The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance.System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy.

https://ajph.aphapublications.org/doi/pdfplus/10.2105/AJPH.2005.062059

System dynamics modeling for public health: background and opportunities.

Discrete Event Simulation (DES) has been widely used in modelling health-care systems for many years and a simple citation analysis shows that the number of papers published has increased markedly since 2004. Over the last 30 years several significant reviews of DES papers have been published and we build on these to focus on the most recent era, with an interest in performance modelling within hospitals. As there are few papers that propose or illustrate general approaches, we classify papers according to the areas of application evident in the literature, discussing the apparent lack of genericity. There is considerable diversity in the objectives of reported studies and in the consequent level of detail: We discuss why specificity dominates and why more generic approaches are rare.

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Discrete event simulation for performance modelling in health care: a review of the literature

A review of the recent contribution of systems thinking to operational research and management science

We provide a comprehensive overview of the typical decisions to be made in resource capacity planning and control in health care, and a structured review of relevant articles from the field of Operations Research and Management Sciences (OR/MS) for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making.

/pdf/taxonomic-classification-of-planning-decisions-in-health-2eisyi4lp1.pdf

Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS

The feedback mechanism involved in all principles for artificial learning refers back to the notion of the control-circuit. This very common concept serves as a basis for the analysis and the design of feedback-control systems.

Principles of Systems

Department of Health staff wished to use systems modelling to discuss acute patient flows with groups of NHS staff. The aim was to assess the usefulness of system dynamics (SD) in a healthcare context and to elicit proposals concerning ways of improving patient experience. Since time restrictions excluded simulation modelling, a hybrid approach using stock/flow symbols from SD was created. Initial interviews and hospital site visits generated a series of stock/flow maps. A ‘Conceptual Framework’ was then created to introduce the mapping symbols and to generate a series of questions about different patient paths and what might speed or slow patient flows. These materials formed the centre of three workshops for NHS staff. The participants were able to propose ideas for improving patient flows and the elicited data was subsequently employed to create a finalized suite of maps of a general acute hospital. The maps and ideas were communicated back to the Department of Health and subsequently assisted the work of the Modernization Agency.

System dynamics mapping of acute patient flows

This paper describes the collaborative process of building a simulation model in order to understand patient waiting times in an accident and emergency department. The purpose is to explore the issues that arise when involving clients, in this case health care professionals, in the process of model building. The study background and a detailed account of the modelling process are presented. The focus of the paper is on some general themes that can be discovered running through the process. These offer some tentative insights into client involvement in system dynamics modelling, in particular its application in health care. Given this study's first promising results, further collaborative studies are encouraged.

Client involvement in simulation model building: hints and insights from a case study in a London hospital

Blending systems thinking approaches for organisational analysis: reviewing child protection in England

Relating system dynamics to the broad systems movement, the key notion is that reinforcing loops deserve no less attention than balancing loops. Three specific propositions follow. First, since reinforcing loops arise in surprising places, investigations of complex systems must consider their possible existence and potential impact. Second, because the strength of reinforcing loops can be misinferred - we include an example from the field of servomechanisms - computer simulation can be essential. Be it project management, corporate growth or inventory oscillation, simulation helps to assess consequences of reinforcing loops and options for interventions. Third, in social systems the consequences of reinforcing loops are not inevitable. Examples concerning globalization illustrate how difficult it might be to challenge such assumptions. However, system dynamics and ideas from contemporary social theory help to show that even the most complex social systems are, in principle, subject to human influence. In conclusion, by employing these ideas, by attending to reinforcing as well as balancing loops, system dynamics work can improve the understanding of social systems and illuminate our choices when attempting to steer them.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1002/sdr.396

Elke Husemann

Papers

System dynamics mapping of acute patient flows

Client involvement in simulation model building: hints and insights from a case study in a London hospital

Blending systems thinking approaches for organisational analysis: reviewing child protection in England

Steering without Circe: attending to reinforcing loops in social systems

Understanding foodborne transmission mechanisms for Norovirus: A study for the UK's Food Standards Agency