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. Copyright © 2004 John Wiley & Sons, Ltd.

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.

Chronic illness is the largest cause of death and source of health care costs in developed countries and a growing problem in developing countries. Here we build on past work in system dynamics and present a generic model of chronic illness, its treatment and prevention, applied to the U.S. population. The model explains the rising prevalence of illness and responses to it, including the treatment of complications and management activities designed to reduce complications. We show how progress in treatment and disease management has slowed since 1980 in the U.S., largely due to competition between health care payers and providers, resulting in price inflation and an unstable climate for health care investments. We demonstrate the impact of moving “upstream” by managing known risk factors to prevent illness onset, and moving even further upstream by addressing behaviors and living conditions linked to the initial development of these risk factors. Copyright © 2007 John Wiley & Sons, Ltd.

The Prevention Impacts Simulation Model (PRISM) projects the multiyear impacts of 22 different interventions aimed at reducing risk of cardiovascular disease. We grouped these into 4 categories: clinical, behavioral support, health promotion and access, and taxes and regulation. We simulated impacts for the United States overall and also for a less-advantaged county with a higher death rate. Of the 4 categories of intervention, taxes and regulation reduce costs the most in the short term (through 2020) and long term (through 2040) and reduce deaths the most in the long term; they are second to clinical interventions in reducing deaths in the short term. All 4 categories combined were required to bring costs and deaths in the less-advantaged county down to the national level.