The costs and benefits of bowel cancer service developments using discrete event simulation

Colorectal cancer includes cancerous growths in the colon, rectum and appendix and affects around 30?000 people in England each year. Maximizing health benefits for patients with colorectal cancer requires consideration of costs and outcomes across the whole service. In an era of scarce healthcare resources, there is a need to consider not only whether technologies and services may be considered clinically effective, but also whether they are cost-effective, that is, whether they represent value for money for the health service. Through the development of a whole disease model, it is possible to evaluate the cost-effectiveness of a range of options for service development consistently within a common framework. Discrete event simulation has been used to model the complete colorectal cancer patient pathway from patient presentation through to referral and diagnosis, treatment, follow-up, potential recurrence, treatment of metastases and end-of-life care. This simulation model has been used to examine the potential cost-effectiveness of different options for change across the entire colorectal cancer pathway. This paper provides an empirical demonstration of the potential application of modelling entire disease areas to inform clinical policy and resource allocation decision-making.     

Combined Discrete-event Simulation and Ant Colony Optimisation Approach for Selecting Optimal Screening Policies for Diabetic Retinopathy

In this paper we present the first application to a healthcare problem of discrete-event simulation (DES) embedded in an ant colony optimisation (ACO) model. We are concerned with choosing optimal screening policies for retinopathy, a sight-threatening complication of diabetes. The early signs of retinopathy can be detected by screening before the patient is aware of symptoms, and blindness prevented by laser treatment. In this paper we describe the methodology used to combine the purpose-written DES model with the ACO algorithm. We simulate the effects of different screening strategies on a population of diabetic patients, and compare them in terms of two objective functions: Min C/E, cost-effectiveness (minimum incremental cost per year of sight saved, compared with a no-screening baseline) and Max E, maximum effectiveness (years of sight saved). We describe how ACO is used to optimise these two objectives, and discuss the issues involved in optimising stochastic variables. We present results for a range of different assumptions and scenarios about the format of screening programmes, using realistic data, and make policy recommendations on the basis of our findings.     

Combining discrete-event simulation and system dynamics in a healthcare setting: A composite model for Chlamydia infection

This paper presents a composite model in which two simulation approaches, discrete-event simulation (DES) and system dynamics (SD), are used together to address a major healthcare problem, the sexually transmitted infection Chlamydia. The paper continues an on-going discussion in the literature about the potential benefits of linking DES and SD. Previous researchers have argued that DES and SD are complementary approaches and many real-world problems would benefit from combining both methods. In this paper, a DES model of the hospital outpatient clinic which treats Chlamydia patients is combined with an SD model of the infection process in the community. These two models were developed in commercial software and linked in an automated fashion via an Excel interface. To our knowledge this is the first time such a composite model has been used in a healthcare setting. The model shows how the prevalence of Chlamydia at a community level affects (and is affected by) operational level decisions made in the hospital outpatient department. We discuss the additional benefits provided by the composite model over and above the benefits gained from the two individual models.     

Exploring the model development process in discrete-event simulation: insights from six expert modellers

This paper explores the model development process in discrete-event simulation (DES) by reporting on an empirical study that follows six expert modellers while building simulation models. DES is a widely used modelling approach, however little is known about the modelling processes and methodology adopted by modellers in practice. Verbal Protocol Analysis is used to collect data, where the participants are asked to speak aloud while modelling. The results show that the expert modellers spend a significant amount of time on model coding, verification and validation, and data inputs. The modellers iterate often between modelling activities. Patterns of modelling behaviour are identified, suggesting that the modellers adopt distinct modelling styles. This study is useful in that it provides an empirical view of existing DES modelling practice, which in turn can inform existing research and simulation practice as well as teaching of DES modelling to novices.     

Incorporating human behaviour in simulation models of screening for breast cancer

Simulation modelling is widely used in many industries in order to assess and evaluate alternative options and to test strategies or operating rules which are too complex to be modelled analytically. Simulation software has developed its capability in parallel with the growth in computing power since the 1980s. However in practice, the results from the most sophisticated and complex simulation model may not truly reflect what happens in the real world, because such models do not account for human behaviour. For example, in the domain of healthcare simulation is often used to evaluate the outcomes from medical interventions such as new drug treatments. However in reality patients may not complete the course of a prescribed medication, perhaps because they find the side-effects unpleasant. A simulation study designed to evaluate this medication which ignores such behavioural factors may give unreliable results. In this paper we describe a model for screening for breast cancer which includes behavioural factors to model women’s decisions to attend for mammography. The model results indicate that increasing attendance through education or publicity campaigns can be equally as effective as decreasing the intervals between screens. This would have considerable cost implications for healthcare providers.     

