SimLean: Utilising simulation in the implementation of lean in healthcare

Discrete-event simulation (DES) and lean are approaches that have a similar motivation: improvement of processes and service delivery. Both are being used to help improve the delivery of healthcare, but rarely are they used together. This paper explores from a theoretical and an empirical perspective the potential complementary roles of DES and lean in healthcare. The aim is to increase the impact of both approaches in the improvement of healthcare systems. Out of this exploration, the ‘SimLean’ approach is developed in which three roles for DES with lean are identified: education, facilitation and evaluation. These roles are demonstrated through three examples of DES in action with lean. The work demonstrates how the fusion of DES with lean can improve both stakeholder engagement with DES and the impact of lean.     

Key performance indicators for successful simulation projects

There are many factors that may contribute to the successful delivery of a simulation project. To provide a structured approach to assessing the impact various factors have on project success, we propose a top-down framework whereby 15 Key Performance Indicators (KPI) are developed that represent the level of successfulness of simulation projects from various perspectives. They are linked to a set of Critical Success Factors (CSF) as reported in the simulation literature. A single measure called Project’s Success Measure (PSM), which represents the project’s total success level, is proposed. The framework is tested against 9 simulation exemplar cases in healthcare and this provides support for its reliability. The results suggest that responsiveness to the customer’s needs and expectations, when compared with other factors, holds the strongest association with the overall success of simulation projects. The findings highlight some patterns about the significance of individual CSFs, and how the KPIs are used to identify problem areas in simulation projects.     

Overcoming the barriers: a qualitative study of simulation adoption in the NHS

This paper addresses a key issue in the health OR literature, namely the apparent failure of OR modelling to become embedded and widely implemented within healthcare organisations. The research presented here is a case study to evaluate the adoption of one particular simulation modelling tool, Scenario Generator (S:G), which was developed by the SIMUL8 Corporation in a PPI partnership with the UK's National Health Service (NHS) Institute for Innovation and Improvement. The study involved semi-structured interviews with employees of 28 Primary Care Trusts who had all been engaged in some way with the initiative, with participants classified as ‘Not Started’, ‘Given Up’ and ‘Actively Using’. This paper presents a brief summary of barriers and facilitators to the successful use of the S:G software, but its main purpose is to focus more broadly on factors influencing the successful adoption of simulation tools in general within healthcare organisations. The insights gained in this study are relevant to improving the uptake of OR modelling in general within the NHS.     

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.     

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

Existing approaches to conceptual modelling (CM) in discrete-event simulation 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 CM requirements.     

Conceptual modelling and the project process in real simulation projects: a survey of simulation modellers

A survey was used to obtain information on the processes and methods used by simulation experts in real projects. The 102 survey respondents answered questions about their most recent simulation project. This paper presents some of the survey results, focussing mainly on conceptual modelling and the pattern of time allocation to different topics. There are a wide range of findings that include the modellers making changes to the initial conceptual model during subsequent tasks in most of the projects usually by adding complexity, model coding taking on average about twice the time of other topics, and the topics generally occurring in single blocks of time (at the resolution of the survey data collection) but with considerable overlaps. The results give an insight into the way experts approach simulation projects and their problem solving strategies. A potential application is in training novice modellers, particularly in developing ‘craft skills’. The results also provide an empirical basis for further research, especially in conceptual modelling.     

Polar and singular value decomposition of 3×3 magic squares

In the literature there have been reported a number of studies of probabilities involved in Monopoly, the worldwide popular game designed by Charles B. Darrow in the 1930s. Simple assumptions often lead to inaccurate results. In this paper, having distinguished between ‘In Jail’ and ‘Just Visiting’, both theoretical computations and computer simulations are conducted to determine the probability of landing on ‘JAIL’. Theoretical and simulation results are consistent. The sum of the probabilities of landing on ‘In Jail’ and ‘Just Visiting’ is found to be 6.40%, both in theory and in simulation, compared with Ian Stewart's 5.89%. The long-term probabilities of landing on the other 39 spaces are computed and it is concluded that the best properties to buy are the orange ones.     

Simulation in manufacturing and business: A review

This paper reports the results of a review of simulation applications published within peer-reviewed literature between 1997 and 2006 to provide an up-to-date picture of the role of simulation techniques within manufacturing and business. The review is characterised by three factors: wide coverage, broad scope of the simulation techniques, and a focus on real-world applications. A structured methodology was followed to narrow down the search from around 20,000 papers to 281. Results include interesting trends and patterns. For instance, although discrete event simulation is the most popular technique, it has lower stakeholder engagement than other techniques, such as system dynamics or gaming. This is highly correlated with modelling lead time and purpose. Considering application areas, modelling is mostly used in scheduling. Finally, this review shows an increasing interest in hybrid modelling as an approach to cope with complex enterprise-wide systems.     

