Our New Tool Finds Over £100m in New Cost Savings for the NHS
Today we are launching something very exciting: a new tool that identifies over £100m in new prescribing cost savings for the NHS. The average practice can save £50,166 a year by using our tool. These are vastly bigger savings than any other current advice such as “always prescribe generically”. You can use the tool right now, online, for free, at our OpenPrescribing.net service: just look for the “experimental measures” link on any CCG or GP practice page. You can also read our preprint paper describing the extent of the NHS savings, and more detail on the technical background, here; and also our detailed FAQ on various technical matters here.
How does this new tool work?
Most doctors already know that there is wide variation in the cost of different treatments: essentially, generic drugs are cheaper than branded drugs. But even when you prescribe generically, there is still huge variation in the unit cost of medicines, due to the way the reimbursement system is structured. For example, different generic treatments can have wildly different costs; drugs which are outside something called the “Drug Tariff” can have peculiar prices; and so on.
Our tool automatically identifies the drugs with the biggest cost savings opportunities for each individual practice, or CCG, every month; and then, crucially, it helps them choose cheaper options.
This is a massive piece of computation run by our Bennett Institute at the University of Oxford, every month. Our method is entirely new, and unlike more complex prescribing advice (“always use the cheapest drug in class”) our method does not require that patients switch to completely different drugs.
We think that many of the cost-savings identified here are due to oddities at the level of national NHS negotiation, reimbursement, and regulation, and that they would be best fixed nationally. In the absence of such fixes, we are helping practices and CCGs save huge sums with our tool.
We hope you like it, and we hope you can give us feedback, good and bad: we want to know if you find the tool easy to use, and if you disagree with our methods.