Navonil Mustafee

Applications of Simulation within the Healthcare Context

A large number of studies have applied simulation to a multitude of issues relating to healthcare. These studies have been published in a number of unrelated publishing outlets, which may hamper the widespread reference and use of such resources. In this paper, we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high-quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies’ results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied to healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques in solving diverse healthcare problems.

Profiling Literature in Healthcare Simulation

The publications that relate to the application of simulation to healthcare have steadily increased over the years. These publications are scattered amongst various journals that belong to several subject categories, including operational research, health economics and pharmacokinetics. The simulation techniques that are applied to the study of healthcare problems are also various. The aim of this study, therefore, is to review healthcare simulation literature that have been published between 1970 and 2007 in high-quality journals belonging to various subject categories and that report on the application of four simulation techniques, namely, Monte Carlo simulation, discrete-event simulation, system dynamics and agent-based simulation. Arguably, journal impact factor is fundamental in assessing the quality of publications. Thus, the 201 publications selected for review have been queried from the ISI Web of Science® bibliographic database of high-impact research journals. Through a review of healthcare simulation literature the following three objectives have been realized: (a) papers have been categorized under the different simulation techniques, and the healthcare problems that each technique is employed to investigate are identified; (b) variables such as authors, article citations, etc., within our dataset of healthcare papers have been profiled; (c) turning point (strategically important) papers and authors have been identified through co-citation analysis of references cited by the papers in our dataset. The above objectives have been realized by devising and then employing a methodology for profiling literature. It is expected that this review paper will help the readers gain a broader understanding of research in healthcare simulation.

Facilitating the Analysis of a UK National Blood Service Supply Chain Using Distributed Simulation

In an attempt to investigate blood unit ordering policies, researchers have created a discrete-event model of the UK National Blood Service (NBS) supply chain in the Southampton area of the UK. The model has been created using Simul8, a commercial off-the-shelf (COTS) discrete-event simulation package (CSP). However, as more hospitals were added to the model, it was discovered that the length of time needed to perform a single simulation severely increased. It has been claimed that distributed simulation, a technique that uses the resources of many computers to execute a simulation model, can reduce simulation runtime. Further, an emerging standardized approach exists that supports distributed simulation with CSPs. These CSP Interoperability (CSPI) standards are compatible with the IEEE 1516 standard, the High Level Architecture (HLA), the de facto interoperability standard for distributed simulation. To investigate if distributed simulation can reduce the execution time of NBS supply chain simulation, this paper presents experiences of creating a distributed version of the CSP Simul8 according to the CSPI/HLA standards. It shows that the distributed version of the simulation does indeed run faster when the model reaches a certain size. Further, we argue that understanding the relationship of model features is key to performance. This is illustrated by experimentation with two different protocols implementations (using Time Advance Request (TAR) and Next Event Request (NER)). Our contribution is therefore the demonstration that distributed simulation is a useful technique in the timely execution of supply chains of this type and that careful analysis of model features can further increase performance.

Hybrid simulation for modelling large systems: an example of integrated care model

Developing models for large systems is not a trivial task. Using only Discrete Event Simulation (DES) as a modelling technique may mean that the complexity of the underlying model will increase exponentially with the size of the model. An alternative to this is the use of System Dynamics (SD) for modeling large systems using the positive and negative feedback loops. However, for modelling a human-centric system like healthcare, DES is important as it provides individuality analysis; similarly, SD is important as it facilitates the whole systems approach. The combined application of OR/Simulation methods enable the symbiotic realization of the strengths of individual techniques, while reducing their limitations; in this paper it is suggested that a combined SD-DES approach (also referred to as hybrid technique) can be effectively used for modelling large systems. The example being used in this context is the modelling of an Integrated Care (IC) system in healthcare.

