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Despite increased prominence and funding of global health initiatives, efforts to scale up health services in developing countries are falling short of the expectations of the Millennium Development Goals. Arguing that the dominant assumptions for scaling up are inadequate, we propose that interpreting change in health systems through the lens of complex adaptive systems (CAS) provides better models of pathways for scaling up. Based on an understanding of CAS behaviours, we describe how phenomena such as path dependence, feedback loops, scale-free networks, emergent behaviour and phase transitions can uncover relevant lessons for the design and implementation of health policy and programmes in the context of scaling up health services. The implications include paying more attention to local context, incentives and institutions, as well as anticipating certain types of unintended consequences that can undermine scaling up efforts, and developing and implementing programmes that engage key actors through transparent use of data for ongoing problem-solving and adaptation. We propose that future efforts to scale up should adapt and apply the models and methodologies which have been used in other fields that study CAS, yet are underused in public health. This can help policy makers, planners, implementers and researchers to explore different and innovative approaches for reaching populations in need with effective, equitable and efficient health services. The old assumptions have led to disappointed expectations about how to scale up health services, and offer little insight on how to scale up effective interventions in the future. The alternative perspectives offered by CAS may better reflect the complex and changing nature of health systems, and create new opportunities for understanding and scaling up health services.

Understanding pathways for scaling up health services through the lens of complex adaptive systems