Kriging for interpolation in random simulation

Whenever simulation requires much computer time, interpolation is needed. Simulationists use different interpolation techniques (eg linear regression), but this paper focuses on Kriging. This technique was originally developed in geostatistics by DG Krige, and has recently been widely applied in deterministic simulation. This paper, however, focuses on random or stochastic simulation. Essentially, Kriging gives more weight to ‘neighbouring’ observations. There are several types of Kriging; this paper discusses—besides Ordinary Kriging—a novel type, which ‘detrends’ data through the use of linear regression. Results are presented for two examples of input/output behaviour of the underlying random simulation model: Ordinary and Detrended Kriging give quite acceptable predictions; traditional linear regression gives the worst results.     

Using hydropower to smooth intermittent and unreliable sources of generation

This work describes, in part, the extent to which the large hydropower system on the Snake and Columbia rivers, and tributaries, could be used to ‘smooth’ or level the intermittent contributions of large numbers of wind generators, so that the sum of these contributions becomes reliable. Data for wind generators on site is given, the methods by which the ‘smoothing’ would occur is described, and a computer simulation model of the Pacific Northwest hydropower system is used to develop several case studies. The several constraints imposed on the flexibility of the hydropower system are defined by streamflow restrictions at the hydropower projects.     

Writing practitioner case studies to help behavioural OR researchers ground their theories: application of the mangle perspective

Behavioural research into the practice of OR needs to be grounded. Case studies written by practitioners can potentially help address this need but currently most do not. The paper explores a way of describing OR projects that place the emphasis on the ‘actors’ who provide the motivating force and the consequences of their actions. The ‘mangle’ perspective focuses on the dynamic intertwining of people, technology and concepts; this can provide the basis for an insightful narrative describing the reality of the project in terms of the planned approach, the problems met and the outcomes. Two examples are given, one of a conventional model building exercise, the second of a ‘soft OR’ intervention: both describe projects conducted by practitioners for commercial purposes. It is concluded that, by using the mangle perspective, the OR case writer can winnow the wheat from the chaff in order to write a succinct informative narrative, a narrative that could be utilized by behavioural OR (BOR) researchers. It is further concluded that BOR researchers should engage with ‘practice theory’ to deepen their understanding of what actually happens in projects.     

Using 3D Animation Techniques to Help with the Experimental Design and Analysis Phase of a Visual Interactive Simulation Project

This paper describes an interactive 3D animation approach that may help with the investigation, understanding and interpretation of results for a Visual Interactive Simulation (VIS) project. The method uses a graphics algorithm to draw on a computer screen ‘3D contour maps’ which show the response of a simulation model to changes in its input parameters. A previous paper showed that it is possible for a neural network to learn the response of a simulation. This paper shows that the speed of response of a neural network can be exploited so that 3D animation sequences of the simulation's results can be produced. It is possible to rotate the ‘3D contour map’, zoom, pan, or generally view the projection from different perspectives. Two example problems are described. The paper suggests that this approach can further improve the quality of VIS by being able to give comprehensive graphic 3D sensitivity analyses to the original problem under investigation.     

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 today's 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.     

Systemic risk assessment: a case study

Project Risk Registers have been used extensively for many years. However, they do not account for the interaction between risks, for example, the occurrence of one risk exacerbating other risks or portfolios of risks being more significant than the sum of the individual risks. This leads to the need to consider ‘risk systemicity’ as a part of risk analysis. This paper reports on a specific case for a large multinational project based organization, one that the authors had been involved with in the analysis of a number of projects that had massive cost overruns. Following these analyses the organization was persuaded of the importance of risk systemicity. The organization therefore engaged the authors to develop a ‘Risk Filter’. This filter is a tool for identifying areas of risk exposure on future projects and creating a framework for their investigation. The ‘Risk Filter’ is now used on all projects ever since its introduction; by the end of May 2003 it had been used by nine divisions, on over 60 major projects, and completed by 450 respondents. It is also used at several stages during the life of a project to aid in the risk assessment and management of each project, and contributes to a project database.     

