You probably don’t want to hear your doctor proclaiming “I’m so indie, I was prescribing that *way* before it was cool.” Or maybe you do?
If you’re a hipster and you really need to know when a particular band stops being underground and teeters on the edge of being mainstream so you can only like it in the cool ironic way, then you would want to know how quickly it passes from the early adopters into the hands of the mainstream.
It’s the same for prescribed drugs in primary care – we want to know how long it takes for new prescription drugs to become part of mainstream practice.
tl;dr – we had a go at working out how long it takes for prescription drugs to be fully adopted in Australia, and published it here.
We already know quite a lot about how an individual prescriber makes a decision to change his or her behaviour for a new drug on the Pharmaceutical Benefits Scheme (PBS). Sometimes it has something to do with the evidence being produced in clinical trials and aggregated in systematic reviews. But often it is all about what the prescriber’s colleagues are saying and the opinions of influential people and companies.
It’s evidence of social contagion. And it’s been shown to be important for innovations in healthcare.
What we haven’t seen are good models for describing (or even better, predicting) the rate of adoption within a large population the size of a country. So in a new paper in BMC Health Services Research I wrote about a well-studied model and its application to prescription volumes in Australian general practice. Together with some of my more senior colleagues, I applied a simple model to over a hundred drugs that were introduced to Australia since ‘96.
It turns out that, in Australia, your average sort of drug takes over 8 years to reach a steady level of prescriptions.
The model is arguably too simple. It assumes an initial external ‘push’, which falls away as social contagion grows. The problem is that these external pushes don’t all happen at once when a new drug is released onto the PBS but more likely exist as a series of perturbations which correspond to new evidence, new marketing efforts, other drugs, and changes and restrictions. So while the model produces some very accurate curves that correspond to the adoption we have seen historically, it wouldn’t be particularly good at predicting adoption based on some early information.
For that, I think we need to create a strong link between the decision-making of individuals and the structure of the network through which diffusion of information and social contagion flows. I’ve started something like this already. I think we still have quite a way to go before we can work out why some drugs take over a decade and some are adopted within a couple of years.