The wealth of data we have available to us has the potential to predict what treatment works best for us; but can this method really change the way we do trials? A new review paper sheds light on how big data could transform the use of real-world evidence in healthcare, and the barriers that we may come up against as a result.
This work was led by Kimberley Alba McCord and Lars G Hemkens from the Basel Institute for Clinical Epidemiology and Biostatistics, with contribution from HSRU’s Prof Shaun Treweek and PhD Student Heidi Gardner.
Most people are familiar with routinely collected data; these days everything from electronic medical records to population registries and Fitbits hold valuable information that could help researchers to predict how people will respond to different healthcare interventions.
There is a lot of excitement surrounding use of these kinds of data because it could help to enable collection of real-world evidence, facilitating more pragmatic trials. Some researchers have even said that that using routinely collected data will be the “next disruptive technology in clinical research”.
In reality, researchers often experience significant barriers to obtaining data, accessing it in a useful format, and/or ensuring that the data is accurate. Just because the data is present, doesn’t mean that it’s easy for us to get it how we want it and when it is required.
This new review paper, published in the Trials journal, provides researchers with a comprehensive look at what routinely collected data can realistically enable us to do, where the potential barriers are for those looking to use it, and the methodological implications and potential biases that could be introduced. Importantly, the paper also offers possible solutions and actions that provide researchers with a means to overcome many of these challenges.
For more information click here to read the paper.