Model development in discrete-event simulation and system dynamics: An empirical study of expert modellers

An empirical study comparing the model development process followed by experts in discrete-event simulation (DES) and system dynamics (SD) modelling is undertaken. verbal protocol analysis (VPA) is used to study the modelling process followed by ten expert modellers (5 SD and 5 DES). Participants are asked to build simulation models based on a case study and to think aloud while modelling. The generated verbal protocols are divided into seven modelling topics: problem structuring, conceptual modelling, data inputs, model coding, verification & validation, results & experimentation and implementation and then analyzed. Our results suggest that all modellers switch between modelling topics, however DES modellers follow a more linear progression. DES modellers focus significantly more on model coding and verification & validation, whereas SD modellers on conceptual modelling. Observations are made revealing some interesting differences in the way the two groups of modellers tackle the case. This paper contributes towards the comparison of DES and SD.     

Emergency and on-demand health care: modelling a large complex system

This paper describes how system dynamics was used as a central part of a whole-system review of emergency and on-demand health care in Nottingham, England. Based on interviews with 30 key individuals across health and social care, a ‘conceptual map’ of the system was developed, showing potential patient pathways through the system. This was used to construct a stock-flow model, populated with current activity data, in order to simulate patient flows and to identify system bottle-necks. Without intervention, assuming current trends continue, Nottingham hospitals are unlikely to reach elective admission targets or achieve the government target of 82% bed occupancy. Admissions from general practice had the greatest influence on occupancy rates. Preventing a small number of emergency admissions in elderly patients showed a substantial effect, reducing bed occupancy by 1% per annum over 5 years. Modelling indicated a range of undesirable outcomes associated with continued growth in demand for emergency care, but also considerable potential to intervene to alleviate these problems, in particular by increasing the care options available in the community.     

A simulation approach to cost-effectiveness and cost-benefit calculations of screening for the early detection of disease

The computer simulation program Miscan, developed for analysis, prediction and optimization of screening for early detection of disease, has been extended to enable full cost-effectiveness and cost-benefit calculations. The user specifies which of the available cost- and effectiveness-items are to be used and can choose the valuation per unit for each item. The program computes the volume of each item for scenarios with and without screening, and calculates the costs and effectiveness of the simulated screening policy. The program allows for discounting and present value computations, for scale effects, and for quality adjustment of life years for age and disease stage. The use of the program is illustrated with a model of cervical cancer screening that was based on data from the pilot project in the Netherlands. Two screening policies are compared for several discount rates, and for several exchange rates between costs and health effects.     

The DH Accident and Emergency Department model: a national generic model used locally

The Department of Health (DH) Accident and Emergency (A&E) simulation model was developed by Operational Research analysts within DH to inform the national policy team of significant barriers to the national target, for England, that 98% of all A&E attendances are to be completed (discharged, transferred or admitted) within 4?hours of arrival by December 2004. This paper discusses why the model was developed, the structure of the model, and the impact when used to inform national policy development. The model was then used as a consultancy tool to aid struggling hospital trusts to improve their A&E departments. The paper discusses these experiences with particular reference to the challenges of using a ‘generic’ national model for ‘specific’ local use.     

Comparing discrete-event simulation and system dynamics: users' perceptions

This paper is the first of its type in that it provides an empirical study comparing the two simulation approaches of discrete-event simulation (DES) and system dynamics (SD). Prior comparison work is limited and mostly based on the authors' personal opinions. In the present work, the comparison is based on managers' (executive MBA students) perceptions of two simulation models of the same problem, one in DES and one in SD. The study found that there is no significant difference from the users' point of view between DES and SD in terms of model understanding and model usefulness. Some minor differences were found in terms of complexity and validity of the models, and the model results. The implications of our findings regarding model understanding, model complexity, model validity, model usefulness and model results are discussed.     

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.     

Evaluation of strategies for Downs Syndrome screening

Downs Syndrome is a chromosomal disorder affecting approximately 1 in 700 live births in unscreened populations. Definitive prenatal diagnostic tests are available but they are invasive and can cause miscarriages. Non-invasive tests earlier in pregnancy have the potential for identifying pregnancies that are at sufficient risk to warrant the invasive diagnostic test being performed. A model has been developed to evaluate possible screening strategies. Although at first sight this problem seems amenable to traditional decision analysis, our alternative method has proved more fruitful. The method can be used to derive closed form analytical expressions for a number of relevant outcome measures. This modelling allows the study of the effect of the timings of the two tests within pregnancy, optimisation of screening options and investigation of effects related to diagnostic accuracy.     

