Last week I attended a day-long symposium on ‘implementation science’ organised by FHI 360. I had been asked by the organisers to give a presentation, and it was only after agreeing that it occurred to me that I really had no idea what implementation science was. It turns out I was not alone – I did a quick survey of colleagues engaged in the evidence-informed policy world and discovered that the majority of them were also unfamiliar with the term (see pie chart). And even when I arrived at the conference full of experts in the field, the first couple of hours were devoted to discussions about what implementation science does and does not include.
To summarise some very in-depth discussions, it seems that there are basically two ways to understand the term.
The definitions that seem most sensible to me describe implementation science as the study of how evidence-informed interventions are put into practice (or not) in real world settings. These definitions indicate that implementation science can only be done after efficacy and effectiveness studies have demonstrated that the intervention can have a positive impact. As @bjweiner (one of the conference speakers) said, implementation science aims to discover ‘evidence-informed implementation strategies for evidence-informed interventions’.
A second category of definitions take a much broader view of implementation science. These definitions include a wide variety of additional types of research including impact evaluations, behaviour change research and process evaluations within the category of implementation science. To be honest, I found this latter category of definitions rather unhelpful – they seemed to be so broad that almost anything could be labelled implementation science. So, I am going to choose to just go with the narrower understanding of the term.
Now I have to mention here that I thoroughly enjoyed the symposium and found implementation scientists to be a really fascinating group to talk with. And so, as a little gift back to them, and in recognition of the difficulties they are having in agreeing on a common definition, I have taken the liberty of creating a little pictorial definition of implementation science for them (below). I am sure they will be delighted with it and trust it will shortly become the new international standard ;-).
So what else do you need to know about implementation science?
Well, it tends to be done in the health sector (although there are examples from other sectors) and it seems to focus on uptake by practitioners (i.e. health care providers) more than uptake by policy makers. In addition it is, almost by definition, quite ‘supply’-driven – i.e. it tends to focus on a particular evidence-informed intervention and then study how that can be implemented/scaled up. I am sure that this is often a very useful thing – however, I suspect that the dangers of supply-driven approaches that I have mentioned before will apply; in particular, there is a risk that the particular evidence-informed intervention chosen to be scaled up, may not represent the best overall use of funds in a given context. It is also worth noting that promoting and studying the uptake of one intervention may not have long-term impacts on how capable and motivated policy makers/practitioners are to take up and use research in general.
A key take home message for me was that implementation science is ALL about context. One of my favourite talks was given by @ who described a study of the scale-up of HIV prevention care in South Africa. At first the study was designed as a cluster randomised controlled trial; however, as the study progressed, the researchers realised that, for successful implementation, they would need to vary the approach to scale-up depending on the local level conditions, and thus an RCT, which would require standardised procedures across study sites, would not be practical. Luckily, the researchers (and the funders) were smart enough to recognise that a change of plan was needed and the researchers came up with a new approach which enabled them to tailor the intervention to differing contexts, and at the same time generate evidence on outcomes which was as robust as feasible. Another great talk was given by Theresa Hoke of @FHI360 who described two programmes to scale up interventions that almost completely failed (paper about one of them here). The great thing about the implementation science studies were that they were able to demonstrate clearly that the scale-up had failed and to generate important clues for why this might be the case.
One final cool thing about implementation science is how multi-disciplinary it is; at the symposium I met clinicians, epidemiologists, qualitative social scientists and – perhaps most intriguingly – organisational psychologists. I was particularly interested in the latter because I think it would be really great if we could get some of these types involved in evaluating/investigating ‘demand-side’ evidence-informed policy work funded by organisations, including DFID, (the department formerly known as-) AusAID and AHSPR. These programmes are really all about driving organisational change, and it would be very useful to get an expert’s view on what approaches (if any!) can be taken by outside actors to catalyse and support this.
Anyway, sorry for such a long post but as you can tell I am really excited about my new discovery of implementation science! If you are too, I would strongly recommend checking out the (fully open access) Implementation Science Journal. I found the ‘most viewed’ articles a good place to start. You will also soon be able to check out the presentations from the symposium (including my talk in which I call for more unity between ‘evidence geeks’ like me and implementation scientists) here.