The price of technological innovations in health care has once again been brought into focus. Orkambi, a new pharmaceutical treatment for a specific type of cystic fibrosis has not been approved for availability on the NHS because its price is deemed too high.
Meanwhile, there is panic at the relentless rise of fatal antibiotic-resistant infections in hospitals for which no treatment is available.
Pharmaceutical companies are reticent to invest in such research, because any drug would be reserved as a treatment of last resort. The price would therefore have to be very high for it to make commercial sense, potentially leading to the sort of backlash seen with Orkambi.
We are at an impasse that has been coming for the last 30 years at least. And it is difficult to envision a way out.
Having spent over 15 years working on pharmaceutical pricing issues, it is clear to me that there is no such thing as a fair or socially just price for pharmaceutical products or other medical innovations. The costs and risks of undertaking drug discovery and development need to be offset by decent commercial returns. But such returns can be increasingly difficult to come by in healthcare systems where budgets are strained to breaking point.
Some companies, such as Astrazeneca, seem to be putting their faith in data. Outcomes-based pricing – in other words a pricing system where healthcare providers only pay for a drug for those patients where it is shown to be effective – has been talked about for over 20 years. But not much advance has been made beyond the odd example here and there, although the current fashion for big data analytics has given the idea a fresh impetus.
The reality is that outcomes-based prices, while potentially providing a modicum of respite, is unlikely to be a magic bullet.
First of all, the most severe (and most expensive) diseases are treated with multiple therapies. Trying to disentangle which part of the therapeutic cocktail is having which clinical effect will be challenging, to put it mildly.
Secondly, outcomes-based pricing will result in less revenue per treatment for pharmaceutical companies. This means that they will need to increase the price of successful treatments in order to maintain their returns. True, they can argue that the higher price is fair because it is seeing clear success – and, potentially, a decrease in related healthcare costs. This may work in some disease areas, but is unlikely to be sufficient in many others.
Neither does it resolve the fundamental issue facing healthcare payers and providers: their budgets cannot accommodate the absolute costs of medical innovations, and not just drugs.
Turning to data, artificial intelligence, and data analytics as a “solution” to this issue risks trying to apply a technological fix to what is fundamentally a political problem. Political because it relates to how we choose to fund and provide health care. Political because responding to the backlash from drugs perceived to be too expensive is about managing public opinion in an area of policy that is emotionally highly charged.
The easy way out is to turn on pharmaceutical companies as “profiteering from people’s illnesses”.
This may be politically convenient for some, but does not reflect reality. More than 20 years ago, I was constructing risk models which showed that large, integrated pharmaceutical companies were no longer going to be in a position to carry the financial risk associated with drug discovery and development. And so it has proven to be. This is why so many new therapies now originate in startup companies that can tap the financial markets, thereby spreading risk. This has worked only partially, since the price that large pharmaceutical companies are now paying to acquire smaller ones with promising drugs in development has become astronomical.
The way out of this increasing challenge is not obvious. It’s a complex Rubik’s cube that seems almost insoluble.
Much thinking has gone into these questions for many years – with precious little to show for it. And the old pharmaceutical company formula of generating ever-more data and combining that with sustained lobbying efforts will not be effective for much longer.
Resolving this challenge is important for all of us, as we will all need treatment for something or other at some point in our lives.
The solutions, if there are any, will not come simply from embracing the latest new technological fad – the default position for all companies that are technologically minded. Instead, it will require some fundamental reimagining of how we think about costs, benefits, the future of health research and healthcare systems, and their funding and provision models.
And, ultimately, we need to accept that the issues are political, not technological or technocratic. Until we start looking at them through that lens, and hopefully allow some ways forward to emerge, then we should all be concerned about what will happen to us when we are diagnosed with a severe illness.