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Information Mastery 2. Approaches, tools, techniques and skills. Information Mastery requires two different approaches to managing information: Foraging - a method of being alerted to new information when it is published Hunting - a method of finding information when it is needed
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Information Mastery 2 Approaches, tools, techniques and skills
Information Mastery requires two different approaches to managing information: • Foraging - a method of being alerted to new information when it is published • Hunting - a method of finding information when it is needed • Without both: • clinicians won’t know when new important information becomes available • clinicians won’t be able to find it easily, even when they remember reading it
Usefulness = Relevance x ValidityWork What are the criteria used when looking for the best answer or important evidence? Slawson DC and Shaughnessy AF. J Am Board Fam Pract 1999; 12: 444-9
So, filtering for relevance • Feasible (intervention) • Outcomes (patient-orientated) • Common (condition) • Change in practice required
Validity - A hierarchy of evidence • (Well conducted MA of several, similar, large, well designed RCTs) • Large well designed RCT • Meta analysis of smaller RCTs • Case control and cohort studies • (Case reports and case series) • Consensus from expert panels • I think
Some terms used • Relative risk: • “What is the chance of the endpoint occurring in the treatment group compared with the control group?” • Stays constant in different populations • Relative risk reduction: • “By how much did treatment reduce the chance of the endpoint occurring in the treatment group compared with the control group?” • Stays constant in different populations • Absolute risk reduction: • “How many fewer patients experienced the endpoint in the treatment group than in the control group?” • Decreases the lower the baseline risk • Number needed to treat: • “How many people, on average, need to be treated for one to gain a benefit?” • Increases the lower the baseline risk
Filtering for validity • P values and confidence intervals tell us if the result was likely to have occurred by chance • Confidence intervals tells us the range in which the “true” result probably lies • BUT we still need to determine the clinical significance of the result even if statistically significant • Look for the POOs • Power - watch out for short term studies, and studies / subgroups with few people • Watch out for the comparator • Beware of publication bias • Look to see if the allocation was concealed