Clinical trials are an essential stage in any medical product reaching the market. But a well-known issue across the healthcare sector is low rates of candidate satisfaction with these trials. I think effective use of data visualisation can help product/service developers solve this long-standing attrition problem.
On average, 30% of patients leave clinical trials for non-clinical and avoidable reasons. Here are the top four:
The first thing to say here is that the above issues would almost completely evaporate if patient happiness was put at the centre of any clinical trial design, especially early on. The move towards ePRO (electronic patient-recorded outcome) platforms is only the first step in the right direction. The next question is how providers can communicate complex medical ideas or procedures in a way that a patient can not only understand, but also completely trust and feel involved in.
Bespoke or personalised data visualisations for trial candidates – with elements of automation, interactivity and even gamification – can address this challenge. Not only that, they can also contribute to more efficient and more reliable data collection. As an example, interactive calendars and data-centric support tools can offer additional levels of support and continued reassurance for trial patients, making them feel like human beings and not just another data point.
The fact is, the majority of patients who enrol in clinical trials want to contribute to scientific understanding and make real social impact happen. And their contribution should be recognised as such, especially the personal sacrifices they make along the way. By taking the time to make candidates feel valued and involved rather than an afterthought, patient-centric and data-led ePRO systems have the potential to re-define the clinical trial methodology. In doing so, the data works for everyone without compromising scientific integrity.
At infogr8, we’ve already started work on developing a patient-centric ePRO solution that can be easily adopted into existing clinical trials, or as a bespoke full-service package that covers not only patient interaction, but also internal data collection, security and visualisation needs, patient recruitment, and more.
This is just one example of how the effective adoption of data-centric visualisations can expedite scientifically validated change in medical practice. Data-led progress could also take the form of omnichannel data curricula, or a stand-alone interactive clinical trial comparison tool.
To me, this represents the final hurdle before the widespread adoption of data visualisation in healthcare. Pharmaceutical organisations stand to gain so much once they rethink their current strategies of cherry-picking educational objectives from disparate data sources and instead align their priorities more closely to HCP demand. On their side, too, HCPs stand to benefit from embracing the fact that dataviz is itself as trustworthy as the data that defines it.
After all, it’s exactly the same thing, just presented infinitely better.
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