A Health Technology Assessment perspective on the significance of real-world evidence 18 Jun 2018

Today’s article is an interview with Dr Amr Makady. He is a pharmacist by training with an interest in pharmaceutical economics. Currently, he works as a pharmacoeconomic assessor and policy advisor at the Dutch National Health Care Institute (ZIN), which is the national Health Technology Assessment (HTA) agency. Recently, Dr Amr defended his PhD thesis at Utrecht University, focusing on the use of real-world evidence (RWE) in HTA practice. As a member of ROADMAP’s Expert Advisory Group, he will give us an insight into the significance of RWE from an HTA perspective.

Why are you doing research on real-world evidence?

My initial work on RWE started with the IMI Get Real project. However, already before that, the use of RWE was a question that was very important for the HTA organization where I work. They still see quite a discrepancy between the kind of information they would like to have and the information they receive, especially for societal decisions which need to be assessed on a lifetime horizon. I believe that is where the initial momentum came to step into this research question.

Personally, I also found it interesting because I come from a pharmacy background and saw what medicines do within a hospital setting and within the personal setting of the home. Also, I had a feeling that what happens in real life may understandably be different to what happens in a study. This is where my personal motivation came from – the idea that looking into what insights RWE and real-world data (RWD) can provide to address this gap in knowledge.

With those gaps in mind, what do you think could be the potential benefit of using RWE for decision-making?

It delivers pieces of the puzzle, which we conventionally cannot get from, for example, randomized clinical trials (RCTs). This kind of insight is very much needed. Looking from a scientific point of view, RCTs can deliver very accurate, precise information within a very idealised setting.

However, it is almost a no-brainer that other sources of evidence are also needed if one wants to know how medicines work among very heterogeneous patient populations with much less strict follow-up and while keeping in mind that the healthcare system itself is a learning process (it’s not static or fixed but quite dynamic).

I’m sure that this kind of RWE can give insights that RCTs are not designed to provide, hopefully to answer the kind of policy questions that we face.

Within the IMI Get Real project you worked on a review of definitions of RWD. What would you consider to be the next step in developing a common understanding?

We do highlight several definitions that have been formed, including the one developed by Get Real. I think these kinds of definitions provide a good starting point for consensus. Nevertheless, it’s also a question of ‘should we be dedicating too much effort into harmonising the definition or the understanding of RWE use?’. Some people think we should move away from the term RWD or RWE. We could just say ‘anything not collected by an RCT’ and then directly address the different kinds of evidence sources, methodologies and interpretations for decision making. Personally, I still think it’s important that we try to refer to common definitions, just to avoid confusion and level the discussion, even if we don’t stand completely behind the definition.

What would you consider the potential risks of appraising RWE in decision-making?

I think the main risk now is that we have little experience in how different methods of analysis and interpretations of RWE will translate into decisions several years down the line.

I do not think it is a danger though. From a different perspective, one can also argue the fact that we are using RCTs to make the same kinds of extrapolations, which means that we are not using the optimal evidence for the question at hand. To a degree, it is a risk that we might analyse this RWE with sub-optimal methods or interpret them incorrectly. Nevertheless, it should also not mean that we do not dare to do it, because in the long run the need for insights from these kinds of sources is growing.

What particular strengths do you see in ROADMAP’s activities?

I believe one very positive aspect is that we have all these stakeholders together, engaged in an open dialogue. It is very nice to see how members of the European Federation of Pharmaceutical Industries and Associations (EFPIA) and public organisations are brainstorming about how to bring this forward. It’s a very comfortable and constructive environment to look into common challenges together.

I think that the project is also delivering some interesting products like the data cube (a way of visualising the European landscape in terms of data availability for AD research).

It is very nice to see the workflow of the EXAG committee, where we’re trying to seek harmonisation on what regulatory and HTA needs may be, and link those back to current development pipelines in Alzheimer’s disease drugs. That sort of dialogue, streamlining, and harmonising as well as bringing this back to EFPIA partners is something unique.

With regard to the long-term deliverables of the project and what will come out of the modelling exercises and health economics exercises, I believe they will be very cutting edge, especially for Alzheimer’s disease.

One last positive point I would like to highlight is that the ROADMAP project is actually moving beyond the clinical effectiveness aspect and the use of RWE for that. ROADMAP looks at cost-effectiveness, which is a sensitive topic for different HTA agencies, and seeing the project daring to go there is very refreshing.

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