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Improving health care involves many actors, often working in complex adaptive systems. Interventions tend to be multi-factorial, implementation activities diverse, and contexts dynamic and complicated. This makes improvement initiatives challenging to describe and evaluate as matching evaluation and program designs can be difficult, requiring collaboration, trust and transparency. Collaboration is required to address important epidemiological principles of bias and confounding. If this does not take place, results may lack credibility because the association between interventions implemented and outcomes achieved is obscure and attribution uncertain. Moreover, lack of clarity about what was implemented, how it was implemented, and the context in which it was implemented often lead to disappointment or outright failure of spread and scale-up efforts. The input of skilled evaluators into the design and conduct of improvement initiatives can be helpful in mitigating these potential problems. While evaluation must be rigorous, if it is too rigid necessary adaptation and learning may be compromised. This article provides a framework and guidance on how improvers and evaluators can work together to design, implement and learn about improvement interventions more effectively.

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Just as in other modern industries, the term ‘innovation’ in healthcare has become associated with new developments in the field that allow for improvements in solving problems, in this instance, healthcare problems. This paper seeks to clarify what the term truly means. To address this issue, we first define innovation as a general term, then define what innovation means in the context of the healthcare industry. To better understand what may be considered ‘innovative’ in healthcare, we suggest criteria for innovation and identify potential challenges to newly introduced innovations in the field.