Coordinated Tension: The “Secret Sauce” to Enable Decision-Making in a Global Health Complex Adaptive System
Many resources and approaches have been used to improve health in a global context; however, change at scale, especially in the hardest to reach areas, is a challenge. The Salud Mesoamerica Initiative (SMI) was created to test a new way to intervene in this space. After 5 years of implementation, SMI has demonstrated positive results through their results-based financing plus model.
The distinctions found in complex adaptive systems help to describe the organizational, social, and technological solutions associated with scaling-up global health innovations, particularly the mechanisms of exploration, exploitation, and coordination which are inherent in the learning process. In a complex and dynamic setting such as improving health outcomes for women and children, the type of output to be produced is a function of the actions at all levels of the system to attain a change in health coverage or status.
We examined the SMI experience through a complexity science lens to describe the mechanisms at work within the program to detect elements which could be potentially adapted and replicated in other contexts. We find that SMI created a learning system within the global health complex adaptive system to achieve results which relied on three main elements: (1) system of rules (exploitation); (2) system of actors and variation (exploration); and (3) coordinated system of learning. To manage the tension between exploitation and exploration systems, the learning system intentionally created a feedback mechanism that required specific data, the right actors, enabling factors, and adaptive coordination abilities. Based on this experience, we find that to manage complex adaptive systems and balance the tension between exploitation and exploration, it is necessary to create coordinated learning systems with four critical objectives: creating a learning environment, experimentation, translation, and brokering. This chapter describes how these elements were applied in SMI, lessons learned, and remaining questions for scale-up, sustainability, and future replication.
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