Big Data

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Paving the way in social license research: an interview with Ghislaine van Thiel and Shona Kalkman

Paving the way in social license research: an interview with Ghislaine van Thiel and Shona Kalkman

Ghislaine van Thiel works as an ethicist at the Julius Center, UMC Utrecht together with Shona Kalkman, assistant professor at the Julius Center, UMC Utrecht. The UMC Utrecht is the academic lead of Work Package 7, which involves ethical, legal and governance issues in BigData@Heart. 


One of the topics you are doing research on in BigData@Heart is social license. Could you explain what a social license is?

Ghislaine: The idea of a social license is actually quite old. It was used for example in the mining and the oil industry where people became aware that they needed some kind of confirmation or support from societies to be able to operate their businesses. The concept of social license has been reintroduced a few years ago in the context of data health research. The idea is that if you want to do big data research, you may need to deviate from traditional systems of getting consent from people by individually speaking to every person and asking if they would be willing to share their data.

The idea is that, on the one hand this would not be feasible in big data research, and on the other hand, that if we would deviate from the older system of informed consent, it is not always the case that this is also supported by the people whose data we are using. This was actually experienced quite intensely in a big data health research in the UK ( where they decided to use primary care data under an opt out system. Instead of asking each patient: 'are we allowed to use your data?', the proposal was to use the data of all patients, and to offer an opt-out.  When this became public, both professionals and patients boycotted the plan and this really had an impact on data projects. The idea of a social license was introduced in response to problems with informed consent. The idea is that a social license can help povercome challenges with informed consent for data sharing in health research.

How can you obtain a social license for research?

Shona: This is one of the things we are trying to explore in BigData@Heart. If you think of a social license as a mandate given by society to researchers it comes with expectations. You can get a mandate based on the expectation that data is treated in a responsible way. So we want to understand the conditions for data sharing. We already did some work on the more high level ethical guidelines, norms and principles, but we also want to understand more bottom up how citizens or patients view responsible use of data. Transparency is very important in this. People might be quite willing to share their data, but only as long as they know what is being done with their data. The same is true for topics like accountability and responsibility. So, it is important to operationalize these conditions. We are now exploring how we can transfer the knowledge about these conditions into a ‘performance framework’ as a tool for researchers and institutions to show they are trustworthy.

Ghislaine: Parallel to that, we are also working on a system for patient and public involvement (PPI). The idea is that obtaining a social license is not only a matter of scientists or researchers coming up with ideas of how this should be done, but instead real and meaningful involvement of patients and the public should also be an aspect of obtaining a social license. On a longer term, we also plan to test different modalities of PPI in health data research.

So patients are really an important stakeholder group in the concept of social license?

Ghislaine: Yes. We not only look at what we currently know from empirical research about what patients and the public think is important, but we believe that for a sustainable social license, you need ongoing and meaningful PPI in research governance. It is not only important, it is really necessary.

Shona: And I would like to add that we are thinking of a type of governance that is adaptable and flexible, because people are aware things are changing, so you need a flexible and dynamic system.

Ghislaine: And involve stakeholders and also make room for further innovation. It is hard to adapt new innovations to fixed systems. We are working in a world with different researchers and different groups of people from different geographical areas, so if everybody has their own fixed system, we would not be able to share data or match governance systems, because these are too varied.

The ultimate goal of a social license in doing research is the freedom to research. Could you elaborate a bit more on this?

Ghislaine: I think the word license includes the word mandate. You are mandated by society to have a certain degree of freedom to do your research and we are trying to describe the degree of freedom. We think that, in order to really maximize the benefits of big data research, the research community together with patients and the public should make an effort to maximize the freedom of science, while at the same time conserving the trust of society. We should not only emphasize that this is important, but also be very serious about obtaining this mandate in a responsible way. And I think a mandate is a very good word for the term social license. You have a license to operate in a certain way and the license to operate should be established in order to define the playing ground of society and scientists.

Shona: And I also think that there are different conceptions of freedom here. Some researchers might find the ‘old system’ of going to the patient for using data, relocate them, contact them etc. quite restrictive. But at the same time, there are no real obligations yet to do PPI. I like to use the analogy of a playing field, where you have the pillars of your fence defining the freedom you have, but within a confined area.

Ghislaine: The consent structure can indeed be very restrictive for research, because it could be very intense and burdensome for researchers. But at the same time, it does not pay any attention to what you are actually doing with the data. There is no going back to patients or society and accountability for what is actually done with the data. We would carefully like to propose an alternative standard of informed consent that matches better with performance criteria, with more transparency and more responsibility in the use of data. That is where the concept of a social license can be used. In this case people should not always have to be asked if their data can be used, but science is accountable for the use of data for the public good, and responsible for the protection of the rights and the wellbeing of the people whose data are used.

I understand it is really important to change the idea of how big data research should be done and the involvement of patients and the public in this. Related to that: what could be the potential factors of success or failure in trying to achieve a social license?

Ghislaine: We have to realize that a social license is not unconditional and that there are, for example, cultural differences influencing the social license. Some countries find it completely normal that their citizens’ data, tissue and DNA is collected in a biobank, whereas other countries are much more reluctant to do so. Also, the need for flexibility is related to these cultural issues. What we have learned from the literature so far is that we should not think there is an unconditional trust in science that would allow us to just change the rules and expect society to go along with that. Instead, I think that the success factor in achieving a social license should come from a pro-active attitude, coming up with proposals for changing the informed consent culture.

Shona: I think a challenge for operationalizing a social license is how to meaningful involve patients and the public. If you involve patients and the public, but they only nod and say nothing, you can call it PPI, but it is not a meaningful involvement at all. That is why we are hammering on a meaningful strategy.

Ghislaine: We still are looking for best practices to do so and that is not easy, because most people are nowadays aware of the need that we need to involve stakeholders in what we do. But it is difficult to conceptualize how to do this. There is a lot of research done, there are a lot of initiatives, but really finding the best practice is still something that we are looking for. It is not easy to involve patients in a good way.

Many thanks for your insights on social license. It is clear you are paving the way in social license research, but also that there is still a lot of work to do. Could you already give some first hints on how responsible and sustainable research looks like with the insights you have gathered so far in BigData@Heart?

Shona: That is indeed the ultimate question we are working towards in BigData@Heart and deliver at the end the project. All the parts we mentioned are a little piece of the puzzle, because a governance framework or a responsible sustainable governance, that is big. It involves so many elements that the five years we have in BigData@Heart to explore this might not be enough.

Ghislaine: We are looking at PPI, GDPR, ethical guidelines and so on, these items are building blocks. We are now taking on each of these building blocks and our goal is to integrate this in a governance framework. But we are not far enough with all these building blocks already to answer what the framework will look like in the end. Nevertheless, we have an idea of the different overall principles and guidelines that are important in a governance framework. In the end, all building blocks will be fitted into a view on what good governance of health data research entails. This is something to look forward to as one of the key outputs of Work Package 7 in BigData@Heart.

Published on: 07/10/2019