Brian Dangerfield

Modelling the feedback effects of reconfiguring health services

The shift in the balance of health care, bringing services ‘closer to home’, is a well-established trend, which has been motivated by the desire to improve the provision of services. However, these efforts may be undermined by the improvements in access stimulating demand. Existing analyses of this trend have been limited to isolated parts of the system with calls to control demand with stricter clinical guidelines or to meet demand with capacity increases. By failing to appreciate the underlying feedback mechanisms, these interventions may only have a limited effect. We demonstrate the contribution offered by system dynamics modelling by presenting a study of two cases of the shift in cardiac catheterization services in the UK. We hypothesize the effects of the shifts in services and produce model output that is not inconsistent with real world data. Our model encompasses several mechanisms by which demand is stimulated. We use the model to clarify the roles for stricter clinical guidelines and capacity increases, and to demonstrate the potential benefits of changing the goals that drive activity.

Judgement and supply chain dynamics

Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and ‘laboratory’ studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper.

Optimisation as a statistical estimation tool: an example in estimating the AIDS treatment‐free incubation period distribution

The identification of the AIDS incubation period distribution, together with its parameters, is a vital component of any epidemiological model designed to portray scenarios concerning future trends in reported AIDS cases or to evaluate intervention strategies. The Transfusion-Associated dataset of AIDS cases in the U.S.A. can be utilised in this identification process. By employing an appropriate system dynamics software tool an optimisation approach to the fitting process has been conducted. However, although the task of interpreting a best fit using parametric methods is hampered because, in particular, the data are right-censored, the results do provide a template against which to judge the effects of recent treatment advances in delaying progression to AIDS. As a case study in system dynamics optimisation, this demonstrates the need to use a powerful tool with care: considerations other than the best objective function, together with its resultant parameter set, have to be taken into account. The results show that a three-stage distribution, with unequal phases at each stage, is an appropriate incubation time model to employ in situations where projections of future AIDS incidence are being attempted. The work is also an affirmation of the utility of the system dynamics approach insofar as real-world complications can be easily handled in model formulation. Copyright

Complex systems in finance and econometrics

47 entries drawn from three sections of the Encyclopedia of Complexity.- Agent Based Modeling and Simulation.- Finance and Econometrics.- System Dynamics.

Modelling the sustainability of mass tourism in island tourist economies

Tourism is one of the worlds largest industries and is a source of jobs across national and regional economies. Assessing the economic, environmental and social impacts of tourism development has become a major activity within the tourism and sustainable development communities. The purpose of this research is to demonstrate the contribution of system dynamics for analysing policies that can not only promote sustainable tourism development, but also act as a warning signal to the industry about the potential negative consequences of uncontrolled growth of mass tourism, particularly in island tourist economies. Previous research in the tourism sector has been fragmented, when a holistic approach is needed in order to try to coerce some alignment in the views of the various stakeholders. The main research results illustrated in this paper are: a generic model of a tourism system informed by the (mainly) South European island tourist economies and a set of scenarios illustrating examples of policy analysis. The generic model and the modelling process developed in this research will have some transferability to other issues concerned with policymaking for sustainable development.

A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

This paper examines the development of clinical pathways (CP) in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system is developed and analysed for this purpose. The study highlights the scenarios that will help hospital administrators to redistribute caseloads among admitting clinicians with a focus on multiple diagnostic-related groups (DRGs) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRGs are the best known classification system used in a casemix funding model. Casemix is a DRG-based government funding model for hospitals with a mix of performance measures aiming to reward initiatives that increase efficiencies in hospitals. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that it can enhance group learning processes and improve decision making. The findings are supported by other recent studies of CP implementation on various DRGs. These showed substantial reduction in length of stay, costs and resource utilization.

Understanding construction competitiveness: the contribution of system dynamics

Purpose – Construction sector competitiveness has been a subject of interest for many years. Research too often focuses on the means of overcoming the “barriers to change” as if such barriers were static entities. There has been little attempt to understand the dynamic inter‐relationship between the differing factors which impinge upon construction sector competitiveness. The purpose of this paper is to outline the benefits of taking a systems approach to construction competitiveness research.Design/methodology/approach – The system dynamics (SD) modelling methodology is described. This can provide practitioners with “microworlds” within which they can explore the dynamic effects of different policy decisions. The data underpinning the use of SD was provided by interviews and case study research which allowed an understanding of the context within which practitioners operate.Findings – The over‐riding conclusion is that the SD methodology has been shown to be capable of providing a means to assess the for...

A strategic evaluation of capacity retirements in the steel industry

Over the past twenty-five years there has been a significant reduction in UK iron and steel making capacity. This has happened primarily as a result of a deliberate strategy which places emphasis on maintaining or improving financial performance. An unanticipated but possible scenario of the consequences of this strategy is offered by means of a system dynamics model. It considers both short and long term effects and represents an aid to learning in the face of the complexity which characterises manufacturing operations.

The system dynamics modelling process and DYSMPA2

Abstract Recent work on the practice of strategic policy-making has highlighted how a model can be introduced to make the process more effective. System dynamics models are particularly appropriate for inclusion in this emerging framework for the debate of policy issues. The procedural framework integrates ideas from group decision support systems, boardroom systems and scenario generation and requires particular features in the system dynamics modelling software employed. Consideration is given to those specific features of the DYSMAP2 software which meet the need of senior managerial groups who are faced with the resolution of policy issues.

Models for Infectious Human Diseases: Relating a transmission model of AIDS spread to data: some international comparisons

Identification means having concealed bearer identifying indicia in the form of a hologram.