2021 brought with it continued uncertainty and chaos that impacted almost every industry in the world. The clinical trial landscape was no exception. However, amidst all of the hardship brought on by Covid-19 came new innovations and creative processes that adapted to a shifting landscape.
Crises often force creative thinking, and during these unprecedented times, life sciences companies worked to adjust their clinical trial data management processes and operations in order to streamline internal efforts and still deliver quality patient experiences.
For instance, the industry saw an increased adoption of decentralized clinical trial models, which enabled more patients to participate in studies and collect more types of data remotely. Additionally, as clinical trials began handling a greater volume of data, data management teams had to maximize their existing technologies and implement new ones in order to more effectively collect, analyze, and clean clinical data.
So, while clinical trial teams were primarily concerned with keeping trials on track this past year, 2022 will likely see the clinical trial data management field continue to evolve and enable researchers to do more with clinical data in a quicker, more cost-effective manner.
Let’s take a look back at what 2021 taught us about data management best practices within clinical trials and consider how it will inform the evolution of clinical trial data management as we head into the new year.
The Importance of True Clinical Research Data Management Professionals
It’s no secret that the rapid evolution of clinical data technology has enabled data managers, trial managers, and clinical operations professionals to better collect, analyze, and understand their data. But as the volume of data being generated continues to increase — with approximately 30% of the world’s data volume being generated by the healthcare industry — clinical trials still require human beings to own and control all of that data.
In the past year, we’ve seen just how important clinical research data management professionals are for efficient trial operations. While clinical and operational trial data management systems like elluminate® work to automate, centralize, simplify, and streamline data management processes, qualified individuals are still needed to maximize the value of these systems.
Today, data management professionals are a driving force behind how data management is carried out, acting more as technology consultants as opposed to behind-the-scenes data quality reviewers. From acquisition and analyses to data cleaning and statistical processes, data managers have increased influence over establishing clinical data strategies.
Needless to say, data management professionals will continue to be at the forefront of how clinical trial data management evolves in the coming years. This makes it all the more important to avoid data management churn within your organization and ensure your team members aren’t feeling burnt out or overburdened with their current responsibilities.
Patient-Centric, Decentralized Clinical Trials Take Center Stage
With the Covid-19 pandemic came the need for life science organizations to think differently about trial designs with many sites in hospital settings limiting access and availability of space and resources for research. Naturally, clinical and operational trial teams understood that embracing technologies to enable patients’ continued participation in trials was a must. But making this switch proved to be easier said than done.
Enabling remote patient participation meant trial administrators needed to use more data sources. The complexity and nuances of each data source coupled with the lack of technological infrastructure to support them meant clinical trial teams struggled to get a grip on effectively managing their data. Having to balance technological capabilities with the need to continually deliver satisfactory patient experiences left data and trial managers scrambling to implement solutions that would check all the boxes.
As decentralized and hybrid trials become more dependent on advanced technologies, organizations must take steps to embrace the transformation of traditional clinical processes. This new white paper walks through the key components of defining a data strategy that embraces digital transformation and helps companies prepare for the digitization of today’s clinical trials.