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In his recent book Ignorance: how it drives science, Stewart Firestein states, ‘Knowledge is a big subject. Ignorance is bigger.’1 Firestein's book does not explore the ways of knowledge, but the mechanisms by which scientists work to develop and answer questions…which invariably lead to more questions. ‘Not knowing’ is a key driver of research and of quality improvement (QI). While research seeks to create new generalisable knowledge, QI often focuses on improving a specific aspect of healthcare delivery that is not consistently or appropriately implemented in a particular setting. A clinical researcher often asks questions such as, ‘Is X a risk factor for Y?’ or ‘Is treatment A more effective than treatment B?’ Those engaged in QI, by contrast, offer questions such as, ‘Why does routine care delivery fall short of standards we know we can achieve?’ or ‘How can we close this gap between what we know can be achieved and what occurs in practice?’
There are multiple ways to ask questions, answer questions and build knowledge. In healthcare research, specific and well-described methods exist for the design, execution and analysis of defined questions. Questions regarding implementation in a specific setting, integrating evidence into practice, or improving the efficiency of local systems are often best answered using methods that differ from traditional methods of clinical research (eg, controlled clinical trials). While a number of formal methods exist for implementing QI in practice—the model for improvement, Lean or Six Sigma—all advocate the use of small tests of change. Small tests of change enable one to learn how a particular intervention works in a particular setting. The goal of these methods is not to test a hypothesis but rather to gain insight into the workings of a system and improve that system. The most common approach to developing and testing …
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