The empirical focus of this paper is to report on measured changes in health system causal understanding and strategic policy alignment within and between student groups before and after their interaction with the ReThink Health simulation environment.  Each student group was given a 50-minute pre-assessment exercise after they had done prior reading on the ReThink Health simulator but before they had a chance to interact with it online.  Each group was asked to select their initial policy preferences from a pre-defined set of 25 policy reform options supported by the simulator, to define metrics of success for their proposed policies, and finally to describe what they believed to be important causal connections between policy innovations and final metrics.  Using qualitative coding methods described by Kim and Andersen (2012), our team derived a causal map of each group’s pre-assessment strategy. 

The ReThink Health Dynamics model is a simulator developed by the Fannie E. Rippel Foundation, the California HealthCare Foundation, and scores of allies designed to support health system reform in regions across the United States. This tool is based on a system dynamics simulation model that organizes scientific data about population dynamics; social, economic, and environmental risks; disease progression; and the demand and supply of health care services. The simulation allows policy makers to adopt a place-based but wide-angle view of the entire health enterprise in a region.  Diverse groups of local health professionals, policy makers, and other stakeholders may use the simulation to explore scenarios in an effort to improve health outcomes, achieve greater equity among sub-groups, drive down the cost of care, and also boost economic productivity in the region.  The simulation model is based on a body of peer-reviewed literature from the fields of health services and health systems research as well as several prior models that have represented U.S. health system dynamics ( Milstein, Homer et al. 2009; Milstein, Homer et al. 2010; Milstein, Homer et al. 2011). The ReThink Health model itself was developed with colleagues in Pueblo County, Colorado and has since been configured for seven other regions in the United States (Hirsch, Homer et al. 2012).

After working with the policy simulator, interacting with policy experts in the field, and making a final policy presentation to a panel of experts, each team was given another 50-minute post assessment, which measured the same set of variables for each of the twelve groups.  These post-assessments were coded using the same coding rules as the pre-assessment.  The post-assessment causal map of each group’s strategy was returned to each member of each group to form part of their final course assignment, which also involved an explicit reflection on how their thinking about health reform may have changed during the overall exercise. 

This measurement exercise produced twelve matched sets of pre/post causal maps expressing each group’s prior and posterior beliefs about what policies are most effective, what metrics are most essential for measuring impact, and what are the key causal connections between strategic policy packages and proposed performance metrics.