And there are lots of ways to do ‘synthesis’ of evidence within a systematic review. We’ve gone on – at length – about meta-analysis and described qualitative synthesis with meta-ethnography, but in a new paper in the Archives we see how a narrative combination of quantitative research studies with a qualitative framework to understand them can allow us to see where the trees lie in the wood [insert alternative forestry based metaphor if preferred].
This group of authors decided to examine the safety netting tools after discharge from the paediatric emergency / urgent care department.
Taking a FAST approach, we can show that they have
F – found a lot of studies –
(As with many reviews where the ‘thing of interest’ is not a pharmacologically codable intervention, a very broad sweep with connected, spiderlike acquisition of information is most effective.)
(While the risk of bias of randomised trials is well worked out – we have a whole series of posts on these elements and can be acronymed as RAMbo – there are greater difficulties in other areas, like diagnosis and prognosis. This paper used a version of a generic observational studies risk of bias score to given an overview of how reliable the answers might be.)
(This is the really interesting section. They visually grid the risk of bias against study number and ‘direction’ of answer for categories of particular question / sub-question.
What you can’t see is the ‘weight’ of each study – n=16 will be the same sized circle as n=673 – but this is meant to be impressionistic. It’s a feel for where it sits, rather than conclusive proof of anything.)
(And they do a nice textual job actually explaining it.)
(What’s really clear is that lots of people have fiddled with this concept in lots of different ways and not fundamentally bashed out a strong basis for any approach, let alone any specific approach. Many things can be said and a citation found to underpin those statements. Whatever the truth is – if there is one – it’s not clear yet.)
Such a paper really helps us see where what we might suggest is founded on good intention not always good solid evidence.