Dunja Dreesens

90 practice (e.g. how services are organised to deliver care), this may be better achieved by drawing on qualitative or mixed-method evaluative research rather than RCTs. If the aim is to assess the effectiveness of a specific treatment or approach, evidence from RCTs or high-quality prospective cohort studies would usually be the primary source of knowledge, with qualitative or mixed-method studies serving to help understand the local context of implementation. It is important to note, however, that for most guideline developers, the primary purpose remains that of supporting decision making in the clinical encounter. This leads us to the next fundamental aspect of guideline development. The problemof induction How do different types of knowledge in guidelines development help to make clinical decisions? Some basic concepts from the philosophy of science may help to understand the problem. Inference, the problem of induction and evasions In logic, to infer means to conclude from evidence using reasoning (218). In everyday healthcare practice, care professionals and patients reason to reach conclusions about what has happened, to make predictions about what will happen and to decide what to do next. Because of uncertainty in medicine, we usually deal with a specific type of inference, called induction , where the conclusions of our reasoning are not always right even when based on true premises. In philosophy, there is a concern whether this is actually possible, called the problem of induction (218), as introduced by Hume in 1739 (219). At its simplest, this means we cannot predict the future with certainty. Although this seems reasonable, we are in fact able to predict the future quite accurately on many occasions in clinical practice. How is this possible? Philosopher of science Ian Hacking (218) argues that we never solve the problem of induction, but only evade it by applying different kinds of reasoning to reduce uncertainty and increase our chance of reaching the best possible outcome. The dominance of frequency-based reasoning The evasion most dominantly used in guideline development is frequency-type reasoning in the form of systematic reviews, RCTs and observational studies (8). This evades the problem of induction by recognising that ‘although we can’t predict the future for the individual case, we can be “usually” right (e.g. 95% of the time)’ (218) as long as events or cases are frequent enough. Frequency-based reasoning relies on basic assumptions that have some drawbacks. First, this line of reasoning assumes that reality is dice like and that we – e.g. scientists, guideline developers and healthcare professionals – are rolling the same dice (see Text box 4). Frequency-type reasoning presupposes adequate framing and defining of what is similar and what is not, which is always based on judgement and choice. Chapter 5