The role of health economics in cancer outcomes research

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Published: 6 Jan 2015
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Prof Bengt Jönsson, Stockholm School of Economics, Stockholm, Sweden

Dr Jonsson speaks to ecancer at the 2nd EurocanPlatform Translational Research Course, discussing his presentation into the economic aspects of the final stage in translational cancer research: outcomes research.

He notes the variations between and even within countries and the importance of ascertaining ‘value for money’ in terms of clinical drug use.

He also explores what changes this work could make to clinical practise, what the next steps are and what obstacles pose problems.

Learn more about the EurocanPlatform project here

 

I’ve been talking about outcomes research, which you can see is the final stage in translational medicine; it’s actually when you are looking at how therapies are used in clinical practice. Since I am an economist I have focussed on the economic aspects of this. The observation in outcome research is, of course, that first of all there are great variations between countries and also within countries in how, for example, medicines are used in clinical practice. Secondly, also it’s obviously an observation that they are not always used in clinical practice in the same way as they’re used in clinical trials and not with the same results as in clinical trials either. So this is, of course, very important because new medicine only produces value for patients if they are given to the right patients at the right time. So that’s the basics of what I have been talking about. The reason I think this is becoming so… to have so much interest and importance at the moment is also that new therapies when they come in are, first of all, they’re usually very costly and secondly also we don’t know when they come in to clinic exactly what their value are. So what we have to do is as quickly as possible try to find out for which patients they actually produce value for money, as we say, because we have seen they are costly, also we have to balance what we are paying towards the value. So that was in essence what I have been talking about.

One key message which relates also to the specific course which you have here which is about translational medicine, it is about personalised medicine also, is that cancer therapy is changing very much. We are defining predictors, more and more precise predictors for which patients can actually have benefit from the new treatment. One thing is how do we actually use this information in the healthcare system in order to make more better use of the resources. This is where we are in the big transformation is also how do we make sure that we have all those data for the patients when they are having a decision about which therapy they could benefit from. Then, also, how are we following up in clinical practice which patients are actually benefitting from this therapy because it is not so easy that we just make a clinical trial and we say patient benefits on this drug. In clinical practice we usually use a combination of drugs and drugs in sequences and so on and we have to look at what the outcome is in clinical practice.

Could this work make a significant change in clinical practice?

As we are doing studies in clinical practice, I think we have made the observation before that even if we make the right decision, the right guidelines and everything, we really have to study that this knowledge which we have about it is implemented in clinical practice. We know that in clinical practice so many things happen and we know that it’s not only the new drug which is important, it’s also about the healthcare system – are they making the right diagnosis? Are they doing the right follow-up? Do they do other things around it, which is very important for the patient? Then, of course, very important also from an economic point of view is that do we really allocate our resources? Because all healthcare systems would like to improve quality of cancer care but we also have to tell them, well what should we do? What are the policy instruments we need to develop to do this?

What are the next steps?

There are two major types of studies. The first study is more descriptive: we need to have the information about how we are actually using resources for cancer, how we are spending our money, which patients are treated etc. So we have to… that is one thing because we have actually, surprise, surprise, we know quite a lot of cancer. We know about cancer incidence, we know about cancer mortality etc., but we need to know much more about, say, the resources used for cancer care and the quality of the cancer care we are providing. But that’s the one type; the other type is that we have to build and that’s the next step. We have to build up a system for creating evidence about the new therapies, new diagnostics, new therapies. We also need to do this on a European level because we are 500 million people in Europe and a lot of cancers are quite limited, in small populations etc., so by collaborating over the countries we can actually get this information and this knowledge much faster because patients are similar in different cancers and we can use those data. So this is a way of building up the relevant database for scientific study about outcome.

What are the main obstacles of this work?

If I would say a main obstacle is that this is we need data and we need real data about individual patients and how individual patients are treated. There are several aspects of this; this has to do very much with the development of e-health and information systems because it’s expensive to collect these data, do it in a high quality way. So we really need to be efficient in the way how we are developing this. And then, of course, also it’s that sharing of data is also something because now patients are interested in data, not only the researchers and not only the industry and the pharmaceutical industry which is developing new drugs. The healthcare system is also needing this type of data. So there are issues in the way of developing this type of database, this individual patient data, personalised medicine. We have to develop it in a way while protecting the integrity and the autonomy, of course, of the patient also, even if it is in the interests of patients also to have this data.

Then the major, or the third obstacle, if we are just talking about problems, because I think still there are more opportunities than there are problems, but of course the problem is to really implement this knowledge into the decision making because in all healthcare systems they are not always functional and they are having financing mechanisms and incentives and various. It’s well know that it is one way to decide about health policies but one is a matter of more difficult to implement these policies and in particular when it comes to technology like personal cancer medicine and so on which basically transforms the whole healthcare system. So maybe even the old classification of cancers according to organs, different disciplines of medicine come in and so on. So there are a lot of issues involved in implementing this knowledge into clinical practice but if we are not implementing it in the correct way there will be no benefit for patients. Because it’s only when the right treatment meets the right patients, then is when we are creating value for our healthcare resources.