Using Complexity Theory to Improve Public Health Partnerships
Last modified: October 9, 2007
In public health, researchers and practitioners are beginning to use collaborative partnerships to address complex population health problems. However, collaborative partnerships that are based on traditional public health planning methods have varied in their effectiveness. New complexity-based methods provide a more effective alternative. Based on complexity science concepts of complex adaptive systems, self-organization, parts and wholes, simple rules, and emergent coevolution, new complex adaptive planning and evaluation (CAPE) methods were developed and tested on a statewide healthcare disparities task force in Minnesota, with immediate results on multiple levels. This presentation will provide an overview of the CAPE model, its use with the Minnesota Healthcare Disparities Task Force, and evidence of its relative effectiveness compared to traditional public health planning and evaluation models. The presentation will also compare complexity-based and traditional public health planning approaches in five critical areas associated with effective partnerships: the diversity of the partnership's members, the framing of the public health solution and theory of change, the partnership's organizational structure, the quality of member dynamics and interactions, and the use of developmental evaluation methods. Practical CAPE methods and tools will also be shared.