Edutainment for Sustainable Development

Background. The ever-increasing demand for natural resources has led to the continuing depletion of resources. Reversing this trend will require knowledge of effective environmental management strategies and adoption of sustainable development practices by society at large. Thus, it is critical that citizens increase their awareness of sustainability and acquire managerial skills required to effect change. Use of decision games for teaching sustainable development is a step in this direction. Games present great opportunities as tools of edutainment (educational entertainment) for teaching and training, with positive effects on learning outcomes. Aim and Method. In this article, we undertake a methodological review of games on sustainable development, analyzing their underlying characteristics, including the stated focus of the games, game availability, number of players and their roles, their target age, game validation and evaluation, stakeholder involvement in game development, learning outcomes, and so on. A total of 49 games are included in this survey. Conclusion. Our findings suggest that the games used for teaching sustainable development have generally increased players’ understanding of issues around sustainability and have enhanced their knowledge of sustainable development strategies. Our classification of the games’ characteristics assists educational instructors and potential learners in identifying games that are best suited for their teaching and learning needs.

Comparing conventional and distributed approaches to simulation in a complex supply-chain health system

Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with todays powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a ‘conventional’ approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations.

Towards Simulating the Internet of Things

There is an increasing interest in Internet of Things (IoT) and healthcare is considered to be one of the most common applications of it. Using the IoT paradigm, various devices including smart-phones and sensor-embedded healthcare applications can be used for monitoring health. In this study, we model an IoT use case scenario with regard to monitoring the activities associated with health. In particular, we present our use case using the SimIoT extended simulation toolkit to demonstrate the various functions and the interactions occurring within the IoT-enabled healthcare context. Specifically, we extend the functionalities of the SimIC simulation toolkit by adding the IoT layer that incorporates IoT devices which generated data for the private clouds. We focus our experimental analysis from the perspective of cloud performance to illustrate the turnaround and make span of the system.

Commercial-off-the-shelf simulation package interoperability: issues and futures

Commercial-Off-The-Shelf Simulation Packages (CSPs) are widely used in industry to simulate discrete-event models. Interoperability of CSPs requires the use of distributed simulation techniques. Literature presents us with many examples of achieving CSP interoperability using bespoke solutions. However, for the wider adoption of CSP-based distributed simulation it is essential that, first and foremost, a standard for CSP interoperability be created, and secondly, these standards are adhered to by the CSP vendors. This advanced tutorial is on an emerging standard relating to CSP interoperability. It gives an overview of this standard and presents case studies that implement some of the proposed standards. Furthermore, interoperability is discussed in relation to large and complex models developed using CSPs that require large amount of computing resources. It is hoped that this tutorial will inform the simulation community of the issues associated with CSP interoperability, the importance of these standards and its future.

Distributed computing and modeling & simulation: speeding up simulations and creating large models

Distributed computing has many opportunities for Modeling and Simulation (M&S). Grid computing approaches have been developed that can use multiple computers to reduce the processing time of an application. In terms of M&S this means simulations can be run very quickly by distributing individual runs over locally or remotely available computing resources. Distributed simulation techniques allow us to link together models over a network enabling the creation of large models and/or models that could not be developed due to data sharing or model reuse problems. Using real-world examples, this advanced tutorial discusses how both approaches can be used to benefit M&S researchers and practitioners alike.

Distributed simulation with COTS simulation packages: a case study in health care supply chain simulation

The UK National Blood Service (NBS) is a public funded body that is responsible for distributing blood and associated products. A discrete-event simulation of the NBS supply chain in the Southampton area has been built using the commercial off-the-shelf simulation package (CSP) Simul8. This models the relationship in the health care supply chain between the NBS processing, testing and issuing (PTI) facility and its associated hospitals. However, as the number of hospitals increase simulation run time becomes inconveniently large. Using distributed simulation to try to solve this problem, researchers have used techniques informed by SISOs CSPI PDG to create a version of Simul8 compatible with the high level architecture (HLA). The NBS supply chain model was subsequently divided into several sub-models, each running in its own copy of SimulS. Experimentation shows that this distributed version performs better than its standalone, conventional counterpart as the number of hospitals increases