A generalized activity network model

In recent years activity networks for projects with both random and deterministic alternative outcomes in key nodes have been considered. The developed control algorithm chooses an optimal outcome direction at every deterministic alternative node which is reached in the course of the project's realization. At each routine decision-making node, the algorithm singles out all the subnetworks (the so-called joint variants) which correspond to all possible outcomes from that node. Decision-making results in determining the optimal joint variant and following the optimal direction up to the next decision-making node. However, such models cover a limited class of alternative networks, namely, only fully-divisible networks which can be subdivided into nonintersecting fragments. In this paper, a more generalized activity network is considered. The model can be applied to a broader spectrum of R&D projects and can be used for all types of alternative networks, for example, for non-divisible networks comprising nodes with simultaneously ‘must follow’, random ‘exclusive OR’ and deterministic ‘exclusive or’ emitters. The branching activities of the third type refer to decision-making outcomes; choosing the optimal outcome is the sole prerogative of the project's management. Such a model is a more universal activity network; we will call it GAAN—Generalized Alternative Activity Network. The problem is to determine the joint variant optimizing the mean value of the objective function subject to restricted mean values of several other criteria. We will prove that such a problem is a NP-complete one. Thus, in general, the exact solution of the problem may be obtained only by looking through all the joint variants on the basis of their proper enumeration. To enumerate the joint variants we will use the lexicographical method in combination with some techniques of discrete optimization. A numerical example will be presented. Various application areas are considered.     

Mixing methodologies to enhance the implementation of healthcare operational research

Healthcare Operational Research (OR) has had limited success in achieving a sufficient level of stakeholder acceptance to lead to implementation of results. This research study is aimed at combining OR methodologies to achieve greater acceptance of results for organizational change. Patient flow delays in the Paediatric intensive care unit (PICU) at Children's Hospital of Wisconsin were identified using case studies. Patient flow was modelled using hard OR (simulation) using case study findings, with active stakeholder participation, and enhanced with outcomes research. Outcomes research allowed achieving greater clinical relevance of OR findings. Results from hard OR, particularly for politically sensitive issues, were persuasive but inadequate to result in change. Soft OR (cognitive mapping) was used to identify new issues and enhance results. Consequently, the planned PICU expansion was deferred, and resources focused on improving staffing strategies identified independently from both hard and soft OR. These findings suggest that: (1) Outcomes research can play a unique role to enhance results in healthcare OR. (2) After obtaining a holistic understanding of the system using hard and soft OR, stakeholders are willing to implement results from each independently, supporting the development of a common form of knowledge, which is consistent with Mixed-Mode Modelling. (3) Hard OR, enhanced with outcomes research, with active stakeholder participation, and combined with soft OR, results in greater acceptance and sustained organizational change.     

Problem structuring methods: theorizing the benefits of deconstructing sustainable development projects

Problem structuring methods or PSMs are widely applied across a range of variable but generally small-scale organizational contexts. However, it has been argued that they are seen and experienced less often in areas of wide ranging and highly complex human activity—specifically those relating to sustainability, environment, democracy and conflict (or SEDC). In an attempt to plan, track and influence human activity in SEDC contexts, the authors in this paper make the theoretical case for a PSM, derived from various existing approaches. They show how it could make a contribution in a specific practical context—within sustainable coastal development projects around the Mediterranean which have utilized systemic and prospective sustainability analysis or, as it is now known, Imagine. The latter is itself a PSM but one which is ‘bounded’ within the limits of the project to help deliver the required ‘deliverables’ set out in the project blueprint. The authors argue that sustainable development projects would benefit from a deconstruction of process by those engaged in the project and suggest one approach that could be taken—a breakout from a project-bounded PSM to an analysis that embraces the project itself. The paper begins with an introduction to the sustainable development context and literature and then goes on to illustrate the issues by grounding the debate within a set of projects facilitated by Blue Plan for Mediterranean coastal zones. The paper goes on to show how the analytical framework could be applied and what insights might be generated.     

The role of feedback dynamics in disruption and delay on the nature of disruption and delay (D&D) in major projects

The idea that small disruptions and delays can cause serious consequences to the life of a major project, well beyond that which might be easily attributed to their direct impact, is well established. Nevertheless, the nature of this ‘delay and disruption’ is still not fully understood. This paper discusses some of the issues and difficulties in gaining a full understanding. In particular it presents the variety of ways in which disruptions occur, and the variety of consequences that may unfold. It also focuses attention on a number of issues that arise when ‘normal’ methods of analysis of complex projects might be used, for example, the analysis and costing of change orders and the use of network analysis. The role of dynamic feedback and the ‘portfolio effect’ is introduced, particularly with reference to project acceleration and changing productivity.     

Helping Managers Manage

Do conventional management accounts help managers manage? This paper argues that the answer to this question is ‘No’, primarily because conventionally prepared budgets are not accepted by managers as valid measures of performance as a result of either forecasting errors in the data used in the original budget or weaknesses in the simulation algorithms inherent in the budget. The paper then suggests that management accounts can be made more meaningful by incorporating within the management accounting system a ‘resource management system’, the basis of which is a powerful simulation model.