This session in the London Global Cancer Week is going to be focusing on the various aspects of data management and data access, especially from an LMIC lens. My talk, along with that of my colleague, is going to be focusing on the challenges of good data management in clinical trials in resource-limited countries, like Pakistan.

What are the challenges of data management in clinical trials in resource-poor settings?

I would say that to understand these challenges it’s important that we firstly understand the context within which research operates in LMICs. So, of course, the context within LMICs is largely that most of these are underdeveloped or developing economies with a patchy healthcare infrastructure, so even healthcare access is very patchy and is not uniform across all sectors of the society. Then the capacity for health research, especially high-quality health research, in the form of trained personnel and dedicated research centres is again limited. Then the culture is not very pro-research. In many high volume centres the focus is on providing treatment rather than having research built in as a treatment response, which is how it should be. So that really limits not only the kind of research that is happening in low- and middle-income countries but also the quality of that research output also. 

If we look at it a little systematically, any research equity from a country depends on the health research profile of that country. So health research profile would mean that there are ways to prioritise what research happens, and then there are adequate resources to conduct that research in the form of logistics and infrastructure and human resource. Then a way to package that research through robust research networks and peer review journals. Finally, and most importantly, there needs to be evidence of that research on health-related policy and practice. 

So all of these areas are deficient in low- and middle-income countries. For instance, and if we talk specifically from a data lens, to prioritise health research you need your baseline data. For that you need robust national or regional disease registries. Most low- and middle-income countries don’t have those. Also, for any national action plan around a disease to work, whatever you plan is going to be based on your understanding of the problem. So the understanding of the problem again is patchy at best; it’s based on isolated, limited data that is collected from silos of sometimes research excellence that exist in such countries. But, again, most low- and middle-income countries lack the disease registries that can inform the research agenda from those countries.

It goes without saying that there is a limited potential to conduct that research in terms of our… I would probably use the word ability rather than potential, there’s a lot of potential, but the ability lags because we don’t have trained human resource, we struggle with bandwidth, we struggle with availability of computers, we struggle with availability of individuals who would be able to run those electronic data management systems. The world has moved on to e-research but for us, we are in a developmental phase, and in many cases we end up importing electronic data management systems that have been built elsewhere, catering to needs of a completely different context. So this leads us to adopt systems that are not responsive to our context and, hence, often not sustainable as well. 

Then, again, whatever research we do end up conducting, when it is conducted we need to have better mechanisms to ensure that the data that is being collected is accurate. But health data in low- and middle-income countries is being collected in variable ways, so you have both paper-based systems and electronic systems. Increasingly, the adoption of electronic medical records is increasing, but then the health literacy to understand the usage of those records, that is really variable. It’s improving, it has changed a lot in the last decade especially, ever since the revolution of big data and understanding of the importance of data has evolved globally, but we lag behind – we are not where we should be. So again, like I said, the importance of robust research networks who can package that research and put it up in those peer-reviewed journals where it gets the maximum visibility. Again, we don’t have those in many low- and middle-income countries, and then again access to published literature is also limited. There are open access journals now, the revolution of open access has really changed the accessibility for health research for researchers from resource-limited settings. But again, I would emphasise, it’s still not where it needs to be. There are walls behind which most high quality journals sit behind. So it’s not as accessible as it could be for populations which need it the most. 

Finally, and most importantly, because of all of this there is limited impact of our health output on our health related policy making. That, I would say, that we have to look internally for that because the decision makers, the healthcare decision makers, have limited commitment and perhaps at times a naivety towards this important aspect of evidence-based decision making. So I would say that, in a nutshell, these challenges exist for good data management in research; they exist at all levels of research planning and its conduct and its dissemination. 

What has been done so far to overcome these challenges?

What has changed in the last two decades especially is that not only has there been greater international funding that supports electronic data management system development in LMICs and its sustainability, but also there has been a shift off both funding agencies and international donor bodies to look at ways by which we can have research leadership from the South, and not have North-South collaborations where the South is just a data provider, and it is being utilised by researchers from high-income countries. So a lot has changed, the process has become more inclusive and it has led to many projects, especially, I would say, in diseases of poverty because that is a global priority area where, in many African countries, it has resulted in big data-sharing networks. It has also enhanced data governance in these regions. In Asia, again, this varies a lot from country to country. Some countries are ahead of others, but the change is surely and slowly coming. 

What does the future look like?

I think for Pakistan, especially, the biggest change has been that there’s a realisation amongst the research community that we need to come together and we need to collaborate firstly within ourselves, do a priority agenda setting of our own, especially in terms of our capacity. It’s extremely important that any regional or national research-based system that is developed is developed by our very own research community and is responsive to our own needs so it’s contextually relevant and hence more sustainable. It’s also very important that we don’t work in silos, we work not even at a national level but at a regional level, and we really pool data. It’s important that we… and people are slowly coming to that, people are slowly coming to a realisation that standardising case definitions and agreeing on data validation inputs is going to improve the accuracy and the quality of data in these data management systems, which is then going to improve the quality of research output from the country.

Anything you’d like to add?

One of the biggest challenges to all of these things happening has been a lack of sustainable capacity development in low- and middle-income countries. Although there has been a shift in funding bodies, they’re increasingly funding LMIC PIs; they are looking at built-in capacity development initiatives within the funding calls that they agree to fund. But it’s important that this is enhanced further, it is important that there’s greater emphasis on having leadership from LMICs for research grants so that any capacity development that comes to us doesn’t end with a project, or doesn’t end with us just being providers of data, but really leads us to developing our data management capacity in a more sustainable way.

Is there a programme for young oncologists to join to increase the research capacity?

So one thing that we have started very recently is with the Global Health Network at the University of Oxford. It’s a community of practice that enables research in every healthcare setting, and one of their knowledge-sharing activities is setting up knowledge hubs in different regions. So what we have done fairly recently is that we have joined their Asia knowledge hub, and we now have a Pakistan presence there. As part of that initiative, we have started working on our capacity and needs assessment for health research and setting up a cancer research network on that very portal so that those who work in oncology and wish to undertake cancer research can come together on a single platform, share ideas, work collaboratively and also enhance their capacity.

There are plans in place to have workshops and webinars and symposia, as well as some training, some form of degree awarding training programme, eventually that will look at our capacity, specifically of cancer research. So it has just started, this is one of the activities that has started, and then within Pakistan, the National Institute of Health have also started developing these diploma and some degree programmes towards health research. They are not targeted specifically towards oncology, but I think that the discourse towards our capacity development has started in Pakistan.