Strong consistency of the empirical martingale simulation option price estimator

A simulation technique known as empirical martingale simulation （EMS） was proposed to improve simulation accuracy. By an adjustment to the standard Monte Carlo simulation, EMS ensures that the simulated price satisfies the rational option pricing bounds and that the estimated derivative contract price is strongly consistent with payoffs that satisfy Lipschitz condition. However, for some currently used contracts such as self-quanto options and asymmetric or symmetric power options, it is open whether the above asymptotic result holds. In this paper, we prove that the strong consistency of the EMS option price estimator holds for a wider class of univariate payoffs than those restricted by Lipschitz condition. Numerical experiments demonstrate that EMS can also substantially increase simulation accuracy in the extended setting.     

Waiting list behaviour and the consequences for NHS targets

The United Kingdom's National Health Service (NHS) is investing considerable resources in reducing patient waiting times for elective treatment. This paper describes the development of a waiting list model and its use in a simulation to assess management options. Simulation usually assumes that waiting is adequately described by simple queuing disciplines, typically first-in-first-out. However, waiting in the United Kingdom's NHS is a more complex phenomenon. The waiting list behaviour is explored through an analysis of the changes in waiting time distributions for elective orthopaedics in one Scottish Health Board, NHS Fife. The evolving distributions suggest that there have been substantial changes in priorities in response to the various NHS targets. However, in the short or medium term, the form of the distribution appears reasonably stable, providing a basis for estimating future waiting times in different scenarios. A model of the waiting behaviour and prioritization in the appointment allocations was embedded in a simulation of the complete elective orthopaedic patient journey from referral, through outpatients and diagnostics to surgery. The model has been used to explore the consequences of various management options in the context of the NHS target that no patient should wait more than 18 weeks between referral and treatment.     

Global dynamics of a two-patch SIS model with infection during transport

A two-patch SIS model is formulated and studied. The standard incidence rate and mass-action incidence rate are used within each patch and during transport, respectively. The basic reproduction number is calculated and the global dynamics is investigated. The simulation results show the influence of travel rates, the different dynamics by using standard incidence rate and mass-action incidence rate. The importance of border screening is also explored by numerical simulation.     

Modelling and analysis of Canadian Forces strategic lift and pre-positioning options

This paper presents analysis of some of the strategic lift and pre-positioning issues within the context of rapid deployability to failed and failing states conducted for the Canadian Forces (CF). A simulation framework was developed to study the effectiveness of a variety of pre-positioning options. An aircraft loading optimization model based on a genetic annealing algorithm with a novel convex hull-based measure of effectiveness was also developed to analyse different strategic lift options. The model was used both to provide insights into the optimal mix of airlift capabilities and to conduct sensitivity analysis. Historical CF deployments provided a baseline performance measure against which several movement solutions were compared and contrasted. Analysis indicates that pre-positioning of equipment and supplies at various strategic locations and use of efficient mix of transport aircraft could be potential strategies for improvement of the CF's strategic lift capability.     

基地化保障模式下飞机四站装备需求确定研究

基地化保障模式对飞机保障资源需求的影响是制约其发展的重要问题.基于离散事件仿真(DES)方法建立了航空兵场站四站保障过程的数学模型,考虑了四站装备自身故障的影响,并在所建模型的基础上提出运用离散系统仿真软件ARENA对四站保障过程进行仿真.仿真结果表明,与现行的航空兵场站单机种保障策略相比,基地化保障模式能够减少各个机种通用的四站装备数量需求,而单个机种特有的四站装备需求不变.     

Parallel Simulation of a Compressible Jet Including Nozzle Modelling

Circular jet flows play an important role for many technical applications. Realistic simulations of such flows require modelling of the nozzle geometry to represent the turbulent state of the boundary layer at the nozzle exit. An available high-order finite-difference code for solving the compressible Navier-Stokes equations on a cylindrical grid was adapted to account for the nozzle geometry within the simulation domain. The code was parallelized using the message-passing interface MPI to be able to complete the simulations within acceptable turn-around times. Validation of the implementation was performed by checking the convergence behaviour of the spatial discretization schemes. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modelling of Shape Memory Alloys and Experimental Verification

Prestrained shape memory alloys change their length when heated above their transformation temperature. This effect can be used to generate high forces in a small workspace, which has particular advantages in actuator design. The optimization and control of the shape memory actuator requires a comprehensive simulation of the material behavior. However, many of the existing models are limited to specific load cases or offer rough approximations only. A material model for shape memory alloys from Seelecke [1] is examined in this paper. This model describes the behavior of a shape memory wire, which is heated by electric current. It is implemented in a simulation program to investigate the actuator output and to improve the performance. Finally, the parameters of the simulation are adapted to experimental results.