Publication Explainer: Routinely Collected Data for Randomized Trials: Promises, Barriers, and Implications

This week I had a new publication come out – hoorah! Told you that all the effort I put towards my 2017 goals would pay off eventually. In another post later on in the year I’ll explain what my experiences have been like as a co-author on a publication, as well as what it’s like to be a first author, but today I want to use this post as a starting point for a new series on my blog. I’ll add to this ‘Publication Explainer’ series whenever I have a new publication out, and these posts will be a place for me to answer 3 of the most common questions I’ve been asked by people around me (here I mean colleagues that haven’t worked in this field, other scientists, non-scientists.. basically anyone who doesn’t work in the same research area as I do).

What is routinely collected data?

When we’re taking about health, routinely collected data (RCD) refers to data that has been collected during routine practice – basically, the stuff that your doctor adds to your medical record. This could be height, weight, blood type, blood pressure, blood levels, drug dosages, symptom frequency… the list goes on. As technology improves, RCD can also refer to things like number of steps, time spent sitting down, time spent standing etc – the sorts of things that a fitness tracker collects.

Why should we use routinely collected data in trials?

Routinely collected data could enable us to do trials better; whether that means more cheaply, with reduced patient burden, with less work for the trial team, more quickly, more environmentally friendly.. whatever ‘better’ means. This area of research is of particular interest to me because I’m trying to solve the problem of poor recruitment to trials. Recruiting volunteers to take part in trials is difficult, and if we can somehow design trials that are integrated into existing care pathways so that patients don’t have additional clinic visits to go to, then problems with recruitment could be solved much more quickly. In theory, we could design a trial that is fully integrated into routine care – meaning that when you visit your doctor and they collect data from you, that data can go straight to the trial team without the need for the patient to come in to the clinic on a separate occasion, which is what usually happens in trials.
This has been done before, the most well-known trial being the Salford Lung Study. This pioneering study involved over 2,800 consenting patients, supported by 80 GP practices and 130 pharmacies in Salford and the surrounding Greater Manchester area. You can read more about it here.

Ease isn’t the only reason to use RCD in trials. There is a huge field of research into what we call ‘pragmatic trials’.

Every trial sits somewhere on a spectrum from ‘explanatory’ to ‘pragmatic’. ‘Explanatory’ being used to describe trials that aim to evaluate the effectiveness of an intervention (a drug, a device, a type of surgery, or a lifestyle intervention like an exercise or diet change) in a well-defined and controlled setting. ‘Pragmatic’ being used to describe trials that aim to test the effectiveness of an intervention in routine practice – i.e. some people might not take their tablets as directed, they’ll likely skip an exercise every now and again, they might forget to pick prescriptions up or get their doses mixed up – these trials reflect real life. The more pragmatic a trial is, the more likely that the results of that trial will then translate into the real world if/when the intervention is rolled out for public use. Using routinely collected data could help to ensure that trials are more pragmatic.

Why aren’t we already using routinely collected data in trials?

The idea of using routinely collected data in trials sounds perfect, right? Patients won’t have to go to clinic visits, trials will recruit more easily, therefore they’ll be completed faster and more cheaply, trials will be more pragmatic – why aren’t we already using RCD in trials?

If only it were that simple! Just because data are collected, doesn’t mean that researchers are able to access it, never mind access it in a useful format at the time that they need it. There are lots of concerns about using RCD in trials as standard, but these issues are likely to be overcome at some point in the future (as for time, that’s the big unknown – it could be 50 years, could be longer!). This is an exciting field of research, and one that I’ll be keeping a close eye on over the next few years.

BioMedCentral as a publishing group is open-access meaning that their publications are not hidden behind paywalls, if you’d like to read the full paper you can find it here.

I also wanted to flag up a blog post that Lars and Kim wrote to go along with the publication, essentially it’s a more condensed, relaxed and easy to understand version of the paper – you can read that here.

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4 thoughts on “Publication Explainer: Routinely Collected Data for Randomized Trials: Promises, Barriers, and Implications

  1. heidirgardner

    Hi Amy, sorry it’s taken me ages to reply – I just saw your comment! Thanks for sharing the paper, great to hear it will be helpful to you and your colleagues. The writing collaboration came about after Evidence Live 2017, I remember you being at the workshop that I presented at with Lars Hemkens? Basically, my PhD Supervisor Prof Shaun Treweek knows Lars, Lars asked if he could present with him, but I was going to Evidence Live anyway, so it went to me. The discussions we had at the workshop, and afterwards within our own teams, were really helpful and led Kim & Lars to put together a basic draft of the paper. They then reached out to a group of us (Shaun and myself included) to comment on specific bits of the paper. We were particularly interested in how RCD could/would impact on recruitment, feasibility and other methodological issues. It’s been a brilliant collaboration so far – I think we’ve all learned from each other which is great. Hopefully more to work to come!

    Like

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