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.

Community psychologists have a long history of interest in understanding social systems and how to bring about enduring positive change in these systems. However, the methods that community psychologists use to anticipate and evaluate the changes that result from system change efforts are less well developed. In the current paper, we introduce readers to system dynamics modeling, an action research approach to studying complex systems and the consequences of system change. We illustrate this approach by describing a system dynamics model of educational reform. We provide readers with an introduction to system dynamics modeling, as well as describe the strengths and limitations of the approach for application to community psychology.

Proposals to improve the US health system are commonly supported by models that have only a few variables and overlook certain processes that may delay, dilute, or defeat intervention effects. We use an evidence-based dynamic simulation model with a broad national scope to analyze 5 policy proposals. Our results suggest that expanding insurance coverage and improving health care quality would likely improve health status but would also raise costs and worsen health inequity, whereas a strategy that also strengthens primary care capacity and emphasizes health protection would improve health status, reduce inequities, and lower costs. A software interface allows diverse stakeholders to interact with the model through a policy simulation game called HealthBound. (Am J Public Health. 2010;100:811-819. doi:10.2105100:811-819. doi:10. /AJPH.2009 The multiple shortcomings of the US health system are well known. US health care spending per capita is the highest in the world, but Americans have comparatively high rates of morbidity and premature mortality, 1 along with persistent disparities among subgroups. People with lower socioeconomic status, for example, are much more likely to develop disease and injury and to become disabled or die prematurely as a result, in part because they face greater health threats and are also less likely to have access to high-quality health care. 2,3Various theories have been offered to explain why the US health system performs so poorly and is so costly.4,5 Many point to the lack of health insurance for millions as the system's chief problem. 6 Some criticize the medical industry and the public at large for overemphasizing disease detection and treatment while missing opportunities to reduce preventable risk and protect people's health. 7,8 Others blame perverse incentives and community norms that encourage physician entrepreneurship and profit making over collaboration, coordination, or conservative practice. 9, 10Still others say that there are too few primary care providers or that the providers we do have are underpaid and unable to offer the highest-quality care. 11,12 And some fault private insurers, who pass along high overhead costs to consumers, are unwilling to reimburse adequately for preventive care, and offer a confusing array of coverage plans, creating a substantial administrative burden for providers. 13Likewise, reform proposals vary widely in their goals and policy levers. One leading proposal calls for wider health insurance coverage and better quality of care through computerization and payment incentives for providers. Supporters claim that these 2 changes will improve people's health and reduce health care costs, effectively remaking the health delivery system. 14 Other proposals run the gamut, from outlining 15 ways to cut costs 15 to focusing on relatively inexpensive population-based programs to increase physical activity, improve nutrition, and prevent tobacco use. 16Such proposals are usually justified by calculating their costs and benefits over time. However...

Chronic illness is a large and growing problem throughout the world. Experts agree that the U.S. health care system is poorly organized to care for chronic illnesses and, as a result, is wasteful and unresponsive to the needs of patients. This article describes a program to improve chronic care in a county of Washington State, and how system dynamics models focusing on diabetes and heart failure supported the planning of that program. The models project the program's costs and benefits over 20 years and have given its leadership the ability to do resource planning, set realistic expectations, determine critical success factors, and evaluate the differential impacts on affected parties. Relying upon model projections, the leadership is seeking ways to address concerns about financial "winners" and "losers" so that all parties are willing to participate in and support the program.

Planning programs for the prevention and treatment of cardiovascular disease (CVD) is a challenge to every community that wants to make the best use of its limited resources. Selecting programs that provide the greatest impact is difficult because of the complex set of causal pathways and delays that link risk factors to CVD. We describe a system dynamics simulation model developed for a county health department that incorporates and tracks the effects of those risk factors over time on both first-time and recurrent events. We also describe how the model was used to evaluate the potential impacts of various intervention strategies for reducing the county's CVD burden and present the results of those policy tests.