of infectious diseases in healthcare context, inclusion of this into the framework will enhance the utility of the framework.

This framework will aid in the development of hybrid models capable of comprehending both detail as well as dynamic complexity, which will contribute towards a deeper understanding of the problems, resulting in more effective decision making.

It is expected that this research will encourage those engaged in simulation (e.g. researchers, practitioners, decision makers) to realise the potential of cross‐fertilisation of the two simulation paradigms.

Currently, there is no conceptual framework which provides guidance for developing hybrid models. In order to address this gap, this paper contributes by proposing a conceptual framework for hybrid simulation for the healthcare domain.

The Emergency Department (ED) at Grand River Hospital in Kitchener, Ontario sought insight into strategies that would reduce patient length of stay and queuing for initial assessment. The purpose of this paper is to focus on the ED's operational level and determine an optimal fast track strategy to improve performance measures.

The paper describes the application of discrete event simulation to the ED's “fast track” system and determines an optimal fast track strategy to improve performance measures. Topics discussed include: the design and development process for the simulation model, proposed operational strategies, and the analysis of scenarios for optimizing fast track.

Length of stay and queue length were most significantly reduced when there was an increased physician presence in the fast track system, followed by an additional emergency nurse practitioner in the system. Finally, the implementation of See‐and‐treat had a negligible effect on both performance measures for fast‐tracked patients.

Using real data, the effectiveness of a number of fast track strategies within a hospital ED were evaluated, which have practical implications for reducing patient wait times in ERs. This would be most valuable to practitioners in areas such as health service research, simulation modeling, and health service delivery.

Purpose – Aims to describe a project carried out within Hampshire Social Services investigating potential care pathways for older people after discharge from hospital and to show the potential of the simulation methodology in such situations. Design/methodology/approach – A discrete‐event simulation was used to determine the system capacities and to estimate the likely associated reimbursement costs. Findings – A prototype simulation model was developed showing the potential value of this approach. Research limitations/implications – Restrictions in data access shifted the focus from quantitative service mapping to a more descriptive approach. Practical implications – Currently, many older patients experience delayed discharge from acute beds because of capacity limitations in Social Services’ traditional post‐acute care services. At the same time, new regulations require Local Authorities to reimburse NHS Acute Trusts if hospital discharge is delayed solely due to inadequate provision of social care assessments and services. In order to overcome the so‐called “bed‐blocking” problem, a new range of services termed “Intermediate Care” has been introduced to offer alternative options for older patients. These services are examined in terms of capacity and appropriateness. Originality/value – This paper fulfils an identified need to record and evaluate the new post‐acute packages introduced by the Social Services and NHS and proposes simulation as one of the most suitable methodologies for such objectives.