Evaluation and learning in complex, rapidly changing health systems: China’s management of health sector reform - Xiao, Yue; Husain, Lewis; Bloom, Gerald (Globalization and Health, 2018)
Healthcare systems are increasingly recognised as complex, in which a range of non-linear and emergent behaviours occur. China’s healthcare system is no exception. The hugeness of China, and the variation in conditions in different jurisdictions present very substantial challenges to reformers, and militate against adopting one-size-fits-all policy solutions. As a consequence, approaches to change management in China have frequently emphasised the importance of sub-national experimentation, innovation, and learning. Multiple mechanisms exist within the government structure to allow and encourage flexible implementation of policies, and tailoring of reforms to context. These limit the risk of large-scale policy failures and play a role in exploring new reform directions and potentially systemically-useful practices. They have helped in managing the huge transition that China has undergone from the 1970s onwards. China has historically made use of a number of mechanisms to encourage learning from innovative and emergent policy practices. Policy evaluation is increasingly becoming a tool used to probe emergent practices and inform iterative policy making/refining. This paper examines the case of a central policy research institute whose mandate includes evaluating reforms and providing feedback to the health ministry. Evaluation approaches being used are evolving as Chinese research agencies become increasingly professionalised, and in response to the increasing complexity of reforms. The paper argues that learning from widespread innovation and experimentation is challenging, but necessary for stewardship of large, and rapidly-changing systems.

Evaluating complex interventions: A theory-driven realist-informed approach - Douthwaite, Boru; Mayne, John; McDougall, Cynthia; Paz-Ybarnegaray, Rodrigo (Evaluation, 2017)
There is a growing recognition that programs that seek to change people’s lives are intervening in complex systems, which puts a particular set of requirements on program monitoring and evaluation. Developing complexity-aware program monitoring and evaluation systems within existing organizations is difficult because they challenge traditional orthodoxy. Little has been written about the practical experience of doing so. This article describes the development of a complexity-aware evaluation approach in the CGIAR Research Program on Aquatic Agricultural Systems. We outline the design and methods used including trend lines, panel data, after action reviews, building and testing theories of change, outcome evidencing and realist synthesis. We identify and describe a set of design principles for developing complexity-aware program monitoring and evaluation. Finally, we discuss important lessons and recommendations for other programs facing similar challenges. These include developing evaluation designs that meet both learning and accountability requirements; making evaluation a part of a program’s overall approach to achieving impact; and, ensuring evaluation cumulatively builds useful theory as to how different types of program trigger change in different contexts.