DATA MANAGEMENT TECHNOLOGY &
something with technology, does not mean that we will. Digital transformation is difficult and largely depends not just on the capabilities of new technology, but on our ability to move from the old world to the new.
Adopt a solution When we adopt new technology solutions, we typically deploy systems that take existing business processes and enhance them or make them more efficient – or both. In many of these cases, technology provides such a powerful replacement to the status quo that it is rapidly embedded in organisations. The first piece of technology is joined by the second, the third and so on, and then more technology springs up to help connect all of these different pieces together. Before we know where we are, we have a collection of technologies that accurately represent our business processes and provides a bunch of ancillary benefits.
“As the industry moves to fully embracing new paradigms of research, redesigned technology architectures are emerging that enables innovation rather than inhibiting it. These systems separate out functionality from underlying data, with that underlying data available to all applications that can use it.”
Organisations usually get great value from their
technology investments. However, no matter how good a piece of technology is when it is deployed, its unlikely to be the best choice forever and each component usually only represents a tiny part of the overall business problems that the organisation is trying to address. Culture changes, business conditions change, regulations are introduced and now our patchwork of technologies is no longer fully fit for purpose. Yet this intricate web of technology we have built becomes ossified, and is remarkably difficult and costly to unravel. In IT circles, this is known as technical debt – a penalty that must be paid to create new and better technology solutions. To solve this problem, we often install the ultimately
flexible technology – the human being – to deal with the new inadequacies. People are employed to check, modify or add to data within systems, or translate information in one system to another. This continues until the situation is untenable and, finally, we start all over again. In the world of clinical research, we have taken
steps that have actually made the problem worse. When we have adopted new systems, we have missed the opportunity to reimagine the value that they bring and, instead, have taken the easier path of adopting electronic instantiations of paper-based systems that date back decades. In other cases, we have adopted technology suites that claim to reduce technical debt by simply being ‘the system that does it all’. But doing it all doesn’t necessarily equate to doing it best; we can finish installing a suite on a Friday, only to find a new solution on the Monday to supplement it, starting the problem all over again.
Transform clinical research As the industry moves to fully embracing new paradigms of research, redesigned technology architectures are emerging that enables innovation rather than inhibiting it. These systems separate out functionality from underlying data, with that underlying data available to all applications that can use it. Swapping in and out a new piece of functionality can be almost as simple as replacing a Lego brick. As we think of new uses for data – such as next-generation patient registries – the industry should be thinking of them as new views into the data we have, rather than copying and repackaging data for a different purpose. We should not have to build out new representations of data once we discover a new piece of data or metadata is important. We also do not need to develop entirely new systems when we discover that the volume of data we need is greater than before. The fact that data fidelity and data volume will increase is not unexpected, so we need to design our systems with the flexibility to cope with those changes. As challenging as technical debt is, it can
ultimately be solved by investment and the adoption of new technology architectures designed to minimise it going forward. But clinical research will not truly be transformed until we address two more intractable problems, which can be thought of as organisational and ecosystem debt. Just as webs of technology
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